POSTAL REGULATORY COMMISSION

Flats Operations Study 

Report

April 6, 2023

Postal Regulatory Commission

Submitted 4/6/2023 2:16:57 PM

Filing ID: 124853

Accepted 4/6/2023
TABLE OF CONTENTS

Page

EXECUTIVE SUMMARY.......................................................................................................................................1

CHAPTER I. PURPOSE AND SCOPE OF THE FLATS STUDY ..................................................................4

A. Section 206 of the Postal Service Reform Act of 2022...............................................4

B. Summary of the Report..........................................................................................................4

CHAPTER II. BACKGROUND..............................................................................................................................6

A. Flats Volume and Financial Performance .......................................................................6

1. Financial Performance in FY 2021-FY 2022....................................................6

2. Financial Performance Over PAEA Era..............................................................8

B. Flats Commission Rules and Directives........................................................................ 16

1. ACD Recommendations & Directives .............................................................. 16

2. Reporting Requirements...................................................................................... 20

3. New Ratemaking Rules for Non-Compensatory Classes and Products

........................................................................................................................................ 21

4. FY 2021 ACD Directives and Recommendations ........................................ 22

CHAPTER III. CAUSES OF INEFFICIENCIES IN FLATS OPERATIONS............................................. 23

A. Introduction............................................................................................................................. 23

B. Analysis of Flats Operations at the Facility Level ..................................................... 24

1. Summary of the Preliminary Facility-Level Data Analysis...................... 24

2. Methodology for Selecting Facilities for Site Visits.................................... 31

3. Summary of the Site Visits................................................................................... 33

4. Common Causes of Inefficiencies (Analysis of Pinch Points)................. 38

5. Summary of Newly Identified Causes of Inefficiencies............................. 76

6. Impact of Facility Management Decisions on Efficiency: Case Studies

........................................................................................................................................ 81

C. Inefficiencies in Flats Collection and Processing: Data Analysis......................... 84

1. Bundle Breakage During Mail Preparation, Collection, and Bundle 

Processing.................................................................................................................. 84

2. Analysis of Productivity and Other Issues in Automated Flats 

Operations.................................................................................................................. 91

3. Analysis of Allied Operations............................................................................104

4. Low Productivity in Manual Sorting Operations ......................................105

D. Inefficiencies in Transporting and Delivery of Flats Mail: Data Analysis ......109

1. Transportation.......................................................................................................109

2. Last Mile Delivery .................................................................................................125

CHAPTER IV. IMPACTS OF DIFFERENT FACTORS ON FLATS COST............................................134

A. Impact of Volume Trends on Flats Cost......................................................................134
- ii -

1. Analysis of Volume Trends and Unit Attributable Costs at the Product 

Level for Non-Compensatory Flats Products .............................................134

2. Econometric Analysis of the Impact of the Decreasing Flats Volumes 

on Unit Cost.............................................................................................................142

B. Analysis of Flats Unit Costs for Major Functional Categories by Dependent 

Component.............................................................................................................................152

1. Overall Flats Unit Attributable Costs by Functional Category (Mail 

Processing, Delivery, Purchased Transportation, and Other).............155

2. Analysis of the Trends in Unit Attributable Costs by Major Functional 

Cost Category for Non-Compensatory Flats Products ............................162

C. Impact of Excess Capacity and Idle Time on Flats Sorting Operations...........182

1. “Excess Capacity” in Postal Service Operations ........................................182

2. Analysis of the Relationship Between Excess Capacity and Workhours 

in Flats Sorting Operations................................................................................188

D. Effects of Different Operational Factors and Certain Investment Decisions on 

Flats Cost.................................................................................................................................191

1. Cost Impacts of Bundle Breakage ...................................................................191

2. Impacts on Flats Transportation Costs.........................................................192

3. Impact on Last Mile/Delivery Costs...............................................................193

4. History of FSS Operations and Potential Impact of FSS 

Decommissioning on Flats Costs.....................................................................195

5. Potential Changes in Flats Operations and Costs Due to Sorting and 

Delivery Centers ....................................................................................................198

E. Impact of Methodological Changes on Unit Attributable Cost...........................200

1. Introduction ............................................................................................................200

2. Costing Methodology Impacts on Flats Unit Attributable Cost...........201

CHAPTER V. SUMMARY OF CONCLUSIONS...........................................................................................209

Appendix A—Flats Study Report Analysis

Appendix B—Acronyms and Abbreviations

Appendix C—Glossary
EXECUTIVE SUMMARY

Flat-shaped mail or “flats” refers to large envelopes, magazines, and other flexible, 

rectangular mail that meet certain criteria.

1 Service performance and operational efficiency 

for flats has historically been below that for other types of mail.

Section 206 of the Postal Service Reform Act (PSRA) required the Commission to conduct a 

Flats Operations Study (“Flats Study”) not later than 1 year after enactment of the Act:

2

(a) Flats Operations Study.—:

(1) In General.—The Postal Regulatory Commission, in 

consultation with the Inspector General of the United States 

Postal Service, shall conduct a study to—

(A) comprehensively identify the causes of

inefficiencies in the collection, sorting, transportation, 

and delivery of Flats; and

(B) quantify the effects of the volume trends, 

investments decisions, excess capacity, and operational 

inefficiencies of the Postal Service on the direct and 

indirect costs of the Postal Service that are attributable 

to Flats.

The Commission’s Flats Study identifies causes of inefficiencies in the collection, sorting, 

transportation, and delivery of flats. In addition, the Flats Study quantifies the effects of the 

volume trends, certain investment decisions, excess capacity, and operational inefficiencies 

of the Postal Service on costs that are attributable to flats. To carry out the Flats Study, the 

Commission collected and reviewed flats data provided by the Postal Service. Commission 

staff also visited Postal Service facilities over a period of 4 months (from July to October of 

2022), visited mailers’ facilities in November of 2022, contracted with an operations 

expert, and consulted with the Office of Inspector General.

The principal findings of this Flats Study are:

• In FY 2022, the cost coverage (revenue divided by attributable cost) for all flats 

products increased. However, unit attributable costs also increased for the majority 

of flats products.

1 A flat-shaped mailpiece must have one dimension that is greater than 6-1/8 inches high or 11-1⁄2 inches long or 1⁄4 inch thick and cannot be 

more than 12 inches high x 15 inches long x 3⁄4 inch thick. United States Postal Service, Publication 32, Glossary of Postal Terms, July 1, 2016, 

at 88, available at https://postalpro.usps.com/storages/2016-04/pub32_glossary.pdf.

2 Postal Service Reform Act of 2022, Pub. L. 117-108, § 206(a), 136 Stat. 1127 (2022), available at 

https://www.congress.gov/117/plaws/publ108/PLAW-117publ108.pdf.
Docket No. SS2022-1 - 2 -

• Since FY 2010, the total volume of all flats products has decreased by 43.4 percent

or an average of 4.6 percent annually.

• Six pinch points (as identified by the Commission in previous ACDs) continue to 

contribute to cost and service issues for flats: (1) bundle processing; (2) automated 

processing; (3) manual sorting; (4) allied operations; (5) transportation; and (6) last 

mile/delivery.

• Reported bundle breakage rates likely underestimate true bundle breakage because 

only bundles that break on bundle sorters are reported; however, bundles break, or

are treated as if they will break, during other processing stages.

• Bundle breakage often results in inefficient manual processing of individual flats.

• How bundles are prepared and presented to the Postal Service significantly impacts

bundle breakage rates. Better coordination between the Postal Service and mailers 

is necessary to improve bundle integrity.

• Due to the lack of machine counts and clocking errors, measurement of both 

workhours and volumes in manual flats sorting are unreliable. The lack of reliable 

volume or workhour data represents a tremendous loss of opportunity to track or 

use this data in any meaningful way.

• Lack of relevant data prevents effective communication between mailers, facility 

staff, and Postal Service Headquarters, inhibiting corrective action.

• Insufficient data, coupled with data quality issues, makes it difficult to assess the 

Postal Service’s ability to improve flats processing efficiency.

• The Postal Service does not always understand the sources of flats processing 

inefficiencies or track volumes that cause inefficient operations.

• Recent operational plans, such as decommissioning Flats Sequencing System (FSS)

machines and the creation of sorting and delivery centers (S&DCs), will likely 

impact flats costs.

The PSRA requires the Postal Service, within 6 months, either to develop and implement a 

plan to remedy each inefficiency identified in the Flats Study or else to provide an 

explanation as to why remedying such inefficiency is impracticable. Based on the findings 

of the Flats Study, the Commission provides the following suggestions to the Postal Service 

for consideration as it develops its plan. Specifically, the Postal Service should consider:

• Continuing the combination of increasing revenue and reducing costs until unit 

revenue exceeds unit attributable cost for each non-compensatory flats product.

• Continuing to study the causes, impacts, and ways to reduce bundle breakage; 

enhancing the reporting and tracking of bundle irregularities; and working with 

mailers to ensure corrective actions are implemented when irregularities are 

shared.
Docket No. SS2022-1 - 3 -

• Further assessing the quality of its data, particularly as it relates to volume, 

workhours, and productivity, and exploring cost effective ways to improve that

quality.

• Implementing initiatives to reduce mail processing costs.

• Identifying mail processing facilities with extreme (unusually high or low) 

productivity values and those with quarterly productivity values based on a large 

number of missing workhours or volume; targeting those sites to improve their 

reporting or explaining why the provided productivity is accurate for a given 

facility.

• Developing an accurate method to track flat-shaped mail that is manually processed. 

Once there is an accurate measurement of such flat-shaped mail, the Postal Service 

should consider developing a specific plan to: (1) continue to decrease the quantity 

of flat-shaped mailpieces processed manually, and (2) achieve a proportional 

reduction in unit mail processing costs for manual operations.

• Including in its plan specific, achievable goals to reduce costs associated with allied 

operations, transportation, and delivery of flats.

• Quantifying the impact of any initiatives on costs to ensure its efforts are effective.

The Commission will continue to work with the Postal Service and the postal community to 

address these challenges.
Docket No. SS2022-1 - 4 -

CHAPTER I. PURPOSE AND SCOPE OF THE 

FLATS STUDY

A. Section 206 of the Postal Service Reform 

Act of 2022

Section 206 of the PSRA requires the Commission, in consultation with the Inspector 

General of the United States Postal Service, to conduct a Flats Operations Study (Flats 

Study). Pub. L. No. 117-108, § 206(a)(1), 136 Stat. 1127, 1148 (2022). A report on the 

findings of the study is due to Congress and the Postmaster General “[n]ot later than one 

year after the date of the enactment of this Act.” Id. § 206(a)(3). In accordance with this 

statutory requirement, the report is due by April 6, 2023.

The Flats Study includes two major parts. The first part involves analytical research and 

empirical studies to “comprehensively identify the causes of inefficiencies in the collection, 

sorting, transportation, and delivery of Flats.” Id. § 206(a)(1)(A). The second part involves 

formal data and quantitative analysis to “quantify the effects of the volume trends, 

investment decisions, excess capacity, and operational inefficiencies of the Postal Service 

on the direct and indirect costs of the Postal Service that are attributable to Flats.” Id. 

§ 206(a)(1)(B).

The Commission consulted with the USPS Office of Inspector General (OIG) through review 

of OIG audits related to manual processing, discussions regarding site visits, and periodic 

dialogue related to preliminary findings.

B. Summary of the Report

In the Executive Summary, the Commission presents its findings from the study in this 

report. In Chapter II, the Commission discusses the financial performance of flats since 

FY 2008 and summarizes actions taken by the Commission to increase transparency and 

assist the Postal Service in developing a comprehensive plan to improve flats service 

performance and cost coverage.

In Chapter III, the Commission analyzes common causes of inefficiencies in flats operations, 

using data provided by the Postal Service and observations from facility visits. The 

Commission also provides newly identified causes of inefficiencies and describes the 

impact of facility management decisions on efficiency.

In Chapter IV, the Commission analyzes the impact of different factors on flats costs. The 

Commission reviews volume trends, excess capacity, and operational factors. The 
Docket No. SS2022-1 - 5 -

Commission also analyzes flats costs for categories such as mail processing, delivery, and 

transportation.

Based on the Commission’s analysis, the Commission provides recommendations in 

Chapter V for the Postal Service to consider as it develops its plan to remedy these issues.
Docket No. SS2022-1 - 6 -

CHAPTER II. BACKGROUND

This chapter provides a brief history of the financial performance of flat-shaped mail and 

summary of Commission flats rules and directives.3

A. Flats Volume and Financial Performance

1. Financial Performance in FY 2021-FY 2022

The Postal Service has eight mail products that consist of more than 80 percent flat-shaped 

mail (flats products).4 As Figure II-1 shows, in FY 2021, five of these flats products did not 

generate sufficient revenue to cover their attributable costs:

5 First-Class Mail Flats, USPS 

Marketing Mail Flats, USPS Marketing Mail Carrier Route, Outside County Periodicals, and 

In-County Periodicals. These products are considered “non-compensatory,” while products 

whose revenues cover their attributable costs are considered “compensatory.”

Figure II-1

Compensatory and Non-Compensatory Flats Products, FY 20216

3 The Commission uses the terms “flats,” “flat-shaped mail,” and “flats products” interchangeably throughout this report.

4 These flats products span four Market Dominant mail classes: First-Class Mail, USPS Marketing Mail, Periodicals, and Package Services. See 

Figure II-1.

5 Prior to FY 2017, attributable cost of a product was defined as the sum of volume variable cost plus product specific cost. Due to 

methodological changes in FY 2017, attributable cost is now presented as the sum of “volume variable and product specific cost, plus the 

product’s inframarginal cost calculated as part of the estimation of the product’s incremental cost.” Docket No. ACR2017, United States Postal 

FY 2017 Annual Compliance Report, December 29, 2017, at 4 (FY 2017 ACR). Computationally, the attributable cost of each individual product 

should match the incremental cost of the same product. Id.

6 Source: Docket No. ACR2021, Annual Compliance Determination, March 29, 2022, at 229 (FY 2021 ACD).

Compensatory Flats Products

USPS Marketing Mail:

High Density and Saturation Flats and Parcels

Every Door Direct Mail—Retail

Package Services:

Bound Printed Matter Flats

Non-Compensatory Flats Products

First-Class Mail

Flats

USPS Marketing Mail

Carrier Route

Flats

Periodicals

In-County

Outside County
Docket No. SS2022-1 - 7 -

In FY 2022, the cost coverage (revenue divided by attributable cost) of all flats products 

increased. See Table II-1. In FY 2021, new rate authorities were introduced that allowed the 

Postal Service more pricing flexibility.7 Since many of the rate increases that used these 

new authorities were not implemented until the end of FY 2021, their impact on the cost 

coverage of flats products did not occur until FY 2022. In the instant report, a product is

classified as non-compensatory if its revenue did not cover its attributable cost in FY 2021

(the year prior to the issuance of the PSRA). For this reason, First-Class Mail Flats is among 

non-compensatory products even though the product was compensatory in FY 2022 and in 

all the PAEA years prior to FY 2021.

Table II-1

Cost Coverage of Flats Products, FY 2021–FY 20228

FY 2021 FY 2022 Change

Compensatory

USPS Marketing Mail Every Door Direct Mail—Retail 248.3% 263.9% 15.6%

USPS Marketing Mail High Density and Saturation Flats and Parcels 125.4% 132.5% 7.0%

Package Services Bound Printed Matter Flats 117.3% 124.7% 7.4%

Non-Compensatory

First-Class Mail Flats 98.9% 108.8% 9.9%

USPS Marketing Mail Carrier Route 94.6% 99.4% 4.8%

USPS Marketing Mail Flats 60.3% 66.7% 6.4%

Outside County Periodicals 53.9% 61.9% 8.1%

In-County Periodicals 45.0% 49.1% 4.1%

Note: All numbers in all tables are rounded.

Cost coverage improved for each flats product in FY 2022. However, as shown in Table II-2, 

the unit attributable costs have also increased for all but three flats products: (1) USPS 

Marketing Mail Every Door Direct Mail—Retail (EDDM-R), (2) Outside County Periodicals;

and (3) In-County Periodicals. Therefore, part of the overall improvement in cost coverage 

is due to an increase in revenue rather than a decrease in attributable cost, and therefore 

primarily due to the new rate authorities. In addition, as shown in Section IV.B.2., the 

repeal of the requirement that USPS annually prepay future retirement health benefits has 

7 See Docket No. RM2017-3, Order Adopting Final Rules for the System of Regulating Rates and Classes for Market Dominant Products, 

November 30, 2020 (Order No. 5763).

8 Source: See Docket No. ACR2021, Library Reference USPS-FY21-1, Public Cost and Revenue Analysis (PCRA) Report, December 29, 2021, PDF 

file “USPS-FY21-1 Preface.CRA.Report.pdf”(FY 2021 Public CRA Report); Docket No. ACR2022, Library Reference USPS-FY22-1, Public Cost and 

Revenue Analysis Report (PCRA), December 29, 2022, PDF file “USPS-FY22-1 Preface.PCRA.Report.pdf” (FY 2022 Public CRA Report).
Docket No. SS2022-1 - 8 -

had a one-time exogenous effect of dampening increases in unit attributable cost in 

FY 2022.

Table II-2

Unit Attributable Costs ($) of Flats Products, FY 2021–FY 20229

FY 2021 FY 2022 % Change

Compensatory

USPS Marketing Mail Every Door Direct Mail—Retail 0.078 0.075 -3.0%

USPS Marketing Mail High Density and Saturation Flats and Parcels 0.143 0.143 0.3%10

Package Services Bound Printed Matter Flats 0.658 0.696 5.7%

Non-Compensatory

First-Class Mail Flats 1.326 1.340 1.0%

USPS Marketing Mail Carrier Route 0.286 0.306 7.0%

USPS Marketing Mail Flats 0.717 0.722 0.7%

Outside County Periodicals 0.514 0.494 -3.9%

In County Periodicals 0.242 0.241 -0.3%

2. Financial Performance Over PAEA Era11

Prior to the new rate authorities, the cost coverage of both compensatory flats products 

and non-compensatory flats products had been falling consistently since FY 2016. This is 

shown in Figure II-2 and Figure II-3.

9 Source: See FY 2021 Public CRA Report; FY 2022 Public CRA Report.

10 While the dollar-denominated unit attributable cost for USPS Marketing Mail High Density and Saturation Flats and Parcels does not appear 

to change, this is only due to rounding all unit costs to three digits.

11 “PAEA Era” refers to the period of time impacted by the enactment of the Postal Accountability and Enhancement Act (PAEA) in 2006. See

Pub. L. 109-435, 120 Stat. 3198 (2006). Since most key PAEA provisions were implemented in December 2007, this report refers to “PAEA Era” 

as FY 2008 through FY 2022.
Docket No. SS2022-1 - 9 -

Figure II-2

Cost Coverage of Compensatory Flats Products, FY 2008–FY 202212

Note: EDDM-R was introduced in FY 2013 so there is no data prior to this year.

12 Source: See Docket No. ACR2022, Library Reference PRC-LR-ACR2022-1, March 29, 2023; Docket No. ACR2021, Library Reference PRC-LRACR2021-1, March 29, 2022; Docket No. ACR2020, Library Reference PRC-LR-ARC2020-1, March 29, 2021; Docket No. ACR2019, Library 

Reference PRC-LR-ACR2019-1, March 25, 2020; Docket No. ACR2018, Library Reference PRC-LR-ARC2018-1, April 12, 2019; Docket No. 

ACR2017, Library Reference PRC-LR-ACR2017-1, March 29, 2018; Docket No. ACR2016, Library Reference PRC-LR-ACR2016/1, March 28, 2017;

Docket No. ACR2015, Library Reference PRC-LR-ACR2015-1, March 28, 2016; Docket No. ACR2014, Library Reference PRC-LR-ARC2014-1, March 

27, 2015; Docket No. ACR2013, Library Reference PRC-ACR2013-LR1, March 27, 2014; Docket No. ACR2012, Library Reference PRC-ARC2012-LR1, March 28, 2013; Docket No. ACR2011, Library Reference PRC-ACR2011-LR-1, March 28, 2012; Docket No. ACR2010, Library Reference PRCARC2010-LR-1, March 29, 2011; Docket No. ACR2009, Library Reference PRC-ACR2009-LR-1, March 29, 2010; Docket No. ACR2008, Library 

Reference PRC-ARC2008-LR-1, March 30, 2009.

0%

50%

100%

150%

200%

250%

300%

350%

400%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Cost Coverage

Bound Printed Matter Flats

USPS Marketing Mail Every Door Direct Mail--Retail

USPS Marketing Mail High Density and Saturation Flats and Parcels
Docket No. SS2022-1 - 10 -

Figure II-3

Cost Coverage of Non-Compensatory Flats Products, FY 2008–FY 202213

Both First-Class Mail Flats and Carrier Route Flats were compensatory until recently. 

First-Class Mail Flats became non-compensatory for the first time in FY 2021, while Carrier 

Route Flats has not covered its cost since FY 2019. With the new rate authorities, the cost 

coverage for First-Class Mail Flats improved to 108.8 percent and the cost coverage for 

Carrier Route Flats improved to 99.4 percent in FY 2022.

USPS Marketing Mail Flats and both Periodicals products have not covered their 

attributable costs since FY 2008. The cost coverage of these products had been relatively 

steady from FY 2010 through FY 2016 (around 82 percent for USPS Marketing Mail Flats 

and 75 percent for each Periodicals product) but steadily declined since FY 2016 until the 

new rate authorities were exercised in FY 2021.

While cost coverage highlights a product’s individual performance, the product’s overall 

contribution to institutional costs (contribution) provides insight to its importance in the 

Postal Service’s financial position. A product’s overall contribution is defined as the 

product’s total revenue minus its total attributable cost. For example, USPS Marketing Mail 

13 Source: See Docket No. ACR2022, Library Reference PRC-LR-ARC2022-1; Docket No. ACR2021, Library Reference PRC-LR-ACR2021-1; Docket 

No. ACR2020, Library Reference PRC-LR-ARC2020-1; Docket No. ACR2019, Library Reference PRC-LR-ACR2019-1; Docket No. ACR2018, Library 

Reference PRC-LR-ARC2018-1; Docket No. ACR2017, Library Reference PRC-LR-ACR2017-1; Docket No. ACR2016, Library Reference PRC-LRACR2016/1; Docket No. ACR2015, Library Reference PRC-LR-ACR2015-1; Docket No. ACR2014, Library Reference PRC-LR-ARC2014-1; Docket No. 

ACR2013, Library Reference PRC-ACR2013-LR1; Docket No. ACR2012, Library Reference PRC-ARC2012-LR-1; Docket No. ACR2011, Library 

Reference PRC-ACR2011-LR-1; Docket No. ACR2010, Library Reference PRC-ARC2010-LR-1; Docket No. ACR2009, Library Reference PRCACR2009-LR-1; Docket No. ACR2008, Library Reference PRC-ARC2008-LR-1.

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Cost Coverage

First-Class Mail Flats Carrier Route Flats Marketing Mail Flats

In County Periodicals Outside County Periodicals
Docket No. SS2022-1 - 11 -

EDDM-R consistently has higher cost coverage than other flats products. However, because 

both the unit attributable cost and the price are low, the unit contribution is low. This, 

coupled with low volume results in a small overall contribution. Similarly, the Bound 

Printed Matter (BPM) Flats product is covering its attributable cost but has a very low 

contribution. The only flats product that has a significant positive contribution is USPS 

Marketing Mail High Density and Saturation Flats and Parcels.

As shown in Figure II-4, the total contribution of all flats products has been negative since 

FY 2018.14 This appears to be largely due to a decline in the overall contribution of 

First-Class Mail Flats and Carrier Route Flats as their volumes fall. Until recent years, both 

of these products had a significant positive contribution. In FY 2008, First-Class Mail Flats 

and Carrier Route Flats together had a positive contribution of more than $2.4 billion,

which helped generate a net positive contribution of more than $3.1 billion for overall flats 

products. The net negative contribution of flats products in the last five years is also due to 

an increase in the negative contribution of USPS Marketing Mail Flats and Outside County 

Periodicals. At its lowest point in FY 2021, flats products had a net negative contribution of 

more than $1.29 billion. In FY 2022, there was a significant improvement in flats 

contribution, which cut the net negative contribution of flats products to $614 million.

14 The numbers above the bars represent the total contribution of all flats products for a given fiscal year.
Docket No. SS2022-1 - 12 -

Figure II-4

Combined Contribution of Flats Products, FY 2008–FY 202215

The decline in contribution is, in large part, driven by both a steady decline in total volume 

and an increase in unit attributable cost. See Figure II-5. Unit cost in this figure has been 

adjusted for inflation using FY 2021 as the base year. Total volume of all flats products has 

fallen by approximately 4 to 6 percent on average each year since FY 2016, except between 

FY 2019 and FY 2020, when volume fell by 14 percent. See Figure II-5.

Total unit attributable cost for all flats products combined has been steadily increasing 

since FY 2014, even when adjusted for inflation.16

15 Source: See Docket No. ACR2022, Library Reference PRC-LR-ARC2022-1; Docket No. ACR2021, Library Reference PRC-LR-ACR2021-1; Docket 

No. ACR2020, Library Reference PRC-LR-ARC2020-1; Docket No. ACR2019, Library Reference PRC-LR-ACR2019-1; Docket No. ACR2018, Library 

Reference PRC-LR-ARC2018-1; Docket No. ACR2017, Library Reference PRC-LR-ACR2017-1; Docket No. ACR2016, Library Reference PRC-LRACR2016/1; Docket No. ACR2015, Library Reference PRC-LR-ACR2015-1; Docket No. ACR2014, Library Reference PRC-LR-ARC2014-1; Docket No. 

ACR2013, Library Reference PRC-ACR2013-LR1; Docket No. ACR2012, Library Reference PRC-ARC2012-LR-1; Docket No. ACR2011, Library 

Reference PRC-ACR2011-LR-1; Docket No. ACR2010, Library Reference PRC-ARC2010-LR-1; Docket No. ACR2009, Library Reference PRCACR2009-LR-1; Docket No. ACR2008, Library Reference PRC-ARC2008-LR-1.

16 This trend does not continue in FY 2022. From FY 2021 to FY 2022, unit attributable cost for all flats products combined increased by only 

0.11 cents in nominal terms, which was a 2.5 cent decrease in real terms (due to a 7.9 percent inflation rate).

3,155

2,078

1,550

1,291 1,318 1,783

1,963

1,340

1,036

434

-78

-576

-1,081 -1,291

-614

-2,000

-1,000

0

1,000

2,000

3,000

4,000

5,000

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Contribution (millions)

Carrier Route Flats FCM Flats EDDM-R MM Flats

In-County Periodicals Outside County Periodicals HD/SAT Flats/Parcels BPM Flats
Docket No. SS2022-1 - 13 -

Figure II-5

Total Flats Volume and Unit Attributable Cost, FY 2008–FY 202217

Table II-3 provides the percent change in volume since FY 2010 for each flats product 

individually, groups of compensatory and non-compensatory flats products, and total 

volume of all flats products combined. Since FY 2010, the total volume of all flats products 

combined has decreased by 43.4 percent, or an average of 4.6 percent annually.

18

Compensatory flats products have had a 19.7 percent decline in volume since FY 2010 

compared to the 54.7 percent decline in volume of non-compensatory flats products. This is 

because USPS Marketing Mail High Density and Saturation Flats and Parcels, which only 

17 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; Docket No. ACR2020, Library 

Reference USPS-FY20-1, Public Cost and Revenue Analysis (PCRA) Report, December 29, 2020, PDF file “USPS-FY20-1 Preface.CRA.Report.pdf”

(FY 2020 Public CRA Report); Docket No. ACR2019, Library Reference USPS-FY19-1, Public Cost and Revenue Analysis (PCRA) Report, December 

27, 2019, PDF file “USPS-FY19-1.pdf” (FY 2019 Public CRA Report); Docket No. ACR2018, Library Reference USPS-FY18-1, Public Cost and 

Revenue Analysis (PCRA) Report, December 28, 2018, PDF file “USPS-FY18-1 pdf” (FY 2018 Public CRA Report); Docket No. ACR2017, Library 

Reference USPS-FY17-1, Public Cost and Revenue Analysis (PCRA) Report, December 29, 2017, PDF file “USPS-FY17-1 Preface.pdf” (FY 2017

Public CRA Report); Docket No. ACR2016, Library Reference USPS-FY16-1, Public Cost and Revenue Analysis (PCRA) Report, December 29, 2016, 

PDF file “USPS-FY16-1 Preface.pdf” (FY 2016 Public CRA Report); Docket No. ACR2015, Library Reference USPS-FY15-1, Public Cost and Revenue 

Analysis (PCRA) Report, December 29, 2015, PDF file “USPS-FY15-1 Preface.pdf” (FY 2015 Public CRA Report); Docket No. ACR2014, Library 

Reference USPS-FY14-1, Public Cost and Revenue Analysis (PCRA) Report, December 29, 2014, PDF file “USPS-FY14-1.Preface.pdf” (FY 2014

Public CRA Report); Docket No. ACR2013, Library Reference USPS-FY13-1, Public Cost and Revenue Analysis (PCRA) Report, December 27, 2013, 

PDF file “Preface.FY13-1.Public.CRA.Rev.2-6-14.pdf” (FY 2013 Public CRA Report); Docket No. ACR2012, Library Reference USPS-FY12-1, Public 

Cost and Revenue Analysis (PCRA) Report, December 28, 2012, PDF file “REV_USPS-FY12-1.Preface.pdf” (FY 2012 Public CRA Report); Docket 

No. ACR2011, Library Reference USPS-FY11-1, Public Cost and Revenue Analysis (PCRA) Report, December 29, 2011, PDF file “USPS-FY11-1.pdf”

(FY 2011 Public CRA Report); Docket No. ACR2010, Library Reference USPS-FY10-1, Public Cost and Revenue Analysis (PCRA) Report, December 

29, 2010, document “USPS-FY10-1.doc” (FY 2010 Public CRA Report); Docket No. ACR2009, Library Reference USPS-FY09-1, Public Cost and 

Revenue Analysis (PCRA) Report, December 29, 2009, document “USPS-FY09-1.doc” (FY 2009 Public CRA Report); Docket No. ACR2008, Library 

Reference USPS-FY08-1, Public Cost and Revenue Analysis (PCRA) Report, December 29, 2008, document “USPS-FY08-1.doc”(FY 2008 Public 

CRA Report); U.S. Department of Labor, U.S. Bureau of Labor Statistics, available at https://www.bls.gov.

18 This calculation includes FY 2013 EDDM-R volumes in FY 2010 total flats volume since EDDM-R was not introduced until FY 2013.

-14%

-8%

-2% -3% 0.1% -4% -2% -3% -4% -4%

-5% -14%

-5%

-6%

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0

10,000

20,000

30,000

40,000

50,000

60,000

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Volume (millions)

Volumes Unit Cost (Real) Unit Cost (Nominal)
Docket No. SS2022-1 - 14 -

had a decline of 17 percent, makes up the majority of the volume of compensatory flats. 

The volume of non-compensatory flats is not significantly determined by a single product. 

The volumes of all flats products, other than USPS Marketing Mail High Density and 

Saturation Flats and Parcels have decreased at least 37 percent since FY 2010. USPS 

Marketing Mail Flats experienced the largest decline in volume (62.0 percent since FY 

2010). See Table II-3.

In FY 2010, the cumulative volume of the five non-compensatory products was more than 

twice as much as the total volume of the three compensatory products. See Table II-3. By 

FY 2022, however, the cumulative volume of the non-compensatory flats had substantially 

declined, and the volume share of these products was only 18 percent higher than that of 

compensatory flats products.19 Section IV.A.1. focuses on the volume and unit cost trends of 

non-compensatory flats because this decline in volume is dramatic, and these flats products 

collectively had a negative contribution of more than $1.7 billion in FY 2021.20

19 Note that while volume mix has shifted toward “compensatory” flats products, the products are categorized by whether they were

compensatory or non-compensatory in FY 2021. This means that First-Class Mail Flats and Carrier Route Flats, which were compensatory until 

recent years, are included in the non-compensatory group in this discussion. Because of this, a shift of volume mix toward “compensatory” 

products did not improve contribution, especially combined with unit attributable cost increases in both non-compensatory and compensatory 

flats products.

20 Commission calculations using data from Docket No. ACR2021, Library Reference PRC-LR-ACR2021-1, March 29, 2022, folder “PRC-LRACR2021-1,” Excel file “FY21 Summary LR-1.xlsx, tab “Total All Mail (Appendix A),” cells E23, E30, E32 E39, E40.
Docket No. SS2022-1 - 15 -

Table II-3

Volume by Product, FY 2010 and FY 202221

FY 2010 FY 2022 % Change

Compensatory

USPS Marketing Mail Every Door Direct Mail—Retail22 974,774,141 512,153,287 -47.0%

USPS Marketing Mail High Density and Saturation 

Flats and Parcels 11,363,444,416 9,440,570,824 -17.0%

Package Services Bound Printed Matter Flats 229,751,608 137,776,384 -40.0%

Total Compensatory 12,567,970,165 10,090,500,495 -19.7%

Non-Compensatory

First-Class Mail Flats 2,483,991,704 1,091,016,219 -56.0%

USPS Marketing Mail Carrier Route 9,473,616,956 4,718,228,310 -50.0%

USPS Marketing Mail Flats 7,067,654,358 2,693,530,387 -62.0%

Outside County Periodicals 6,574,014,264 2,965,609,879 -55.0%

In County Periodicals 695,455,322 434,754,069 -37.0%

Total Non-Compensatory 26,294,732,604 11,903,138,864 -54.7%

Total Flats 38,862,702,769 21,993,639,359 -43.4%

Table II-4 provides nominal unit attributable costs for non-compensatory flats products for 

FY 2010 and FY 2022. For comparison, the cumulative change in inflation from FY 2010 to 

FY 2022 was approximately 32 percent.23 Collectively, the unit attributable cost of noncompensatory flats products has increased by 51.3 percent while volume decreased by 

54.7 percent. Section IV.A.1. includes a more detailed discussion of volumes and unit 

attributable costs of individual non-compensatory flats products. Section IV.B. includes a 

detailed analysis of flats unit costs (overall and for each non-compensatory product) in 

mail processing, transportation, and delivery functional categories.

21 Source: Commission calculations using data from FY 2010 Public CRA Report and FY 2022 Public CRA Report for all products but one. For USPS 

Marketing Mail EDDM-R, the Commission uses data from FY 2013 Public CRA Report (since the FY 2013 was the first year when the product was 

introduced) and FY 2022 Public CRA Report.

22 For USPS Marketing Mail EDDM-R, this row represents FY 2013 volumes and percent change since FY 2013.

23 Commission calculations using data from the U.S. Department of Labor, U.S. Bureau of Labor Statistics, available at https://www.bls.gov.
Docket No. SS2022-1 - 16 -

Table II-4

Nominal Unit Attributable Cost ($) of Non-Compensatory Flats Products,

FY 2010 and FY 202224

FY 2010 FY 2022 Change % Change

Non-Compensatory

First-Class Mail Flats 0.865 1.340 0.475 55.0%

USPS Marketing Mail Carrier Route 0.165 0.306 0.140 84.9%

USPS Marketing Mail Flats 0.448 0.722 0.274 61.1%

Outside County Periodicals 0.364 0.494 0.130 35.9%

In County Periodicals 0.142 0.241 0.099 70.1%

Total Non-Compensatory Flats 0.357 0.539 0.183 51.3%

B. Flats Commission Rules and Directives

In analyzing the Postal Service’s challenges in processing and delivering flats profitably 

during the PAEA era, the Commission issued various recommendations, directives, 

reporting requirements, and rules to increase transparency and assist the Postal Service in 

developing a comprehensive plan to improve flats service performance and cost coverage.

1. ACD Recommendations & Directives

Since 2009, the Commission has consistently recommended in its ACDs that the Postal 

Service improve the financial performance of flats.25 In addition, the Commission has 

directed the Postal Service to provide information regarding operational changes for flats 

designed to reduce costs and improve costing methodologies in both Periodicals and USPS 

Marketing Mail Flats.26

24 Source: Commission calculations using data from FY 2010 Public CRA Report and FY 2022 Public CRA Report.

25 See Docket No. ACR2008, Annual Compliance Determination, March 30, 2009, at 54, 58-60 (FY 2008 ACD); Docket No. ACR2009, Annual 

Compliance Determination, March 29, 2010, at 65, 75, 87-89 (FY 2009 ACD); Docket No. ACR2010, Annual Compliance Determination, March 29, 

2011, at 93-94, 103-07 (FY 2010 ACD); Docket No. ACR2011, Annual Compliance Determination, March 28, 2012, at 106, 117-19 (FY 2011 ACD); 

Docket No. ACR2012, Annual Compliance Determination, March 28, 2013, at 89, 92-97, 109-16 (FY 2012 ACD); Docket No. ACR2013, Annual 

Compliance Determination, March 27, 2014, at 44-45, 53-55 (FY 2013 ACD); Docket No. ACR2014, Annual Compliance Determination, March 27, 

201, at 40-41, 47-48 (FY 2014 ACD).

26 The Commission also directed the Postal Service to make efforts to improve service performance for flats and explain why other efforts have 

not been effective. See FY 2014 ACD at 109.
Docket No. SS2022-1 - 17 -

a. USPS Marketing Mail Flats27

In the FY 2010 ACD, after 3 years of increasing negative contribution from USPS Marketing 

Mail Flats, the Commission determined that USPS Marketing Mail Flats prices in effect in 

FY 2010 did not comply with 39 U.S.C. § 101(d), and directed the Postal Service to increase 

the cost coverage of the USPS Marketing Mail Flats product through a combination of cost 

reductions and above-average price adjustments, consistent with the price cap 

requirements, until such time that revenues exceed attributable costs. FY 2010 ACD at 106. 

In addition, the Postal Service was directed to provide in each of its subsequent Annual 

Compliance Reports (ACRs) the following information: (1) a description of operational 

changes designed to reduce flats costs in the previous fiscal year and an estimation of the 

financial effect of such changes; (2) a description of all costing methodology or 

measurement improvements made in the previous fiscal year and estimated financial 

effects of such changes; (3) a statement summarizing the historical and current fiscal year 

subsidy of each flats product; and (4) the estimated timeline for phasing out this subsidy. 

Id. at 107. Consistent with the Commission’s directive, in subsequent Market Dominant 

price adjustments, the Postal Service was required to report the following information: (1) 

an explanation of how the proposed prices will move the flats cost coverage toward 100 

percent; and (2) a statement estimating the effect that the proposed prices will have in 

reducing the subsidy of the flats product.28

In its FY 2012, FY 2013, and FY 2014 ACDs, the Commission found that the Postal Service 

had made progress towards addressing the issues raised in the FY 2010 ACD and 

concluded that no additional remedial actions beyond those prescribed in the FY 2010 

directive were required.29

Cost coverage remained an issue for USPS Marketing Mail Flats. During FY 2015, the 

Commission stated that the Postal Service took several steps to address the continuing cost 

coverage shortfall, such as above-consumer price index (CPI) price increases and 

operational initiatives to reduce costs.30 However, the Commission found that the Postal 

Service did not fully comply with the FY 2010 directive and directed the Postal Service to 

continue to propose above-average price increases, reduce cost, and provide the required 

documentation of those efforts in future ACRs. FY 2015 ACD at 64. The Commission also 

recommended that the Postal Service take further action by preparing a report on flats. Id.

27 USPS Marketing Mail was previously known as Standard Mail. It was renamed on April 3, 2017. See 81 Fed. Reg. 93606 (Dec. 21, 2016).

28 Id. The Postal Service appealed the Commission’s FY 2010 ACD findings and directive. See USPS v. Postal Regul. Comm’n, 676 F.3d 1105 (D.C. 

Cir. 2012). Although the court rejected the Postal Service’s contention that the Commission acted outside the scope of its statutory authority, 

the court remanded the case to the Commission “for a definition of the circumstances that trigger [section] 101(d)’s failsafe protection, and for 

an explanation of why the particular remedy imposed here is appropriate to ameliorate that extremity....” USPS, 676 F.3d at 1109. In response, 

the Commission issued Order No. 1427, clarifying that its analysis of the circumstances that would trigger 39 U.S.C. § 101(d) depended on the 

totality of circumstances. Docket No. ACR2010-R, Order on Remand, August 9, 2012, at 4 (Order No. 1427).

29 See FY 2012 ACD at 116; FY 2013 ACD at 54; FY 2014 ACD at 47.

30 Docket No. ACR2015, Annual Compliance Determination, March 28, 2016, at 63 (FY 2015 ACD).
Docket No. SS2022-1 - 18 -

As cost coverage continued to decline in FY 2018, FY 2019, and FY 2020, the Commission 

again found USPS Marketing Mail Flats to be in violation of 39 U.S.C. § 101(d) and directed 

the Postal Service propose above-average price increases for USPS Marketing Mail Flats in 

applicable price adjustment proceedings.31

b. Periodicals

Like USPS Marketing Mail Flats, the Periodicals class (which includes two products that are 

both flats) has consistently failed to cover cost, and the Commission has repeatedly 

encouraged the Postal Service to improve Periodicals cost coverage.32 In FY 2010, the 

Commission worked with the Postal Service to produce the Periodicals Mail Study,33 in 

which the Commission and the Postal Service described initiatives designed to reduce the 

cost of flats, including, among others, reducing bundle breakage, enhancing pallet integrity, 

and lowering transportation costs. For a complete discussion of the initiatives, please see

Periodicals Mail Study at 81-99.

However, the trend of Periodicals failing to cover cost continued with the Commission later 

finding that “the Postal Service need[ed] to take further action to reverse Periodicals 

negative net revenue trend.” FY 2012 ACD at 18. The Commission directed the Postal 

Service to “leverage its pricing flexibility to improve Periodicals bundle and container 

pricing to incent more efficient mailer preparation and increase contribution from 

Periodicals.” Id. at 101.

In the FY 2013 ACD, the Commission found that the Postal Service was unable to report on 

the success of initiatives developed from the Periodicals Mail Study that were designed to 

lower the cost of Periodicals. FY 2013 ACD at 45. The Commission, therefore, required the 

Postal Service to quantify the financial impact of implementing the operational strategies 

outlined in the Periodicals Mail Study and develop metrics to track progress in subsequent 

ACRs. Id.

In the FY 2014 ACD, the Commission directed the Postal Service to provide a detailed 

analysis of the progress made in improving Periodicals cost coverage and report on:

• the impact of leveraging its pricing flexibility to improve the efficiency of Periodicals 

pricing;

31 See Docket No. ACR2018, Annual Compliance Determination, April 12, 2019, at 70-72 (FY 2018 ACD); Docket No. ACR2019, Annual Compliance 

Determination, March 25, 2020, at 42-43 (FY 2019 ACD); Docket No. ACR2020, Annual Compliance Determination, March 29, 2021, at 40-42 

(FY 2020 ACD).

32 See FY 2009 ACD at 75; FY 2010 ACD at 94; FY 2011 ACD at 105-106; FY 2012 ACD at 95-97; FY 2013 ACD at 44-45; FY 2014 ACD at 40-41; 

FY 2015 ACD at 50-51; Docket No. ACR2016, Annual Compliance Determination, March 28, 2017, at 47-48 (FY 2016 ACD); Docket No. ACR2017, 

Annual Compliance Determination, March 29, 2018, at 50 (FY 2017 ACD); FY 2018 ACD at 46; FY 2019 ACD at 25; FY 2020 ACD at 20.

33 Periodicals Mail Study, Joint Report of the United States Postal Service and Postal Regulatory Commission, September 2011 (Periodicals Mail 

Study). The Periodicals Mail Study responds to section 708 of the PAEA, which directs the Postal Service and the Commission to jointly address 

the quality of data for attributing costs and opportunities for operational efficiencies, including pricing incentives. See Periodicals Mail Study 

at 5.
Docket No. SS2022-1 - 19 -

• the progress in developing metrics to assess the cost savings impact of operational 

strategies;

• the impact of the implementation of operational strategies outlined in the 

Periodicals Mail Study; and

• the progress in implementing pricing strategies outlined in the Periodicals Mail 

Study.

FY 2014 ACD at 40.

After finding that the Postal Service failed to meaningfully address the directive to report 

on the progress in improving pricing efficiency, the Commission instructed the Postal 

Service to file a Periodicals Pricing Report that analyzes how pricing decisions impact cost, 

contribution, and revenue.34 The Postal Service filed updated versions of the Periodicals 

Pricing Report through FY 2021.35

c. FY 2015 Directive

Recognizing that obstacles to the improvement of cost coverage apply to both Periodicals 

and USPS Marketing Mail Flats, the Commission devoted an entire chapter in the FY 2015 

ACD to further explore potential causes for issues related to flats. FY 2015 ACD at 160. In 

that chapter, the Commission directed the Postal Service to take steps to better define the 

scope of the problems and potential solutions. See id. The Commission identified and 

analyzed six “pinch points” that contribute to cost and service issues for flats:

• Bundle processing,

• Automated processing,

• Manual sorting,

• Allied operations,

• Transportation, and

• Last mile/delivery.

FY 2015 ACD at 165-80. These pinch points are discussed in more detail in Sections III.B.1.

and III.B.4.

34 FY 2015 ACD at 23-24; see Docket No. ACR2015, Third Response of the United States Postal Service to Commission Requests for Additional 

Information in the FY 2015 Annual Compliance Determination, Report Responding to Periodicals Pricing Directives, July 26, 2016 (Docket 

No. ACR2015, Postal Service Third Response).

35 See Docket No. ACR2016, Library Reference USPS-FY16-44, December 29, 2016, PDF file “USPS-FY16-44.pdf;” Docket No. ACR2017, Library 

Reference USPS-FY17-44, December 29, 2017, PDF file “USPS-FY17-44 Preface.pdf;” Docket No. ACR2018, Library Reference USPS-FY18-44, 

December 28, 2018, PDF file “USPS-FY18-44 Preface.pdf;” Docket No. ACR2019, Library Reference USPS-FY19-44, December 27, 2019, PDF file 

“USPS-FY19-44.pdf;” Docket No. ACR2020, Library Reference USPS-FY20-44, December 29, 2020, PDF file “USPS-FY20-44 Preface.Report.pdf”

(Update to Periodicals Pricing Report); Docket No. ACR2021, Library Reference USPS-FY21-44, December 29, 2021, PDF file “USPS-FY21-44 

Preface.Report.pdf.”
Docket No. SS2022-1 - 20 -

Using data available at the time, the Commission identified and discussed flats cost and 

service issues for each individual pinch point. See FY 2015 ACD at 165-80. However, the 

Commission acknowledged that there was a “lack of comprehensive data,” which prevented 

the Postal Service and the Commission from measuring the impact of specific initiatives 

designed to improve cost and service issues for flats. Id. at 180.

The Commission directed the Postal Service to identify a method to measure, track, and 

report the cost and service performance issues relating to each individual pinch point 

identified by the Commission at the most granular level practicable. Id. at 181. To increase 

transparency, the Commission requested certain information in support of the identified 

method, such as:

• available data to support methods to measure, track, and report on cost and service 

issues related to flats,

• information on the cost to produce and aggregate current data,

• additional data that would be needed to support a method to measure, track and 

report on cost and service issues related to flats and the cost to produce that data, 

and

• the identification of information necessary to develop, implement, monitor, and 

quantify results for a comprehensive plan to improve flats service performance and 

cost coverage if an ideal data system were available.

Id.

In each subsequent ACD, the Commission continued to express concerns with the issues 

related to flats.36 The Commission also provided the Postal Service with recommendations 

specific to each pinch point and continued to call for the Postal Service to work to quantify 

the impact of its operational initiatives on costs to ensure its efforts were productive. See 

FY 2020 ACD at 236, 241; FY 2021 ACD at 228.

2. Reporting Requirements

In 2017, the Commission announced that it planned to initiate a strategic rulemaking to 

develop proposed reporting requirements related to flats operational cost and service 

issues. FY 2016 ACD at 171. The reporting requirements were to facilitate measuring, 

tracking, and reporting cost and service issues and also to explore potential enhancements 

to the Postal Service’s data systems.37 After reviewing additional information from the 

Postal Service regarding its data systems and capabilities, as well as comments from 

interested parties, the Commission finalized rules for the Postal Service to provide 

additional information to improve transparency into the cost and service performance 

36 See, e.g., FY 2016 ACD at 158-71; FY 2017 ACD at 174-82; FY 2018 ACD at 213-23; FY 2019 ACD at 155-75; FY 2020 ACD at 236-62.

37 Docket No. RM2018-1, Advance Notice of Proposed Rulemaking to Develop Data Enhancements and Reporting Requirements for Flats Issues, 

October 4, 2017, at 1 (Order No. 4142).
Docket No. SS2022-1 - 21 -

issues, as well as increase the accountability of the Postal Service related to flats 

operational initiatives.38

These reporting requirements seek information readily available and previously provided 

or proposed by the Postal Service, based on filings by the Postal Service in the FY 2015 

ACD, the FY 2016 ACD, the FY 2017 ACD, and Order No. 5004 at 8. The information falls 

into four categories: (1) analysis of consolidated cost and service data; (2) analysis of costs 

by operationally relevant groupings; (3) analysis of data related to individual pinch points; 

and (4) analysis to estimate the impact of operational changes. Id. The Postal Service has 

provided the required information since the rules went into effect, and the Commission has 

analyzed the data in Chapter 6 of the FY 2019 ACD and Chapter VI of the FY 2020 ACD and

FY 2021 ACDs.

39

3. New Ratemaking Rules for Non-Compensatory 

Classes and Products

In addition to directing above-average price adjustments and analyzing data in its ACDs, 

the Commission evaluated non-compensatory products in its statutory review of the 

ratemaking system. See 39 U.S.C. § 3622(d)(3). Based on this review, the Commission found 

that rates which failed to cover the attributable costs of the products or mail classes to 

which they applied undermined the Postal Service’s financial integrity and were 

unreasonable, and thus inconsistent with objectives 5 and 8 of section 3622(b)’s statutory 

objectives.40

To improve cost coverage for non-compensatory classes and products, the Commission 

adopted new regulations granting additional rate authority to non-compensatory classes 

and more strictly governing how rate authority must be used for non-compensatory 

products in compensatory classes. Order No. 5763 at 181-97. In particular, 39 C.F.R. part 

3030, subpart G permits an additional 2 percentage points of rate authority for any class of 

mail where the attributable cost for that class exceeds the revenue from that class. 39 C.F.R. 

§ 3030.222(a). The use of this additional rate authority is optional and may be 

implemented at the Postal Service’s discretion. Id. In addition, the regulations have 

requirements specific to products classified as non-compensatory within classes that are 

compensatory overall. For those products, the rates must increase by a minimum of 2 

percentage points above the average percentage increase for that class.41 The regulations 

also provide that rates may not be reduced for any non-compensatory product. Id. 

§ 3030.127(b).

38 Docket No. RM2018-1, Notice of Proposed Rulemaking for Reporting Requirements Related to Flats, March 1, 2019, at 7 (Order No. 5004); 

Docket No. RM2018-1, Order Adopting Final Rules on Reporting Requirements Related to Flats, May 8, 2019, at 2-3 (Order No. 5086).

39 FY 2019 ACD at 155; FY 2020 ACD at 236; FY 2021 ACD at 278.

40 Docket No. RM2017-3, Notice of Proposed Rulemaking for the System for Regulating Rates and Classes for Market Dominant Products, 

December 1, 2017, at 76 (Order No. 4258).

41 Id. § 3030.221. This requirement does not apply to a non-compensatory product for which the Commission has determined that the Postal 

Service lacks independent authority to set rates (such as rates set by treaty obligation). Id.
Docket No. SS2022-1 - 22 -

4. FY 2021 ACD Directives and Recommendations

The FY 2021 ACD was the first ACD to evaluate compliance under the new rules for 

non-compensatory products and classes. FY 2021 ACD at 8. The Commission found that the 

Periodicals class (In-County and Outside County), First-Class Mail Flats, USPS Marketing 

Mail Flats, and USPS Marketing Mail Carrier Route were non-compensatory in FY 2021. Id. 

at 26. The Commission stated that flats products lost $1.291 billion in FY 2021. Id. at 229.

In accordance with the rules, the Commission directed the Postal Service to increase the 

price for the non-compensatory products by at least 2 percentage points above the average 

percentage increase for that class.42 The Commission also encouraged the Postal Service to 

continue to maximize its usage of rate authority granted under 39 C.F.R. 3030.222 and to 

maximize its revenue by strategically pricing Periodicals. FY 2021 ACD at 31.

Furthermore, after analyzing Postal Service reports and finding that the Postal Service 

continued to face significant challenges in processing and delivering flats in a cost-effective 

manner, the Commission provided directives and recommendations to the Postal Service 

regarding specific plans to resolve both cost and service issues for flat-shaped products. 

FY 2021 ACD at 228. For example, the Commission recommended that the Postal Service 

continue to estimate and report the additional cost that bundle breakage adds to flats 

processing. FY ACD 2021, Appendix A at 23. In addition, the Commission required the 

Postal Service to implement initiatives to reduce mail processing costs and to develop an 

accurate method to track flat-shaped mail that is manually processed. Id. The Commission 

also directed the Postal Service to develop plans to reduce costs associated with allied 

operations, and to reduce costs associated with transporting and delivering flats. Id. 

at 23-24.

The Commission continued to express its concerns regarding the financial performance of 

flats products in its FY 2022 ACD.43 Finding that its past directives have, to a large extent, 

been eclipsed by recent regulatory changes, the Commission rescinded those past 

directives related to USPS Marketing Mail Flats and USPS Marketing Mail Carrier Route for 

FY 2023. FY 2022 ACD at 48-49. In addition, the Commission urged the Postal Service to 

continue to pursue revenue increases and cost reduction efforts in order to improve the 

financial performance of non-compensatory flats products. Id. at 36, 48-49, 52-53.

42 See, e.g., FY 2021 ACD at 49, 61, 65; 39 C.F.R. § 3030.221.

43 Docket No. ACR2022, Annual Compliance Determination, March 29, 2023, at 28-53 (FY 2022 ACD).
Docket No. SS2022-1 - 23 -

CHAPTER III. CAUSES OF INEFFICIENCIES

IN FLATS OPERATIONS

A. Introduction

For years, in response to statutory requirements and Commission directives, the Postal 

Service has been designing and implementing operational and pricing initiatives, but the 

Postal Service “has been unable to [either] quantify the expected impact of those 

operational initiatives and changes” or “isolate those impacts to specific products.” FY 2021 

ACD at 31, 60. The Commission has previously identified multiple factors that likely 

contributed to the steady increase in the unit cost and decrease in contribution of flats (e.g.,

bundle breakage, inefficiency of manual sorting, and low productivity of automated 

equipment). See FY 2015 ACD at 165.

Commission staff visited a number of Postal Service’s and mailer’s facilities. To analyze the 

causes of inefficiencies more thoroughly, and potentially identify new factors in addition to 

the previously discussed inefficiency factors within “pinch points,” Commission staff visited 

Postal Service operational facilities in the period between July and October of 2022.

44 To 

understand the full cycle of flats mail operations (including collection, sortation, 

transportation, and delivery of flats), Commission staff visited postal facilities of different 

types as well as mailer’s facilities. To learn more about facility-specific differences in postal 

operations, Commission staff visited facilities with different levels of productivity, low and 

high rates of bundle breakage and different levels of processed volume (e.g., small, medium, 

and large). It took approximately 4 months to complete the field work at the postal 

facilities. Parallel to the field work, the Commission reviewed flats data provided by the 

Postal Service in prior ACRs as well as additional and more detailed data requested through 

information requests in Docket No. SS2022-1. The Commission also contracted with an 

expert in postal operations to assist the Commission in interpreting information gathered

during the site visits. This chapter summarizes what the Commission learned about flats 

operations from the facility visits and evaluates the major factors contributing to 

inefficiencies in flats operations.

44 For the purposes of carrying out the Flats Study, the Postal Service shall provide “A) access to Postal Service facilities to personnel of the 

Postal Regulatory Commission and B) information and records necessary to conduct such study....” PSRA § 206(a)(2)(A).
Docket No. SS2022-1 - 24 -

B. Analysis of Flats Operations at the Facility 

Level

1. Summary of the Preliminary Facility-Level Data 

Analysis

a. Definitions of Pinch Points and Data Used for Analysis of 

These Pinch Points

The Commission receives a variety of flats-related datasets as part of its analysis of flats 

cost and service issues in the ACD.45 Each dataset corresponds with a “pinch point” 

operation originally identified by the Commission as part of the FY 2015 ACD. FY 2015 ACD 

at 165. Pinch points are “functions where the Postal Service is not operating at maximum 

efficiency from a cost or service perspective.” Id. The six pinch points that the Commission 

previously identified are: bundle processing, automated processing, manual sorting, allied 

operations, transportation, and last mile/delivery.46 These pinch points are briefly 

discussed below.

Bundle processing. Bundles are plastic-wrapped or banded groups of presorted mailpieces. 

FY 2015 ACD at 166. Presorted mail has been sorted by a mailer prior to being inducted 

into the mail system. A bundle of presorted mail can move through the processing system

as a single bundle until it reaches the destination postal facility to which it is sorted. In 

exchange for performing some of the work of presortation, the mailer receives a workshare 

discount. FY 2021 ACD at 14. The majority of flats require bundle sortation on bundle 

processing equipment. Inefficiency occurs when bundles break before they are processed 

at the destination postal facility. FY 2015 ACD at 166. When Postal Service employees 

unload pallets that contain bundles of flats and perform a bundle sort, the material holding 

the flats bundle can break. Id. at 166-67. When a bundle breaks, the Postal Service has to 

process individual mailpieces that were formerly bundled together, thereby increasing mail 

processing costs and diminishing or eliminating the value of presortation. Id. at 167. As 

discussed in detail in Section III.B.4.a., bundle breakage is directly linked to the quality of

the bundles, how they were presented to the Postal Service, the methods used to unload 

the bundles, and how they are handled during processing.

Automated processing. Individual flats mailpieces are sorted on Automated Flats Sorting 

Machines (AFSMs) and FSS machines. During automated processing on these machines, the 

Postal Service does not always achieve high levels of productivity. Productivity for these 

machines has been declining. See FY 2021 ACD at 249. As productivity declines, the cost 

efficiency of Postal Service’s operations also declines. Productivity in processing operations

45 See, e.g., Docket No. ACR2021, Library Reference USPS-FY21-NP31, December 29, 2021; Docket No. ACR2021, Library Reference USPS-FY21-

45, December 29, 2021.

46 See FY 2015 ACD at 165; FY 2016 ACD at 158; FY 2017 ACD at 174; FY 2018 ACD at 213; FY 2019 ACD at 161; FY 2020 ACD at 244; FY 2021 ACD 

at 241-42.
Docket No. SS2022-1 - 25 -

is specifically referring to the units of output per unit of input: in this case, the number of 

mailpieces processed per workhour. Considering that productivity is a function of volume 

and workhours, it would be reasonable to assume that when higher volume is processed on 

a machine, productivity will be higher than machines that process lower volumes. 

However, previous Commission analysis has shown that there is no evidence to support the 

Postal Service’s theory that productivity decline is linked to volume declines. Id. at 255. As 

the Postal Service stated “[d]ifferences in productivities from plant to plant may arise due 

to a number of other factors—many of which are difficult or impossible to quantify.”47

Manual sorting. When compared with automated processing, manual processing tends to 

be more costly and time consuming. FY 2015 ACD at 171. Manual processing of flats is 

another pinch point because a relatively high percentage of flats (up to 7 percent) continue 

to be diverted to manual processing, resulting in higher costs and poorer service.48

Allied operations. These operations occur throughout the mail processing and delivery 

workflow. FY 2015 ACD at 173. Allied operations are mail processing activities that involve 

preparing the mail for pallet, bundle, or piece processing and include platform operations, 

such as unloading trucks and moving pallets to mail processing equipment. During allied 

operations, the Postal Service is not always achieving high levels of productivity. Id.

Declines in the productivity of allied operations can lead to increases in mail processing 

costs. Id.

Transportation. After flats are processed, they must be transported either to another mail 

processing facility for additional sortation or transported to a destination delivery unit 

(DDU) for delivery.49 The Postal Service generally transports all shapes of mail together. Id. 

Delayed arrivals, delayed departures, and some other factors decrease efficiency of 

operations in transportation.

Last mile/delivery. This function encompasses all activities related to last mile operations, 

when mailpieces arrive at the delivery unit, and involve in-office time (when carriers are in 

a delivery unit preparing and manually sorting mail prior to delivery) and street time 

(when carriers are on the street actually delivering mail). FY 2015 ACD at 177. As with 

transportation, there are a number of potential inefficiencies during last-mile operations.

The Commission developed the datasets for the instant study using data from multiple 

datasets provided by the Postal Service. For more details of the tools and methodology 

used, see Appendix A, Sections III.B.1. and III.B.2. Analysis. The final dataset developed by 

the Commission included the bundle breakage and automation processing data for each 

machine at each facility. Data was quarterly and spanned from FY 2016 through FY 2021.

Id.

47 Docket No. ACR2019 Status Reports at 6-7.

48 Id. See Responses of the United States Postal Service to Questions 1-4 of Chairman’s Information Request No. 7, January 26, 2023, question

2.b. (Response to CHIR No. 7).

49 Id. at 176. For purposes of the instant study, analysis of DDUs is limited to the analysis of delivery units, such as Post Offices.
Docket No. SS2022-1 - 26 -

b. Initial Analysis of Automated Operations at the Mail 

Processing Facilities

There are two types of mail processing facilities that sort mail on automated equipment:

(1) Processing and Distribution Centers (P&DCs) and (2) Network Distribution Centers 

(NDCs). A P&DC is “an organizational entity, subordinate to an area with a significant 

responsibility for the processing and distribution of mail for a geographic area. A P&DC 

may have one or more reporting facilities.”

50 An NDC is another “organizational entity, 

generally subordinate to an area, within a three-tier system of distribution of [USPS 

Marketing] Mail, periodicals, and packages. Some NDCs serve as consolidation points for 

truckload volumes.” Id. NDCs are generally larger than P&DCs. The Commission analyzed 

data on processed flats mail volumes, workhours, and productivity for flats operations at 

these facilities. Figures III-1 and III-2 present the FY 2021 flats volumes and workhours at 

the facility level for all facilities with AFSM and FSS machines. The Postal Service operated 

93 FSS machines in FY 2021, which is significantly fewer than the 407 AFSMs it operated in 

the same fiscal year. Volume measures the number of mailpieces processed on an AFSM or 

a FSS, respectively. Workhours are hours of work performed by mail clerks. The color of 

the dots in Figures III-1 and III-2 correspond to the level of labor productivity. On a more 

productive machine, the same (or larger) amount of volume can be processed during fewer 

workhours than on a less productive machine. Red dots correspond to machines that are 

highly productive while blue dots correspond to machines with low productivity.

Figure III-1

AFSM Volume and Workhours51

50 See United States Postal Service, ELM 53 -Employee and Labor Relations Manual, § 113.3, Sept. 2022, available at 

https://about.usps.com/manuals/elm/elmc1.pdf.

51 Source: Docket No. ACR2021, Library Reference USPS-FY21-NP31, December 29, 2021, Excel file “NONPUBLIC MP Variance FY17_21.xlsx."
Docket No. SS2022-1 - 27 -

Figure III-2

FSS Volume and Workhours52

As shown in Figures III-1 and III-2, volume and workhours have a strong relationship 

(correlation) for both AFSM and FSS machines.53 Correlation is a statistical term that 

identifies a relationship between two sets of observations (or two variables) when “no 

conclusions about causality can safely be made.”

54 A correlation coefficient that provides a 

measure of correlation “can range in value from -1.00 to +1.00,” where a correlation 

coefficient of +1.00 indicates a perfect positive relationship between two variables. Id. at 

125-26. In this context, there appears to be a strong relationship between volume and 

workhours (0.74 and 0.86, respectively).

Figures III-1 and III-2 illustrate that at the facility level, the relationship between volume 

processed on AFSM and FSS equipment and productivity is not strong. This is the issue that 

the Commission has discussed starting with its FY 2019 ACD.55 The Commission’s analysis 

of volume and productivity data performed within the instant study shows that there are 

more machines that do not process much flats volumes but still have high productivities

than machines that process high flats volume and also have high productivities. For 

example, the AFSM with the highest labor productivity processes 50 million pieces, which 

is 16 percent above the average volume for all AFSMs.

52 Source: Commission calculations using data from Docket No. ACR2021, Library Reference USPS-FY21-NP31, December 29, 2021, Excel file 

“NONPUBLIC MP Variance FY17_21.xlsx."

53 Commission calculations using data from Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “NONPUBLIC MP Variance 

FY17_21.xlsx."

54 S.K. Kachigan, Multivariate Statistical Analysis, A Conceptual Introduction, (2nd ed. 1991), at 4, 125.

55 See FY 2019 ACD at 167-68; FY 2020 ACD at 253; FY 2021 ACD at 251-55.
Docket No. SS2022-1 - 28 -

Figure III-2 illustrates that, for FSS, the correlation between volume and labor productivity 

is even lower. Some highly productive FSS machines process only 25 million pieces while 

others process 104 million pieces. See Figure III-2. For FSS machines that process more 

than 80 million pieces, there is a broad range of labor productivities. Both figures 

demonstrate that at higher volumes, there is a larger range of productivities.

The Commission’s analysis shows that the majority of AFSM productivities range from 

1,200 to 3,400 pieces per workhour. Although workhours for AFSMs generally increase 

when volumes increase, productivity levels might differ at different volume levels.

The majority of FSS productivities range from 1,300 to 2,100 pieces per workhour. 

Workhours for FSS machines also increase with volume, but there is a stronger correlation 

between volume and workhours for FSS machines than for AFSMs.

The Postal Service reported that from FY 2009 through FY 2021, USPS Marketing Mail Flats 

volume declined from 7.8 billion pieces to 2.9 billion pieces, and the overall AFSM 

productivity fell from 3,114 pieces per workhour to 1,951 pieces per workhour.56

Furthermore, between FY 2020 and FY 2021, AFSM and FSS productivity declined by 

approximately 3 and 4 percent, respectively. FY 2021 ACD at 52.

Figures III-1 and III-2 demonstrate that high volume facilities are not necessarily more 

productive with respect to workhours. Figures III-1 and III-2 also demonstrate that at 

higher volumes, there is a larger range of productivities.

c. Analysis of the Surface Transfer Centers

Surface Transfer Centers (STCs) “are mail consolidation and re-distribution facilities that 

assist the Postal Service in maximizing the utilization of vehicles and their capacity to 

transport mail.”

57 STCs do not handle individual mailpieces, but instead serve as an 

intermediary between other mail processing facilities. The Postal Service often refers to 

them as hubs.58 There were 13 STCs in FY 2021.59

Among other factors, delayed truck arrivals and departures affect hubs’ costs and 

performance. The Commission analysis of the Postal Service data confirms that on-time 

arrival and on-time departure percentages are highly correlated. See Appendix A, Sections 

III.B.1. and III.B.2. Analysis, Figure A-5.

56 FY 2021 ACR at 20; FY 2021 ACD at 52-53.

57 United States Postal Service, Office of Inspector General, Report No. 21-111-R21, Contractor Security Clearances at Surface Transfer Centers, 

September 29, 2021, at 1, available at https://www.uspsoig.gov/sites/default/files/reports/2023-01/21-111-R21.pdf (OIG Report No. 21-111-

R21).

58 United States Postal Service, Postal Pro, Service Hubs and Facilities, available at https://postalpro.usps.com/operations/service-hubs-andfacilities, accessed on 03/30/2023.

59 Responses of the United States Postal Service to Questions 1-6 of Chairman’s Information Request No. 2, September 14, 2022, question 1,

Excel file “ChIR.2.UPDATE_ChIR 1_Q4_Q6 and Q7J_NONPUBLIC.xlsx” (Response to CHIR No. 2).
Docket No. SS2022-1 - 29 -

Figure III-3 illustrates the on-time departure levels at 11 of the 13 STC facilities. On-time 

departure measures the percentage of mail that departs from the facility on time.

Figure III-3

Surface Transfer Centers (actual counts) by Level of On-Time Departure, FY 202160

As Figure III-3 shows, only 3 STCs have an on-time departure rate greater than 80 percent,

and only one STC has it above 90 percent. For the majority of STC facilities, between 70

percent and 80 percent of scheduled trips depart on-time. Two facilities had an on-time 

departure rate of less than 70 percent.

d. Analysis of Destination Delivery Units

The Commission also analyzed data for DDUs before conducting facility visits. The 

Commission limited its analysis of DDUs to delivery units, which are post offices, stations, 

or branches that carry out mail delivery functions.61 Every DDU serves (or delivers mail to) 

at least one 5-digit ZIP Code area. Every 5-digit ZIP Code area is further divided into 

smaller units to which mail destinates: namely, carrier routes. Delivery units can service 

city routes, rural routes, or a mix of both. City routes serve geographic locations within the 

boundaries of a post office, while rural routes generally serve areas falling outside these 

boundaries.62 Figure III-4 shows the portions of the Postal Service’s delivery units that 

service each type of route and a mix of routes. While the majority of post offices delivers

solely to rural routes, there are over roughly 142,000 city routes and 81,000 rural routes.

60 Source: Commission calculations using data from Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “NonPublic SV 

Data_FY17_FY21.xlsx.” Two out of thirteen STC facilities were excluded due to discrepancies between the Postal Service’s dataset.

61 United States Postal Service, Publication 804 – Drop Shipment Procedures for Destination Entry, October 2013, Appendix F Glossary, available 

at https://about.usps.com/publications/pub804/pub804_f.htm.

62 Postal Regulatory Commission, Rural Delivery and the Universal Service Obligation: A Quantitative Investigation, July 31, 1992, at 3, available 

at https://www.prc.gov/sites/default/files/papers/rural.pdf.

2

3

3

1

1

1

below 70%

between 70% and 75%

between 75% and 80%

between 80% and 85%

between 85% and 90%

above 90%

Level of On-Time Departure
Docket No. SS2022-1 - 30 -

Geographic analysis of delivery units that service a mix of city and rural routes shows that 

they tend to be further from urban areas than delivery units that service strictly city routes.

Figure III-4

Delivery Units by Type of Routes63

63 Source: See Response to CHIR No. 1, question 7; see also Library Reference SS2022-1/NP1, August 16, 2021, Excel file “Delivery Units - ChIR 

1_Q7_A thru I and K_NONPUBLIC.xlsx.”

51%

16%

33%

Rural

City

Mixed
Docket No. SS2022-1 - 31 -

Figure III-5

Delivery Units by the Number of Serviced ZIP Codes64

Figure III-5 illustrates how many 5-digit ZIP Codes are serviced by each delivery unit. Most 

delivery units (approximately 74 percent), service a single ZIP Code.65 Seventeen percent of 

delivery units service two ZIP Codes, and just a few hundred delivery units service four ZIP 

Codes or five or more ZIP Codes.

2. Methodology for Selecting Facilities for Site 

Visits

The primary objective of the facility visits was to understand the causes of inefficiencies in 

flats mail operations. As discussed in Section III.B.1., the Commission previously identified 

and discussed in detail the causes of inefficiencies through the perspective of pinch points 

first identified in the FY 2015 ACD. See Section III.B.1.; see also FY 2015 ACD at 165. 

However, the Commission determined that the causes of inefficiencies should not be 

explored solely through formal data analysis of facility-level datasets on mail processing, 

bundle breakage, and transportation provided with the Postal Service’s ACR. As the Postal 

Service consistently noted, mail processing facilities differ in terms of facility layouts, 

management decisions, and relationships with nearby facilities. See, e.g., FY 2021 ACD at 

252. The Commission sought additional empirical and qualitative information on these 

specific characteristics through facility visits. To follow up on observations made during 

the facility visits, the Commission issued a series of questions seeking clarification from the 

Postal Service and consulted with an expert on postal operations.

64 Source: See Library Reference SS2022-1/NP1, Excel file “Delivery Units - ChIR 1_Q7_A thru I and K_NONPUBLIC.xlsx.”

65 Commission calculations using data from Response to CHIR No. 1, question 7, Excel file “ChIR 1_Q7_A thru I and K_PUBLIC.xlsx.”
Docket No. SS2022-1 - 32 -

When selecting facilities to visit, the Commission used multiple criteria. To better 

understand the broad range of activities performed by the Postal Service at every stage of 

the flats mail delivery process, the Commission sought to visit facilities of different types: 

STCs, mail processing facilities sorting both individual mailpieces and bundles (NDCs and 

P&DCs), and DDUs.

Each facility type performs a different and specialized role in moving mail from origin to 

destination. For mail processing sites (P&DCs and NDCs), the Commission focused 

primarily on the level of labor productivity of automated equipment and bundle breakage 

during flats processing. The Commission sought to observe all types of flats mail processing 

machines. Specifically for bundle processing, the Commission sought to observe operations 

on machines that process high volumes of bundles such as the Automated Package and 

Parcel Sorter (APPS) and the Small Package and Bundle Sorter Tracking System (SPBSTS) 

machines. The Commission chose the facilities that had both high and low rates of broken 

bundles.

The Commission also wanted to ensure that it would observe operations on both types of 

flats processing machines (AFSM and FSS). The Commission considered facilities with 

different levels of volumes and different levels of productivity on both types of mail 

processing equipment.

For STCs, the Commission was primarily concerned with transportation-related metrics, 

including, but not limited to, causes of transportation delays, misrouted trucks, and 

contracted transportation costs.

Appendix A, Sections III.B.1. and III.B.2. Analysis provides the details of the facility-level 

data analysis that the Commission used to select mail processing facilities for visits.

When visiting DDUs, the Commission focused on delivery costs and relationships with 

upstream P&DCs visited by the Commission. The Commission also selected delivery units 

that serve different arrays of routes (i.e., rural routes only, city routes only, and both city 

and rural routes; serve just one ZIP Code or several ZIP Codes).

In addition to observing flats processing and other operations, the Commission interviewed

facility managers to discover why certain facilities were above or below average in terms of 

productivity or bundle breakage. These interviews provided the Commission an 

opportunity to understand what the facilities with relatively high productivity or low 

bundle breakage were doing differently, and how other facilities would be able to learn 

from best practices. The Commission also visited some facilities that had close network ties 

to one another to observe network effects and possibly learn about inefficiencies across 

interrelated points in the Postal Service network.

Prior to conducting facility visits, the Commission developed questions spanning topics in 

every pinch point. The Commission then conducted trial visits to three facilities: (1) P&DC 

1; (2) STC 1; and (3) DDU 1. Using the information received from facility managers during 
Docket No. SS2022-1 - 33 -

trial visits, the Commission refined its initial interview questions for future use during 

facility visits. In addition, after conducting trial facility visits, the Commission refined its 

facility visit criteria and selected a few additional sites that had good network ties with

each other. The Commission also visited facilities in the Mid-Atlantic, Northeastern, and 

Midwest regions.

3. Summary of the Site Visits

Following the first three trial visits, Commission staff visited eight mail processing facilities, 

two DDUs, and one hub or STC. In addition to Postal Service sites, Commission staff visited 

the processing facilities of two private-sector mailers. Representatives from the Postal 

Service and private mailers’ facilities guided Commission staff through their operations to 

the extent possible, answered questions, and shared insights into their flats’ operations.

For postal facility visits, Sections III.B.3.a. through III.B.3.c. summarize collected 

observations by core activities that were performed at the facilities: mail processing 

operations (see Section III.B.3.a.), mail consolidation for transportation in the Postal Service 

network (see Section III.B.3.b.), and last mile delivery (see Section III.B.3.c.). Observations 

gathered at visits to mailers’ facilities are summarized in Section III.B.3.d.

a. Mail Processing Sites

Including the trial visits, Commission staff visited two types of mail processing facilities,

two NDCs and seven P&DCs.

Discussions with management at various sites indicated that there has been a general 

redesign of the network in response to increases in package volumes and declines in letters 

and flats volumes in recent years. This redesign has resulted in limited processing 

operations at some facilities. Some mail processing sites that the Commission staff visited 

processed all mail shapes while others performed processing operations only for certain 

mail shapes (e.g., letters and flats or flats bundles and packages). Operations at some sites 

were limited to only certain mail classes (e.g., USPS Marketing Mail and Periodicals or FirstClass Mail) or sort levels,66 or a combination of those and other characteristics.67

Commission staff observed that the limited processing operations were supported by a 

complex surface transportation network, which moved mail between the interconnected 

operations that were performed at different sites. For example, facility A sent its 

successfully sorted flats bundles to facility B for subsequent processing but sent all bundles 

that broke, or were treated as broken, to a different facility (facility C) for processing. Each 

of the two truck trips was less full than if all bundles (successfully processed and broken) 

were sent to the same facility for subsequent processing. Moving mail between sites 

66 For example, a site might sort mail only to the 3-digit ZIP Code level, corresponding to the 3-digit destination ZIP Code of sorted mail, or only

to the 5-digit ZIP Code level.

67 For example, sites limited their processing operations to only outgoing mail (mail that destinated outside the service area of the mail 

processing facility) or only incoming mail (mail that destinated within the service area of the mail processing facility), or to processing of intact 

flats bundles only and transporting broken bundle to other facilities for processing.
Docket No. SS2022-1 - 34 -

increased the time mail spent in allied operations. See Section III.B.4.d. and Section III.C.3. 

for more details. The Commission observes that separating processing operations in this 

manner might lead to increases in the cost related to transporting mail between sites 

because more trips are made, and because the trips are on potentially emptier trucks.

Maximizing truck space used by mail is the goal of efficient transportation operations.

Commission staff also observed that performing different processing operations at 

different sites made facilities interdependent. For example, mail processing operations at 

facility A were scheduled based on schedules for mail processing operations at facilities B 

and C, which fed volumes into facility A’s operations. Any deviations from planned 

schedules at one facility meant deviations from planned schedules for interconnected 

operations performed at other facilities. In these situations, managers were faced with 

decisions, which often involved trade-offs. For example, processing of mail at facility A was 

delayed. The management at the receiving facility (facility B) decided to wait for delayed 

mail from the feeding facility (facility A). During that time, the machine and employees at 

facility B were idle, and machine and employee workhour productivities suffered. Waiting 

to process delayed mail resulted in this mail being dispatched to DDUs within the 

committed time; for this mail, there was no negative impact on service performance. 

However, all subsequent operations at facility B were delayed, which had cascading effects 

on interconnected operations at facilities that expected mail from facility B for processing. 

Some of that mail may have had to be diverted to other modes of transportation than 

intended, such as from prescheduled, contracted trips paying preset rates per mile, to extra 

trips that had to be ordered at a much higher rate per mile.

Observations and discussions with management at various sites indicated major 

inefficiencies related to bundle processing, particularly bundle breakage and manual

handling, which was needed to prepare flats from broken bundles for subsequent 

processing. Bundle breakage is discussed in more detail in Section III.B.4.a. Individual flats 

mailpieces from broken bundles represented only one source of flats that required manual 

work to prepare for additional processing. Facilities also employed a practice of having 

bundles bypass processing on machines if facility staff deemed them likely to break. 

Bundles deemed not strong enough to withstand sorting on a machine without breaking 

were intentionally opened and treated as broken bundles. Although this intentional bundle 

breakage might mitigate some productivity loss, it also ensured that these bundles received 

less efficient manual processing.

During the site visits, Commission staff also learned that some large shipments of bundled 

flats are not compatible with flats sorting equipment, even though these shipments 

qualified for substantial discounts based on the expectation that they would avoid manual 

sorting or sequencing work by the Postal Service. These shipments were meant for 

automated sortation on the FSS machines.68 Instead, they were sorted manually at DDUs. 

68 FSS sorts mailpieces to the sequence in which mail carrier delivers mail along their routes. Flats presorted by mailers for sortation on FSS 

qualify for the deepest discounts, because they eliminate the need for mail carriers to manually sort mail in the sequence of delivery points 

along their routes.
Docket No. SS2022-1 - 35 -

Certain facility personnel commented that the Domestic Mail Manual (DMM)69 standards 

were inaccurate as to what mail was able to be processed on FSS. Even for pieces that 

complied with DMM standards, facilities described how the quality of the paper used in the 

flats has declined, causing machines to jam or entire flats shipments to be rejected from the 

automated flats processing machines. All mail that is not sorted on automated equipment 

requires manual sorting, and once a mailpiece is diverted from automated processing, it is

manually processed downstream as well. The Postal Service does not track mail that pays 

automation rates but bypasses machine sortation.

The Commission notes that without tracking the data on flats mailpieces with irregularities, 

the true prevalence of the issue of flats that cannot be processed on automated equipment 

is unknown, and the discrepancy between the revenues that the Postal Service received 

and the costs it incurred for these unknown volumes cannot be estimated.

Other than financial and service performance implications related to manually sorting flats, 

Commission staff saw that the increase in workload this mail caused led to attrition due to 

the difficulty of the job. Management also described other difficulties retaining existing 

employees. Hiring new staff meant new and, at least temporarily, low-skilled workers. 

From facility visits and discussions with management, Commission staff learned that 

morale, skill level, and management support contribute significantly to a facility’s efficiency 

and productivity. Consequently, difficulties retaining staff negatively affect the efficiency of 

the whole facility.

b. Surface Transfer Centers

The main functions of STCs are mail consolidation and cross-docking. Mail consolidation 

involves combining mail from several containers and placing it into fewer, fuller containers. 

Cross-docking involves combining containers with the same destination and transporting 

them on the same trucks.70 In other words, STCs work to move fuller containers on fuller 

trucks.

The two STCs that Commission staff visited were contracted operations.71 However, both 

STCs had Postal Service employees on site to monitor the timeliness of STCs’ operations 

and to coordinate between the contractors and Postal Service Headquarters.

69 See United States Postal Service, Mailing Standards of the United States Postal Service, Domestic Mail Manual (DMM) (2023), available at 

https://pe.usps.com/DMM300/Index.

70 Cross-docking did not involve opening containers and moving mail. Rather, the term “cross-docking” refers to containers changing docks. For 

example, a container from origin A arrives at an STC, and is unloaded onto dock number 1. Another container arrives from origin B and is 

unloaded onto dock number 2. The two containers are headed for the same destination – destination C. A truck for destination C departs from 

dock 10. Cross-docking involves moving containers headed for destination C from docks 1 and 2 onto dock 10, where they will be loaded onto 

the same truck.

71 In FY 2021, the Postal Service operated about half of its 13 STCs; the other half were contracted operations. The Postal Service representative 

at one of the visited STCs explained that during FY 2022, the Postal Service stopped operating STCs and contracted out operations at all facilities 

that it previously operated.
Docket No. SS2022-1 - 36 -

Of the flats products, only First-Class Mail Flats move through STCs. The focus of these STC

visits was to analyze potential inefficiencies of routing First-Class Mail Flats through STCs. 

Commission staff also focused on the impact this practice has on the time First-Class Mail 

Flats spend in transit, and on their transportation costs. Potential inefficiencies include 

waiting for mail to arrive at the STC for consolidation, insufficient capacity to fit First-Class 

Mail Flats on scheduled transportation departing from STCs, the associated delayed 

arrivals of such mail at downstream processing facilities via alternative transportation 

options, and the cost of such alternative transportation arrangements.

The Postal Service representatives described contractors’ operations as generally very 

efficient and timely, with consolidation and cross-docking times strictly monitored and 

penalties assessed for delays.

However, the Postal Service representatives explained that there were delays on longdistance transportation, describing some trips as routinely delayed. The most common 

causes of delays included origin postal facilities dispatching mail late and delays associated 

with switching drivers at the relay points.

Since most trips that STCs operated were round trips, delayed inbound trucks meant that 

mail that the STC had ready to load onto the return portion of the trip would also arrive 

late at the destination. As for delays related to relay points, an STC representative 

explained that the United States Department of Transportation regulations require drivers 

to rest at regular intervals, and for a certain amount of time. Having one dedicated driver 

on a trip would require adding rest time to drive time, potentially doubling trip time. 

Switching drivers at relay points eliminated the need for rest time. The representative 

added that STCs were exploring an option of team driving to prevent delays related to relay 

points. With team driving, two drivers on a truck would alternate their drive and rest times.

In case of delayed incoming trucks, a Postal Service representative decided whether to 

order extra transportation for outgoing mail. Extra transportation is unscheduled 

transportation, ordered on an as-needed basis.

Another situation that called for decisions to order extra transportation is where scheduled

outgoing trucks are filled to capacity with First-Class packages, with no space remaining for 

First-Class Mail Flats.

The Postal Service representatives explained that decisions to order extra transportation 

were based on critical entry times (CETs) at destination facilities. CETs represent the latest 

times mail can arrive at mail processing facilities to be processed and delivered within the 

stated service standard.

Representatives at the STCs acknowledged that extra transportation was expensive, and 

trucks were frequently not full when they left the STC. They described combining mail for 

several destinations on extra trucks and adding stops to extra trips, to justify the costs. 

However, they added that this was not routinely done because every added trip stop 
Docket No. SS2022-1 - 37 -

increased the risk of delay for the extra trip. In summary, routing First-Class Mail Flats 

through STCs introduces potential inefficiencies in terms of service performance and 

transportation cost.

c. Destination Delivery Units

Every DDU serves at least one 5-digit ZIP code area, and every 5-digit ZIP code area is

divided into smaller units, so-called carrier routes. Typically, one mail carrier delivers mail 

along one carrier route with several delivery points. DDUs ordinarily receive mail from 

destination processing facilities that has been sorted either by carrier route (but not in the 

precise delivery point sequence (DPS)) or in delivery point sequence.72

Flats that were not sorted at mail processing facilities on automated equipment, whether to 

carrier route and/or in delivery point sequence, were sorted and/or sequenced manually 

at DDUs.

Every mail processing facility that Commission staff visited described regularly receiving 

shipments of flats that bypassed machine processing and that were sent directly to DDUs to 

be processed by hand.

The management at the DDU, where Commission staff saw such shipments on the day of 

the visit, described acute staffing shortages and difficulty retaining employees because of 

workloads that shipments like these caused. The management also commented that 

delivering these flats on time was not possible.

d. Mailers’ Facilities

The visits to mailers’ facilities and the discussions with their management showed that 

effective communication with customers has important productivity implications. The 

mailers said that the effectiveness of their communication lay in management’s 

understanding their own operations, including sources of potential inefficiencies. 

Management also described frequent contact with customers, which included customer 

education on mail preparation. In addition to benefiting mailers’ own operating efficiency,

the mailer indicated that this communication style improved the degree to which mail was 

prepared to mail-preparation quality standards (as specified in the DMM) prior to 

induction into the Postal Service’s network.

Mailers expressed their willingness to do their part in addressing the Postal Service’s flats 

cost issues. However, they also expressed concerns about a lack of effective communication 

with the Postal Service. Most notably, mailers did not find that the feedback from the Postal 

Service included relevant data that mailers needed to understand the specifics of any gaps 

in their mail preparation quality, or data that would allow tracking shipments to their own 

operations.

72 This is the finest level of sortation. The sequence of delivery points in which mail carrier delivers mail along a carrier route is predetermined.
Docket No. SS2022-1 - 38 -

4. Common Causes of Inefficiencies (Analysis of 

Pinch Points)

a. Bundle Breakage During Bundle Processing

Mailers assemble flats into bundles in different presort levels, based on shared destination. 

For example, flats in a bundle might destinate in the same 3-digit ZIP Code area (“3-digit

bundles”), or the same 5-digit ZIP Code area (“5-digit bundles”), or on the same carrier 

route (“carrier route bundles”) along which a mail carrier delivers mail. Flats that do not 

share a common destination area can also be bundled together (“mixed bundles”).

Mailers place presorted bundles in postal containers before entering them into the postal 

network. Flat bundles can be placed on pallets or included in sacks (collectively, 

“containers”). Similar to combining flats in a bundle, bundles are combined in containers in 

different presort levels. For example, a 3-digit pallet can include carrier route, 5-digit, or 3-

digit bundles that destinate within the same 3-digit ZIP Code area, and a 5-digit pallet 

would include bundles for different carrier routes that destinate in the same 5-digit ZIP 

Code area. Mixed bundles, described above, are included on mixed pallets or in mixed 

sacks.

Mailers can enter their presorted bundles in presorted containers at mail processing 

facilities that serve the area where bundles originate, referred to as origin entry. 

Alternatively, mailers can enter bundles into the network at mail processing facilities that 

serve the area where bundles destinate, referred to as destination entry.73 Entry facilities 

can include NDCs, Area Distribution Centers (ADCs), P&DCs, or DDUs. Mail preparation 

standards for the numerous bundle and container presort levels and mail entry points are 

defined in the DMM.74 For example, a 5-digit pallet can enter the postal network at an 

origin or destination mail processing facility, but a mixed sack or pallet can only be entered 

into the postal network at an origin facility.

Based on presort level and entry, flats bundles receive different amounts of processing and 

transportation in the postal processing and transportation networks. For example, a 5-digit 

container entered at an origin facility might be transported intact through the postal 

network and require mail processing only at the destination P&DC, before dispatch to 

DDUs. By contrast, a mixed bundle on a mixed pallet needs processing at origin to sort the 

constituent pieces or bundles for transportation through the network, traversing different 

destination mail processing facilities before individual pieces from a mixed bundle can be 

distributed to their respective destinations.

Mail processing facilities sort flats for dispatch to other mail processing facilities, where the 

flats will destinate, and they sort flats that destinate within their service areas for dispatch 

73 The Postal Service has rules regarding specific dropship locations for mailers.

74 For example, mail preparation standards for commercial Marketing Mail volumes can be found at DMM § 245, available at 

https://pe.usps.com/text/dmm300/245.htm.
Docket No. SS2022-1 - 39 -

to local DDUs. Flats that destinate in service areas of other mail processing facilities are 

referred to as outgoing flats. Flats that destinate within the service area of the mail 

processing facility are referred to as incoming or destinating flats.

Outgoing flats, whether bundled or individual, must be sorted to the 3-digit ZIP Code level 

corresponding to mail processing facilities of destinations. Incoming flats, whether bundled 

or individual, must be sorted to at least the 5-digit ZIP Code level before they can be 

dispatched to DDUs for delivery.75 In efficient mail processing operations, flats that can be 

sorted on automated equipment are sorted to finer levels: carrier route or DPS, depending 

on the equipment available at mail processing sites.

When a bundle comes apart, it is referred to as bundle breakage. When bundles with 

different destinations break at the same time, the value of presortation is lost because the 

mailpieces become mixed together.

Bundle breakage has been identified as one of the major sources of inefficiencies in flats 

processing, and the Commission has required the Postal Service to report bundle breakage 

rates since FY 2015.

76

Mixed flats from broken bundles require additional sorting, some of which is done 

manually. For example, when bundles break while being sorted on a bundle sorter to 5-

digit destination ZIP Codes, the constituent pieces require two levels of sorting: first to the

3-digit level, which is the level at which the bundles were inducted into the machine, and 

then to the 5-digit level, which is the level to which bundles would have been sorted on a 

bundle sorter, had they not broken. This disrupts planned operations at mail processing 

facilities because additional work is required that would not be done if the bundles had

stayed intact and their sorting finalized on automated bundle sorters.

Bundles can break during transit or while being processed. Facilities mix flats from bundles 

that break prior to automated sorting with bundles that break during sorting on bundle 

sorting equipment. However, the bundle breakage rates that the Postal Service has 

reported include only bundles that broke during processing on bundle sorters, and do not 

include any bundles that broke before processing. Consequently, the reported bundle 

breakage rates are likely underestimated.

Managers described two main factors affecting bundle breakage during sorting on 

automated equipment: (1) the type of processing equipment; and (2) the ability of bundles 

to remain intact (bundle integrity).

According to managers, most bundles break when they are inducted (fed) onto the 

conveyor belt from the dumper. Dumpers are large containers with many bundles in them 

75 This is because every DDU serves at least one 5-digit ZIP code area.

76 FY 2015 ACD at 166-67; FY 2016 ACD at 161-62; FY 2017 ACD at 175-76; FY 2018 ACD at 215-16; FY 2019 ACD at 162-64; FY 2020 ACD at 244-

48; FY 2021 ACD at 242-47.
Docket No. SS2022-1 - 40 -

that are ready for sorting. From the many bundles included in dumpers, one bundle is 

selected at a time and fed onto the equipment’s conveyor belt. This is referred to as 

singulation. The singulation process involves bundles falling from the dumper onto the 

conveyor belt.

Managers described equipment designed to process both packages and bundles as 

generally “gentler” than equipment designed for processing packages only. This was due to 

the height that bundles fell from during singulation.

Staff at facilities described the Automated Parcel and Bundle Sorter (APBS), the only 

equipment designed for processing packages and bundles, as most gentle during 

singulation, with only a 6-inch drop from the dumper.

Picture III-1

APBS–Bundles Inducted From the Dumper Onto a Conveyor Belt

Facility staff described APPS as “more violent” than APBS, with bundles tumbling a lot in 

the dumper and dropping 2 feet during the singulation process. This can result in bundles 

losing their integrity.
Docket No. SS2022-1 - 41 -

Picture III-2

APPS–Singulated Bundles Fed onto a Conveyor Belt Move Toward a Scanner

(Left Picture) and Will be Directed into Appropriate Bins Based on

Their Scanned Destinations (Right Picture)

 

Management at one facility described recently switching processing of bundles from the 

APPS to the Automated Delivery Unit Sorter (ADUS), citing lower bundle breakage rates for 

ADUS, compared to APPS.
Docket No. SS2022-1 - 42 -

Only one facility that Commission staff visited operated the Small Package Sorting System 

(SPSS).

Picture III-3

SPSS–Bundles on Feeding Belts Being Fed Onto SPSS

The facility’s management emphasized that SPSS was not designed to handle bundles. The 

machine had the highest drop of all equipment Commission staff observed, with a 3-foot 

fall from the dumper.

As for bundle integrity, facility staff commented about strapping and wrapping materials 

used to band and wrap flats into bundles. For strapping, material mattered, and so did the 

number of straps and their tension. Some mailers repeatedly send their bundles strapped 

with rubber bands or wire, which are not permitted materials. Some bundles need extra 

strapping to prevent flats inside from shifting and falling out. The number of flats included

in bundles affected breakage as well. Too many pieces can cause strapping to break, while

very low numbers of flats included in bundles can cause the strapping material to be 

ineffective. The tension of the straps could be compromised during previous handling, such 

as transportation to the mail processing facility.77

For wrapping material, facility staff described breakage related to the quality of material, 

with thinner materials more likely to break. However, the size and weight of bundles 

mattered as well. Some bundles were wrapped (and strapped) according to DMMprescribed standards but were too large and/or heavy for the material to support them.

Staff at some facilities also commented on large and/or heavy bundles often causing 

breakage of smaller bundles during singulation. Management at a few facilities stated that 

77 The DMM includes standards for preparing bundles of flats. The DMM standards relate to physicals dimensions, weight, strapping and 

wrapping materials to use, and their tension, among other things. See DMM § 203, available at https://pe.usps.com/text/dmm300/203.htm.
Docket No. SS2022-1 - 43 -

they would have liked DMM bundle preparation standards to include standards for the 

quality of wrapping material. They specified that higher-quality shrink-wrap or polywrap 

would break less easily.

Management at one facility explained that identification of improperly strapped and/or 

wrapped bundles at the time of their induction into the network was difficult because 

mailers frequently placed such bundles on the bottom of pallets, or in sacks. However, the 

facility’s management provided no details on whether improperly strapped and/or 

wrapped bundles would have been accepted if they were identified upon visual inspection 

of mailers’ shipments.

Facilities’ management added that, even with correctly used strapping and wrapping 

materials, bundle integrity could be compromised for bundles that were handled and 

transported multiple times prior to arriving at their facilities. Management at one site with 

a high bundle breakage rate explained that their high breakage was only partially related to 

the facility’s use of SPSS equipment and attributed at least some of the breakage to the 

amount of previous handling their bundles received. Specifically, prior to coming to the 

facility for sorting to the 5-digit level, bundles were processed to the 3-digit level on

another mail processing facility’s APPS. As such, the mailer transports these bundles to the 

mail processing facility where they enter the postal network (entry facility), whereupon the 

bundles undergo sorting and other handling at the entry facility and subsequent 

transportation to the subject facility for sorting on SPSS equipment. The various handlings 

involve unloading bundles from mailers’ trucks, moving them to the entry facility’s 

processing floor, withstanding the “more violent” singulation process on APPS during 

sortation at the entry facility, loading onto truck for transportation to the subject facility, 

unloading from trucks, and moving to processing floor.

Staff at Postal Service facilities explained that mixed bundles traverse the most facilities 

and receive the most handling before bundles are opened and individual pieces from mixed 

bundles are ready for sortation to destination. This hurts their integrity. Additionally, 

transportation and handling are more likely to weaken the integrity of bundles included in 

sacks, as compared with bundles secured on pallets.

Additionally, bundle content matters. All facilities confirmed that bundle preparation 

quality is far worse for USPS Marketing Mail bundles than for Periodicals bundles. Co-mail 

bundles were described as most likely to break.

Co-mail bundles combine mailpieces of different types or titles or from different mail 

classes to create a larger bundle.78 Mailers prepare co-mail bundles to qualify for deeper 

discounts associated with worksharing. For example, bundles must contain a minimum 

78 Only USPS Marketing Mail, Periodicals, and BPM Flats can be included in bundles and combined in co-mail bundles. First-Class Mail Flats 

cannot be bundled and are included in trays.
Docket No. SS2022-1 - 44 -

number of pieces, as prescribed in the DMM, to qualify for workshare discounts.79 If a 

mailer prepares bundles of a single magazine title, they may only have enough pieces per 

bundle to qualify for a 3-digit discount. However, if the mailer combines the magazines 

with department store catalogues with the same destinations, they may have a sufficient 

number of pieces to create 5-digit bundles. Bundles presorted to the 5-digit level qualify for 

deeper discounts than 3-digit bundles, because the Postal Service avoids the cost of sorting 

from the 3- to 5-digit level, and the associated cost avoided by the Postal Service is 

reflected in the workshare discount. As volumes decline, co-mailing becomes more 

valuable to the mailer.

According to management at Postal Service facilities, co-mail bundles might include flats of 

different dimensions, which sometimes causes the pieces inside the bundles to shift and 

threaten their integrity. Co-mail bundles also tend to be too big and too heavy for their 

strapping and wrapping materials, which makes them more likely to become loose or break 

during transportation, machine processing, or other handling. Some facilities increased 

staffing for certain co-mail shipments that were scheduled to arrive at their sites.

At every P&DC visited, management explained that their goal was to prevent bundle 

breakage during automated bundle processing. To accomplish this goal, employees visually 

assessed bundles for their ability to withstand processing on the type of equipment 

operated at facilities. This visual inspection included assessing the type and quality of 

wrapping and strapping material; whether any pieces were shifting inside bundles; and the 

bundles’ size, weight, and content. Management described their employees as very 

experienced in recognizing bundles that are likely to break and that should accordingly 

bypass machine processing. Staff at the facilities referred to them as “loose bundles.”

The equipment operated at the sites mattered when employees made these determinations 

for individual bundles. For example, the APPS has a side feeder, which can be used to feed 

bundles to the conveyor belt manually. Manually feeding bundles deemed likely to break 

during singulation on the APPS can minimize the number of bundles bypassing automated 

sorting and increase the number of bundles finalized on the APPS. However, it is not clear 

whether all facilities with APPS used the option to manually feed bundles consistently.

79 For standards applicable to co-mail bundles, see DMM section 705.15.0, available at 

https://pe.usps.com/text/DMM300/705.htm#ep1420438.
Docket No. SS2022-1 - 45 -

Picture III-4

Bundle That Bypassed Sorting on APPS Because It Was Strapped with Rubber Bands

Having loose bundles bypass sorting on automated equipment might represent an 

inefficiency, because loose bundles are treated as broken bundles. In other words, loose 

bundles are opened, their pieces are mixed with flats from broken bundles and the 

constituent flats are manually prepared for individual processing. However, the extent of 

any inefficiency depends on how likely bundles bypassing machines are to break. For 

example, for bundles almost certain to break, the bundles would likely receive inefficient 

manual processing regardless. On the other hand, for bundles with only a 50 percent 

chance of breaking, bypassing machine sortation would impose inefficient manual handling 

for bundles that had a 50 percent chance of being finalized on automated equipment. Even 

so, allowing likely-to-break bundles to bypass automated processing may avoid other 

inefficiencies from the disruption that their breakage would cause in the processing of 

other bundles.

Another group of bundles treated as broken and loose bundles are “reject bundles.” These 

bundles cannot be finalized on bundle sorting equipment because of some irregularity. For 

example, Postal Service facilities management discussed bundles that are too heavy as 

being frequently rejected by the equipment. Additionally, management frequently 

mentioned that flash from the machine’s scanners causes glare for shrink-wrapped 

bundles. As a result, the scanners cannot read the bundles’ address labels or barcodes, and 

the bundles are rejected by the equipment.
Docket No. SS2022-1 - 46 -

Picture III-5

Containers with Bundles Rejected from APPS (on the Left) and with “No-Read” Rejects From 

ADUS (on the Right)

 

Every visited facility employed the practice of having bundles bypass machine processing 

to prevent breakage. Commission staff asked the Postal Service to provide separate data for 

the number of bundles that broke during sorting on bundle sorters, number of bundles that 

broke prior to machine processing, the number of bundles that were rejected by the 

equipment during processing, and the number of bundles that bypassed machine 

processing because they were deemed likely to break.80 The Postal Service responded that 

it only tracked bundles that broke during machine processing, since they were the only 

bundles that received machine scans. As noted above, the Postal Service does not track 

bundles that break before they could be processed on bundle sorters, or bundles that 

bypass the equipment.81

This suggests that the reported bundle breakage rates underestimate true bundle 

breakage.

b. Productivity of Flats Sorting on Automated Equipment

As Commission staff observed, one of the major differences between AFSM and FSS 

equipment was how deeply into the network each machine could sort to when preparing 

flats for the final delivery. A 3-digit sort prepares mail to a mail processing facility, a 5-digit 

sort prepares mail to a DDU, a carrier route sort prepares mail to the actual delivery route, 

80 Responses of the United States Postal Service to Questions 1-7 of Chairman’s Information Request No. 4, January 13, 2023, questions 4, 5 

(Response to CHIR No. 4).

81 Response to CHIR No. 4, questions 4.b., 5.d., 7.c.-d. See Responses of the United States Postal Service to Question 1-5 and 9 of Chairman’s 

Information Request No. 5, January 13, 2023, questions 1.a.-d., f.-g. (January 13 Response to CHIR No. 5).
Docket No. SS2022-1 - 47 -

and DPS prepares the mail to the specific address level. Postal Service facility staff 

explained that the AFSM’s finest sort level is carrier route. The FSS’s finest level is DPS.

Figure III-6

Levels of Sorting Specificity

Flats sorted to carrier route must be manually placed by mail carriers into the order in 

which they are delivered along the carrier route. Each delivery route has an assigned case 

that has the sequence of individual delivery points in slots on the case. Flats sorted to DPS 

require no such additional in-office sequencing, but carriers still must merge them with the 

manually cased flats in order for the entire set of flats to be delivered in sequence. The 
Docket No. SS2022-1 - 48 -

techniques for merging these two types of flats will vary depending upon whether they 

destinate on city or rural delivery routes, as well as upon the type of delivery route.82

The labor productivity of automated mail processing operations, defined as mailpieces 

processed per employee workhour, increases when the automated sortation systems are 

used effectively. Staffing levels for AFSM and FSS equipment are defined. When these 

staffing levels are adhered to, and they typically are, the effort to achieve productivity 

targets is focused upon achieving equipment throughput targets. Throughput targets are 

best achieved through a combination of efforts to properly prepare the flats for induction

to the processing equipment, methods used to feed pieces to the equipment, and efforts to 

ensure the timely and proper removal of flats once they are sorted. Jams within the 

automated sortation are inevitable. Minimizing jams and ensuring timely clearance of jams 

also leads to improved throughput. Proper maintenance of the equipment is essential to 

attaining and maintaining high operational throughput.

The Postal Service has attributed productivity declines for both machines generally to 

significant declines in flats volumes.83 The Postal Service also indicated that some of the 

AFSM productivity declines could be attributed to the deployment of FSS operations. Id.

In April 2021, the Postal Service announced that due to declining flats volumes, it would 

start removing “unnecessary” flats equipment.84 Commission staff observed FSS operations 

at four mail processing sites and AFSM operations at seven sites. Through these visits, 

Commission staff aimed to understand the impacts that flats volume declines and FSS 

equipment deployment might have had on automated flats processing productivity, as well 

as to gather insights that would help inform the expected impact that the removal of 

unnecessary flats equipment might have on automated flats processing productivity.85

(1) FSS Processing

Some mail processing facilities adjusted to declines in flats volume by running their FSS 

machines fewer days each week.86 This way, on days when flats volumes were higher, 

machine capacity was better used. Better use of FSS capacity meant more flats processed 

per employee workhour, than the hourly rate achieved on low-volume days. By avoiding 

sorting flats on low-volume days, facilities were better able to maintain their FSS 

productivity levels.

82 For more information on the methods commonly used for casing and preparing mail for delivery on city carrier routes, see United States 

Postal Service, Handbook M-41, City Delivery Carriers Duties and Responsibilities, June 2019, at 20-24. For more information on the methods 

used for casing mail for delivery on rural carrier routes, see United States Postal Service, Handbook PO-603, Rural Carrier Duties and 

Responsibilities, September 2013, at 36-37.

83 See, e.g., Docket No. ACR2014, Responses of the United States Postal Service to Questions 1-6, 8, 10, 12-13 and 15-22 of Chairman’s 

Information Request No. 2, January 23, 2015, question 8.e. (Docket No. ACR2014, Response to CHIR No. 2).

84 See Docket No. ACR2021, Library Reference USPS-FY21-45, folder “Rule 3050.50 (f) Operational Changes Report,” PDF file “FY21 Paragraph (f) 

Report.pdf,” at 4-5. See also United States Postal Service, Office of Inspector General, Report No. 21-240-R22, Transfer of Mail Processing 

Operations from Selected Facilities, May 4, 2022, at 3, available at https://www.uspsoig.gov/sites/default/files/reports/2023-01/21-240-

R22.pdf (OIG Report No. 21-240-R22).

85 For two mail processing sites, FSS machines were removed shortly before the facility visits.

86 At most of the visited facilities, management described running their FSS equipment 7 days a week at the time FSS was deployed. By the end 

of 2022, FSS equipment was operated between 2 and 7 days a week at sites that the Commission staff visited.
Docket No. SS2022-1 - 49 -

Postal Service mail processing staff explained that flats were not fed to FSS continuously, as 

they were prepared for induction to the machine. Instead, when all pieces for respective 

sort plans were ready, they were fed to the machine at once and the machine run started. 

This had a positive impact on FSS productivity.

Picture III-6

Flats in Trays Compatible with FSS Are Gathered for Sorting on FSS Equipment

Many facilities also described upgrading USPS Marketing Mail flats that were not 

committed for a given day (that is, due to be sorted that day), and combining them with 

committed volumes, such as Periodicals. In this way, facilities were able to increase the 

number of flats sorted per machine run. At only one facility that Commission staff visited, 

an NDC, the manager reported that mail from different mail classes was never combined in 

any sortation or allied activities.

The operational expert with whom the Commission collaborated noted that combining 

different mail classes in incoming sort plans has long been a standard procedure used by 

mail processing facilities. First-Class Mail and Periodicals mailpieces have been combined 

with USPS Marketing Mail pieces based on the color-coding chart provided in Figure III-7.

87

There is a national color code policy for USPS Marketing Mail, which is “processed in 

sequence according to the color code commitment, with the oldest mail processed first. 

Delayed mail received from upstream facilities or operations should be queued to be 

processed in front of [USPS Marketing Mail] with a later commitment.”

88

87 The color-coded chart shown in Figure III-7 was provided to Commission staff during a trial visit of P&DC 1. “Standard Mail” is an archaic term 

for USPS Marketing Mail.

88 Docket No. N2014-1, Library Reference USPS-LR-N2014-1/16, Manual Responsive to PR/USPS-T1-14, January 24, 2014, at 2.
Docket No. SS2022-1 - 50 -

Figure III-7

USPS Marketing Mail Color Codes

Figure III-7 indicates days of the week that USPS Marketing Mail pieces must be processed 

and dispatched to DDUs, based on the days of the week that they are received at mail 

processing sites. As described above, however, a facility might upgrade non-committed 

USPS Marketing Mail flats received on a Monday for Tuesday or Wednesday dispatch, 

rather than for the Thursday dispatch that the color-coding would direct for 3-day delivery 

mail.

From discussions with management at the FSS sites, Commission staff learned that FSS 

machines have certain features that enable facility staff to minimize the impact of flats 

volume declines on FSS productivity. The process is described below.

Pieces are sorted on FSS machines to DPS according to their sort plans. Staff at Postal

Service facilities explained that every FSS sort plan includes a unique combination of 5-

digit ZIP Codes, to which pieces sorted to DPS destinate. They clarified that FSS sort plans 

are also referred to as FSS zones, or FSS schemes. FSS sort plan could include up to 30 

thousand delivery points, which could be from several 5-digit ZIP Codes. Staff also

explained that four or five 5-digit ZIP Codes could be included in a FSS sort plan.

Management at the visited facilities explained that as flats volumes declined, existing sort 

plans could be revised. Sort plan revisions involved eliminating delivery points with low 

flats volumes from them. Management also explained that new sort plans could be created, 
Docket No. SS2022-1 - 51 -

most frequently by consolidating 5-digit ZIP Codes for several smaller towns in new sort 

plans.

The FSS machine could be run in two different modes, VM4 or VM2. In VM4 mode, flats for 

only one sort plan could be sorted in one FSS machine run. In VM2 mode, flats for two sort 

plans could be combined and sorted in one FSS machine run.

Picture III-7

A Sign That Identifies Sort Plans to Combine in Visited Facility’s FSS Run in VM2 Mode

For sort plans with high flats volumes, such as those with ZIP Codes in highly populated 

urban areas, volumes were sufficiently high to run such sort plans separately, in VM4 

mode, without reducing FSS productivity. For low-volume sort plans, such as those with 

ZIP Codes for smaller towns, staff at facilities explained that they combined two such sort 

plans in one machine run, with FSS operated in VM2 mode.

By combining sort plans, facilities were able to sort volumes for up to 60,000 delivery 

points in one machine run. Essentially, VM2 mode enabled facilities to expand the number 

of delivery points and thus to increase flats volumes processed in a machine run. This way, 

facilities could mitigate the negative impact of declining flats volumes on FSS productivity 

to some extent. Every facility that operated FSS equipment partially or fully switched to 

running FSS in VM2 mode due to declining flats volumes.

The manager at a mail processing site with high FSS productivity described the importance 

of creating optimal sort plans, which would enable optimal FSS operation in VM2 mode, 

and in turn, maximize FSS productivity. The manager explained that when sort plans were 

revised, flats volumes associated with eliminated delivery points should be minimized.
Docket No. SS2022-1 - 52 -

When flats are sorted on FSS, they pass through the machine twice. During the first pass, 

pieces are sorted from a 5-digit level to delivery point groups.

89 At the end of the first pass, 

the FSS automatically re-inducts grouped flats back into the machine for a second pass. At 

the end of the second pass, flats are sorted to DPS.

Creating optimal sort plans, which would ensure optimal FSS operation, is important to 

maximize the number of flats finalized on FSS to DPS and to ensure efficient processing of 

flats that qualified for the deepest discounts on the premise that they do not need manual 

casing. However, management at the facility with high FSS productivity added that the 

facility’s optimal FSS operations and high productivity could not be attained without 

continuous staff support and training, and that retaining trained staff was also critical to 

ensure continued efficient operations.

As a very important factor in FSS productivity, facility staff described proper preparation of 

flats before inducting them into the machine so that machine jams were reduced. It was 

also important to feed the right volume into the machine, because both over- and underfeeding the machine was not optimal. Striking this balance requires proper staff training

continuously. Management at one P&DC described higher FSS reject rates on days when 

inexperienced or poorly trained staff prepared mail for FSS processing.

Proper mail preparation, correct feeding of volume into the machine, and regular 

maintenance were particularly important because facilities reported a shortage of staff 

trained to fix FSS breakdowns. Management at one mail processing site described everyday 

machine breakdowns, sometimes lasting an entire day. This occurred despite the fact that 

this facility (and every visited facility) reported performing 4 hours of daily routine 

maintenance for its FSS equipment.

Machine breakdowns halt FSS operations and impact all interdependent operations. For 

example, staff was idle during FSS breakdowns but were not moved to other operations 

that may have been understaffed because the expectation was that repairs would not take

long, and the staff needed to be ready to operate the machine when it was fixed.

Breakdowns can also result in pieces not being finalized on FSS to DPS, which increased the 

need to manually case flats by the DDUs’ carriers. As noted above, manual casing for pieces 

that qualified for the deepest discounts, based on expected sortation to DPS on automated 

equipment, represented inefficient operation.

(2) AFSM Processing

Flats that destinate in the service area of a mail processing facility must be sorted to at least 

the 5-digit ZIP Code level before they are dispatched to DDUs.90 The different sorting that 

89 For example, “a first delivery point group compris[es] a first delivery point on a first carrier route and a first delivery point on a second carrier 

route.” United States Patent Application Publication, Pub. No. US 2005/0218046 A1, October 6, 2005, at 1 (United States Patent Application 

Publication, Pub. No. US 2005/0218046 A1), available at 

https://patentimages.storage.googleapis.com/14/47/30/dc187c1f164899/US20050218046A1.pdf.

90 Flats that require manual sorting, are sorted to 5-digit ZIP Code level at mail processing facilities, i.e., the minimum level required for dispatch 

to DDUs.
Docket No. SS2022-1 - 53 -

destinating flats receive on the AFSM is referred to as an “incoming sort.” Flats that 

destinate in another mail processing facility’s service area are sorted at mail processing 

facilities to the 3-digit ZIP Codes associated with their destination mail processing facilities, 

which is referred to as “outgoing sorts.” During the facility visits, Commission staff 

gathered the following information, which might at least partly explain the low 

productivity of sorting flats on the AFSM equipment.

Ability to scale AFSM operations in response to flats volume declines. Every facility that 

Commission staff visited had at least two AFSM machines. It appeared that management 

did not have the flexibility to operate the AFSM on high volume days only, as it did with the 

FSS. On the contrary, AFSM machines were running continuously during the day, except for 

4 hours of daily maintenance that each machine received.91

This was because of the greater variety of sorting jobs that AFSM machines performed 

compared to FSS machines. While the FSS was designed to sort only destinating flats from 

5-digit to DPS, AFSM sorts outgoing flats to the 3-digit level and incoming flats to the 5-digit 

and carrier route levels.

Flats of all types are “staged,” and flats within the USPS Marketing Mail class are colorcoded in accordance with their service commitment. See Figure III-7. Thus, First-Class Mail

Flats, Periodicals, and USPS Marketing Mail flats due for delivery were all combined and 

run together on the same program.92 However, almost every site described combining 

USPS Marketing Mail flats that were not committed for the day with Periodicals and FirstClass Mail Flats, to increase volumes sorted in their AFSM sort plans, and to improve 

overall AFSM productivity. This was consistent with the efforts the management at visited 

sites described making to improve capacity utilization and employee workhour 

productivity in FSS operations.

Impact of FSS operations on AFSM productivity. At facilities that served FSS zones, 

management noted that deployment of FSS negatively affected AFSM productivity. The 

reason was that when FSS-zone-destined flats were diverted from AFSM’s finest sorts 

(incoming sorts to carrier route), the respective sorts were not eliminated from the list of 

jobs that AFSM machines performed. According to staff at facilities and the Commission’s 

operational expert, the Postal Service standard operating procedures dictated that FSS 

rejects destinating to the zones with multiple ZIP Codes had to be re-run on AFSM to the 

extent possible before dispatching them to DDUs.93 As such, even though volumes were 

diverted from AFSM to FSS, AFSM continued to process flats pieces for the ZIP Codes 

included in FSS zones. How this impacted AFSM productivity is explained in more detail 

below.

91 The machines’ maintenance windows were staggered, so that one machine at a facility would always run.

92 According to the operational expert retained by the Commission, the practice of combining all types of flats into single processing operations

started when the first nationwide mechanical flats sorters were deployed in the 1980s.

93 See United States Postal Service, Office of Inspector General, Report No. 21-131-R21, Manual Mail Processing Efficiency, September 21, 2021, 

at 12, available at https://www.uspsoig.gov/sites/default/files/reports/2023-01/21-131-R21.pdf (OIG Report No. 21-131-R21).
Docket No. SS2022-1 - 54 -

As explained in Section III.B.4.b.i., several 5-digit ZIP Codes can be included in one FSS sort 

plan. Moreover, FSS allows combining two sort plans in one machine run, further 

increasing the number of 5-digit ZIP Codes sorted on FSS in VM2 mode. All pieces, whether 

for one or two sort plans, were fed into FSS and sorted at the same time, in one machine 

run. As more 5-digit ZIP Codes have been added to FSS zones in response to flats volume 

declines (see Section III.B.4.b.i.), an increasing number of AFSM sort jobs processed FSS 

rejects only instead of all destinating flats volumes. The negative impact on AFSM 

productivity stems from the increased number of AFSM sort plans that were processing 

FSS reject volumes.

Discussions with facilities management revealed that FSS rejects that could be re-run on 

AFSM were limited. First, Commission staff learned that only rejects from the first pass on 

FSS can be re-run on AFSM. This is because during the first pass on FSS, pieces are sorted to 

groups of delivery points, which more or less resemble groups of delivery points pertaining 

to carrier routes. Such grouped rejects can be aggregated back to individual 5-digit ZIP 

Codes and re-run on AFSM’s incoming sort to the carrier route level. However, since rejects 

from the second pass of the FSS machine runs were output from the sequencing process, 

reassembling pieces to 5-digit ZIP Codes for induction to AFSM would require substantially

more manual labor. As such, staff at facilities explained that second pass rejects cannot be 

re-run on AFSM and are dispatched directly to DDUs.

Moreover, not all first pass FSS rejects can be re-run on AFSM. Mail processing staff 

explained that FSS machines separated rejects into bins based on the reason that the 

machine rejected them: (1) “out-of-sort” rejects, for flats destinating to delivery points that 

were not included in FSS sort plans run on a machine;

94 (2) “no-read” rejects, for flats with 

address labels or barcodes that the machine could not read;

95 and (3) mechanical rejects, 

related to issues with mailpiece dimensions or flexibility.96 Commission staff also observed 

facility staff handling individual pieces that got jammed in the machine or that fell out 

during processing.

94 It is not clear whether sort plan revisions that involved removing low-volume delivery points from existing sort plans may have contributed to 

out-of-sort reject volumes.

95 Causes of such rejects included issues with ink when barcodes were printed, or no address labels/barcodes printed/attached to cover pages 

of individual catalogues, and missing cover pages where address labels/barcodes were attached. Facility staff described the last example as 

occurring frequently and related to mailers using thin paper, which rips off easily when flats sorting equipment handles pieces.

96 DMM includes criteria for physical standards that flats mailpiece must meet, such as minimum and maximum length, height, and thickness, 

ability to bend, uniform thickness (i.e., no bumps or protrusions). See DMM §§ 201.4, 201.6.
Docket No. SS2022-1 - 55 -

Picture III-8

Examples of FSS Machine Rejects

 

(Left: Bin with pieces that fell out or got jammed during FSS machine run. Right: “No-read” rejects from FSS)

Of the FSS rejects, “no-read” rejects cannot be re-run on an AFSM because, like FSS, the 

AFSM cannot read their address labels. Mechanical rejects can be related to an issue with 

mailpiece flexibility, e.g., when a lotion sample inserted in a catalogue prevented sufficient 

bending and FSS rejected it. Mechanical rejects can also be related to paper quality. Staff 

frequently described AFSM as “more forgiving” than FSS. For example, some catalogues 

printed on thin paper are rejected by FSS but are acceptable to AFSM. On the other hand, 

inflexible catalogues might be unacceptable for both machines. As such, the specific 

mailpiece irregularity would determine which FSS rejects could be re-run on AFSM and 

which could not. As for “out-of-sort” rejects, no mailpiece irregularity is involved; as such, 

these would be acceptable for AFSM machine processing.

The nuances described above suggest that, as the number of AFSM sort jobs did not change, 

volumes for individual sort jobs may have been increasingly difficult to project, especially 

for those sort jobs maintained for FSS rejects.

Facility staff described that when FSS reject volumes are low, such as those shown in 

Picture III-8, on the left, staff do not re-run them on AFSM and instead dispatched them to 

DDUs for manual sorting to carrier routes. Facility staff also described high- and lowproductivity AFSM sort plans for FSS rejects, suggesting high and low “supply” of FSS reject 

volumes.
Docket No. SS2022-1 - 56 -

The negative impact on AFSM productivity stems not only from potentially low FSS reject 

volumes for some sort plans, but also from the time that it takes to set up and take down a 

sort plan on AFSM. At one site, the manager described that it took about 25 minutes to set 

up a sort plan and about 35 minutes to take one down. No pieces were sorted while 

employee workhours accrued during sort plan set up and clean up. The manager gave an 

example of an AFSM sort plan with only 2,000-3,000 FSS rejects, which took about 15 

minutes to process on AFSM. Of the 75 minutes (25 minutes for set up + 15 minutes for 

sorting + 35 minutes for take down), during which several employees operated AFSM, only 

15 minutes (i.e., one-fifth) constituted “productive time.” As such, the more such sort plans 

that a facility runs, the more that FSS deployment harms its overall AFSM productivity.

Moreover, the unpredictability of FSS reject volumes makes planning operations, including 

setting up operating windows for the different sort plans, difficult for sites that serve FSS 

zones.

Impact of bundle breakage on AFSM productivity. While FSS deployment impacted volumes 

in AFSM’s incoming sorts to carrier route, bundle breakage impacted volumes sorted in 

AFSM’s other sorts, outgoing sorts to the 3-digit level and incoming sorts to the 5-digit 

level. The difference is that FSS operations cause volumes to divert from AFSM, while 

bundle breakage increases flats volumes that need processing on AFSM.

In general, staff at visited sites explained that mixed flats from broken, loose, and reject 

bundles (loose flats) are manually sorted to the 3-digit ZIP Code level. Discussions with 

management also suggested that the facilities treat loose flats as Managed Mail Program 

(MMP) flats.

Picture III-9

An Example of Flats Processing Flow Chart
Docket No. SS2022-1 - 57 -

A copy of a flats processing flow chart provided by management at a visited site indicates 

that loose and reject destinating USPS Marketing Mail and Periodicals flats bundles are 

processed with MMP flats. (“OP 143” stands for MODS operation code 143, which is for 

MMP flats.) The chart also shows that First-Class Mail Flats are included in the MMP.

Commission data analysis for the visited sites indicates that, other than P&DC 2, sites 

processed between 24 and 54 percent of flats via the MMP in FY 2021.97 See Figure III-8.

Figure III-8

MMP and Non-MMP Flats Volumes (Total Pieces Fed, millions)

Processed on AFSM at the Visited Sites in FY 202198

Figure III-9 shows that, of approximately 130 facilities that reported volumes and/or 

workhours under MMP operations in FY 2021, most processed between 20 and 50 percent 

of flats under MMP.99

97 Docket No. ACR2021, Library Reference USPS-FY21-NP42, February 22, 2022, CSV file “modstour2021r-np.csv.”

98 Docket No. ACR2021, Library Reference USPS-FY21-NP42, February 22, 2022, CSV file “modstour2021r-np.csv.”

99 Source: In Figure III-9, mail processing facilities, identified by unique finance numbers, are included on the horizontal axis, but are not shown,

due to the non-public nature of facility-level data. For example, values for facility number 126, of the 132 facilities for which data is included in 

the figure, are marked with a vertical line in Figure III-9. For this facility, 71 percent of flats volume and 0 percent of employee workhours were 

recorded in MMP operations, in FY 2021.

0

10

20

30

40

50

60

70

80

90

100

110

120

130

P&DC 1 P&DC 2 P&DC 3 P&DC 4 P&DC 6 P&DC 7 NDC 1

MMP TPF non-MMP TPF
Docket No. SS2022-1 - 58 -

Figure III-9

Percentage of Volumes and Workhours Charged to MMP at Sites 

that Reported Volumes Under MMP Operations in FY 2021100

The Commission followed up with the Postal Service to better understand what MMP is and 

the implications that merging loose mail with MMP might have on flats processing and 

costs. In its response, the Postal Service describes MMP as a distribution system, which 

includes First-Class Mail, destinating in specific ZIP Codes.101 The Postal Service also refers 

to the routing of MMP flats as being defined in the National Distribution Labeling List

logistics orders, but provides no other information on the differences in the routing, 

transportation modes, processing operations (e.g., whether there are differences in sort 

plans) between flats in MMP flows and those in non-MMP flows. Id.

As for loose flats from outgoing USPS Marketing Mail and Periodicals bundles, facility staff

explained that they sort them manually to the 3-digit level. Sites that the Commission staff 

visited and that processed originating First-Class Mail Flats described merging manually 

sorted outgoing loose flats with First-Class Mail Flats flows. This suggests that flats from 

broken or loose bundles are upgraded to the First-Class network and receive higher 

priority service than they would have received bundled as USPS Marketing Mail Flats or 

Periodicals.102

For incoming loose flats, manual sorting to the 3-digit ZIP Code level was necessary to 

prepare them for sortation to the 5-digit level on AFSM. Sortation to 5-digit level was 

100 Source: Docket No. ACR2021, Library Reference USPS-FY21-NP42, CSV file “modstour2021r-np.csv.”

101 Response to CHIR No. 7, question 3.

102 See Section III.5. for a discussion on possible implications of merging loose mail with MMP flows.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Percent of MMP flats out of total flats processed on AFSM

Percent of workhours recorded for MMP flats out of total AFSM workhours
Docket No. SS2022-1 - 59 -

meant to sort loose flats to the same level to which incoming bundles would have been 

sorted on bundle sorters had they not broken.

The manual preparation work needed to induct pieces to AFSM was too slow and pieces 

were fed manually into the machine as they were ready, and not all at once. As a result, the 

number of pieces sorted during the time that employees operate the machines (i.e., while 

workhours accrued) is low.

The preparation work included manual sorting of loose flats to the 3-digit ZIP Code level, 

placing pieces in trays compatible with AFSM equipment, properly facing them, and 

properly aligning them in trays. Facing involves turning individual mailpieces so that their 

address labels faced the scanning device attached to the machine. If the scanner cannot

read address labels as pieces were inducted to the machine, they are treated as “no-read 

rejects.”

The speed at which loose flats were prepared for induction into AFSM also depends on staff 

skill level. Management at one site partly attributed the facility’s low AFSM productivity to 

employees who were too slow to prepare loose mail and feed it into the machine. However, 

management also recounted that their facility had difficulty retaining already-trained 

employees and that newly employed staff lacked adequate skills. The facility’s employees 

cited the difficulty of their jobs were as a common reason for quitting.

While processing of loose flats on the AFSM increases volumes processed on the machine, 

the impact on AFSM productivity is not clear. This is partly because of the lack of data that 

would permit distinguishing volumes for First-Class Mail Flats from destinating loose flats 

volumes for other mail classes that are processed under MMP. Similarly, it is not possible to 

distinguish mail classes for volumes processed in outgoing sort plans. In addition,

workhours charged to MMP operations do not follow reported MMP volumes, as illustrated 

for FY 2021 in Figure III-9. The Commission followed up with the Postal Service about 

determining the impact of loose flats processing from the available data.103 The responses 

provided by the Postal Service indicate that some of the impact might be reflected in the 

time loose mail spends in allied operations. However, further research and analysis are 

needed to determine the impact that merging loose mail with MMP or into the First-Class 

network has on flats processing efficiency and costs.

Impact of automated enhancements on AFSM productivity. Level of automation also plays a 

role in AFSM productivity. An AFSM can be enhanced with Automated Induction (AI) 

system, an Automatic Tray Handling System (ATHS), or both. The AI system automates the 

process of feeding mailpieces into the machine. An AFSM without AI might need two or 

three clerks to manually feed the machine, while only one clerk is needed to monitor the 

automated feeding process.

103 January 13 Response to CHIR No. 5 question 1.a.-d.; Response to CHIR No. 7, question 2.
Docket No. SS2022-1 - 60 -

The ATHS reduces the number of employees, and workhours needed to operate the 

machine during sorting. In Picture III-10, trays with carrier route labels are filled with flats 

destinating on respective carrier routes during the AFSM’s incoming secondary sort plan 

(where 5-digit flats are sorted to carrier route level). As trays are filled, the ATHS clears 

them from the machine and replaces full trays with empty trays. For AFSMs that are not 

equipped with an ATHS, staff clears trays and replaces them manually.

Picture III-10

AFSM with ATHS Enhancement

Managers at sites with both AI and ATHS enhancements said that these automated systems 

made AFSM capable of processing volumes per machine hour at a rate comparable to the 

FSS. Staff at some sites with an AI system explained that they do not use it for sort plans 

with low volumes, such as low-volume FSS rejects. However, they added that manually 

feeding the AFSM is too slow. When mailpieces for a sort plan are not fed to the machine all 

at once, it takes longer to process them. During the run, facility staff must operate the

equipment, regardless of how fast or slowly mailpieces are fed to the machine. As a result, 

slower manual feed leads to fewer pieces processed per employee workhour and lowers

AFSM productivity.

Impact of mailpiece irregularities on AFSM productivity and efficient flats processing. In 

efficient processing operations, the proportion of machinable mailpieces sorted on 

mechanized flats sorting equipment is maximized, and the proportion of machine rejects, 

which need to be sorted manually, is minimized. Commission staff observed that the 

mailpiece quality impacts the proportion of flats that are finalized on an automated 

equipment.

The Postal Service staff at most facilities, described an AFSM as more “forgiving” than FSS, 

in that an AFSM is able to process pieces that FSS rejected. Most examples that staff 

provided included issues related to thin paper quality, particularly for USPS Marketing Mail 

flats. The Commission gathered specific examples of issues with mailpiece quality that 
Docket No. SS2022-1 - 61 -

neither machine could process and that will need to be addressed to improve the efficiency 

of flats operations after decommissioning the FSS equipment at the facilities.

For example, Commission staff observed carts filled with trays of FSS rejects. These trays 

were labeled for dispatch to delivery units because they could not be re-run on the AFSM. 

This was because barcode labels on individual mailpieces could not be read, regardless of 

the equipment. Facility staff also noted that return mail would always be rejected. The 

reason was that return address labels failed to adequately cover the original barcodes, 

causing issues for equipment when scanning mailpiece labels. Another example was an 

entire shipment of catalogues that were manually sorted because they had lotion sample 

inserts, which neither FSS nor AFSM could accept.

The above examples resulted in inefficient manual sorting of flats to carrier route and 

manual casing to DPS, for mailpieces that were intended to receive these sortations on 

automated equipment. However, in each example, the inefficient processing involved 

different degrees of “wasted” resources. In the first example, flats went through the first 

pass on FSS, were rejected, and were identified by staff as requiring manual sorting, rather 

than being re-run on AFSM. Flats in the last example resulted in the most resources wasted 

because the facility’s staff was not able to detect sample inserts when preparing mail, 

which would have led staff to have the shipment bypass machine processing. Consequently, 

the entire shipment was run first on FSS and rejected, then re-run on AFSM and rejected. 

Only then was the shipment transported to destinating DDUs for manual sorting, with no 

time available to sort pieces and deliver them timely.

Adequate mailpiece quality is necessary to prevent inefficient use of resources and prevent 

manual sorting and casing of mail that qualifies for discounted prices based on supposedly 

avoided costs. The Commission’s operational expert described repeated discussions

between the Postal Service and mailers over the years, including various proposals related 

to flats quality standards that would ensure machinability. However, the operational expert 

also commented on resistance from mailers, including mailers’ concerns that changed flats

preparation quality standards might disqualify their pieces from presort discounts, or 

significantly reduce their discount levels.

(3) Substitution of FSS by AFSM

The impact of FSS decommissioning on flats processing is difficult to predict because it 

depends on many factors. The Postal Service explains that it considered input from Retail 

and Delivery Operations but does not describe the input that it received.104 Commission 

staff observed the most acute staff shortage at a DDU that served only FSS zones. That DDU 

received about 10 to 20 percent of flats sorted only to carrier route. These flats needed to 

be manually cased. The DDU also received regular shipments of machine incompatible 

Periodicals flats that were not sorted at the upstream facility and needed sorting to carrier 

route and casing. For this DDU, the discontinuance of FSS operations will impose 

104 Response to CHIR No. 2, questions 3.c.-d.
Docket No. SS2022-1 - 62 -

substantial strain on staffing, as the remaining majority of flats received by the DDU will 

require the same manual casing.

As for mail processing facilities, the Postal Service explains that staffing strains related to 

the COVID-19 pandemic are ongoing and that running FSS and AFSM operations 

concurrently has also strained staffing. Id. The Postal Service claims that discontinuing FSS 

operations would allow it to properly staff AFSM operations and improve overall 

efficiencies. Id. The Commission’s operational expert added that removal of FSS equipment 

would free up maintenance staff from previous FSS operations and that with some training, 

this staff might become available for other operations, such as AFSM.

At most sites where one or all FSS machines were decommissioned prior to our visits, 

management described no major impact on operations. As management explained, this was 

because mailers got advance notice about changes in FSS operations and started to presort 

their flats bundles to carrier route levels, instead of FSS schemes. Carrier route bundles 

need no additional processing and are moved directly to DDUs.

However, a manager at one site (P&DC 7), which never operated FSS equipment, described 

an increase in flats volumes related to the decommissioning of a FSS machine at another 

facility (P&DC 2). Prior to the decommissioning, P&DC 7 processed FSS rejects from P&DC 

2’s FSS operations. However, P&DC 7 management explained that it started receiving about 

10 pallets of flats per day from P&DC 2 for processing to carrier route because P&DC 2 

could not handle all of its daily flats volumes after one of its three FSS machines were 

decommissioned. For P&DC 7, management described a notable impact on operations, 

which the facility’s management attributed to a combination of the recent increase in 

volume related to the FSS machine removal from P&DC 2, as well as a steady increase in the 

amount of loose mail and FSS rejects over past several years, coupled with a recent removal 

of one of its 3 AFSM machines.

At sites where FSS decommissioning had not yet occurred but was expected, management 

anticipated no substantial impacts and explained that their AFSM equipment had sufficient 

capacity available to absorb increased flats volumes. However, Commission staff also 

learned that these general expectations of no impact from FSS machine removals were 

based on Postal Service Headquarters projections for increases in flats volumes that would 

require sorting on AFSM at impacted sites. The Commission does not have information on 

site-specific projections for volume increases in AFSM operations.

Discussions with Postal Service facility staff also revealed some uncertainty. At one site, the 

manager stated that their AFSM equipment might not be able to handle more flats than 

Postal Service Headquarters had projected for this site. This was partly because the facility 

had one of its AFSM machines recently removed on the basis of declining flats volumes.

Facility staff also expressed uncertainty related to the complexity that FSS sort plans 

revisions created for their AFSM operations. Management at one site was not confident that 

reverting to simpler, pre-FSS era sort plans would be smooth and immediate.
Docket No. SS2022-1 - 63 -

Discussions with mailers suggested that as flats volumes have declined, presorting bundles 

to finer levels to qualify for deeper discounts has become more difficult. Carrier route 

presort represents the finest presort level possible. as the name suggests, a carrier route 

bundle can include only flats for a single carrier route. FSS schemes represented 

opportunities for mailers to combine pieces for several carrier routes, from several 5-digit 

ZIP Codes, in FSS scheme bundles.

It is unclear why facilities expect that most FSS scheme bundles would be presorted to 

carrier routes following removal of FSS operations. It is also unclear how the Postal Service 

projected flats volume increases for each impacted site. No analysis of the operational or 

cost impacts of FSS decommissioning has been provided to the Commission, and it is not 

clear whether the Postal Service solicited inputs from mailers on its decision to 

decommission FSS operations.

c. Manual Sorting at Mail Processing Plants

Manual flats stations observed by Commission staff were not crowded with containers of 

broken bundles, trays of rejects from FSS or AFSM machines, or shipments of flats 

incompatible with flats sorting equipment. Most pieces that Commission staff saw manually 

sorted and cased (placed on shelves marked with destination labels) were newspapers. 

Most facilities’ management described no changes in manually sorted flats in the past 

several years.

Facility staff explained that mail processing facilities manually sorted destinating flats for 

dispatch to DDUs. Most DDUs serve only one 5-digit ZIP Code area but a small portion of 

DDUs serves five or more 5-digit ZIP Codes. DDUs that serve multiple ZIP Codes tend to be 

located in areas with high population density and high delivery-point density, and many of 

them were included in FSS zones. For those DDUs, mail processing sites sort flats that 

require manual sorting to the 5-digit ZIP Code level. Once at DDUs, pieces are manually 

sorted to carrier routes (by clerks) and manually cased to DPS (by carriers).

Outgoing flats are manually sorted to the 3-digit level at mail processing facilities.

Staff described manually sorting non-machinable flats (such as newspapers), rejects from 

flats sorting equipment, and MMP flats. Discussions with management suggested that 

manually sorted non-machinable and reject flats are sorted separately from manually 

sorted MMP flats. Commission staff did not observe areas where MMP flats were manually 

sorted during the visits. Manual sorting of non-machinable flats is expected for those pieces 

that are entered into the postal network as non-machinable mail. Due to the less efficient

manual sorting of non-machinable flats, non-machinable mail rates apply to these flats 

products by default.
Docket No. SS2022-1 - 64 -

Picture III-11

Manual Sorting Area at a Visited Site, with Mostly Newspapers

As for rejects from flats sorting equipment, the inefficiency stems from the fact that the cost 

incurred by the Postal Service to sort them and prepare them for delivery is not recovered 

from the rates for which these pieces qualified when they were entered into the postal 

network. For example, flats presorted to FSS scheme qualify for the deepest discounts, 

because they are assumed to be processed to DPS on automated equipment and to require 

no manual work. However, where a mailpiece irregularity affects an entire shipment, postal 

employees may need to manually sort every piece in the shipment for delivery. Postal 

Service staff at visited sites frequently described mailpiece irregularities such as mailpieces

being too thick or too thin—a flat mailpiece that is too thin cannot stand on its side,

collapses, and may cause jams—or not bending sufficiently. Staff also described thin paper 

quality as frequently resulting in machines ripping off cover pages, along with address 

labels, which rendered mailpieces “no-reads.”

As noted above, mail processing facilities’ staff explained that they manually sort 

destinating flats to the 5-digit ZIP Code level and not deeper. Facility staff suggested that 

mailpieces rejected from FSS require no or minimal manual sorting at mail processing 

facilities, because FSS rejects are already sorted to the 5-digit level when they are fed into 

the machine for processing.

However, at one site, management commented on the complexity that FSS schemes 

introduce for flats processing. Management explained that as FSS schemes are revised or 

new FSS schemes created, 5-digit ZIP Codes from more than one 3-digit ZIP Code area and 

for more than one DDU can be included in one FSS scheme. The Postal Service’s responses 

to questions on its method for estimating manual volume also indicate that FSS flats may 
Docket No. SS2022-1 - 65 -

need manual separations to both the 3-digit and 5-digit ZIP Code levels at mail processing 

sites before they can be dispatched to DDUs.105

Regardless of whether rejects from flats sorting equipment significantly impacted manual 

sorting at mail processing facilities, the impact on DDUs was substantial. The rejected 

volumes and the sorting jobs that generated them dictate the amount of manual sorting 

that DDU clerks must do to prepare mail for delivery.

For example, “no-read” rejects cannot be re-run on AFSM because AFSM scanners cannot 

read faulty barcode labels. Dispatching “no-read” mail to DDUs requires clerk workhours to 

manually sort pieces to carrier routes. On the other hand, where FSS rejects flats due to an 

irregularity that FSS could not handle but that is acceptable to AFSM, the flats are re-run on 

AFSM and sorted to carrier route before being dispatched to DDUs. Such carrier-routesorted flats still require manual casing, although they avoid manual sorting by DDU clerks. 

As such, the type of mailpiece irregularity determines the amount of sorting that can be 

performed on automated equipment, at mail processing facilities, and the amount of 

manual sorting done by clerks at DDUs.

Every mail processing facility that Commission staff visited described receiving daily 

shipments of machine-incompatible flats that bypassed sortation on automated equipment. 

Facility staff described expediting such mail to DDUs for manual sortation, completely 

bypassing automated processing on the basis that most shipments were already presorted 

for distribution to DDUs. When DDUs received such shipments, clerks had to open each 

bundle and manually sort pieces to carrier routes.

Manual sorting productivity is calculated from volumes and employee workhours recorded 

in respective data systems for respective MODS operations. To explain low productivity of 

manual sorting at one mail processing facility, management commented that productivity 

values are only as reliable as the data used to calculate them and described challenges with 

accurate recording of workhours. This site’s management explained that there are two 

requirements for accurate workhour recording: (1) an individual employee must 

remember to clock in and out as the employee moves between operations; and (2) for the 

employee to be able to clock in and out of operations, the employee’s supervisor first needs 

to change the employee’s base operation in the system. Other facilities confirmed that they 

focused on clocking in and out only at the beginning and end of employees’ shifts and did 

not track much employees’ movement between operations during shifts.

If manual workhours recorded in MODS reflect the number of staff clocked into one base 

operation in a shift, it is not possible to interpret reported productivity values as changes in 

employees’ actual productivity and to attribute these changes to staff skill level, training, or 

changes in manual flats volumes.

105 Response to CHIR No. 7, question 2; January 13 Response to CHIR No. 5, question 1.g.
Docket No. SS2022-1 - 66 -

Not only are workhours charged to respective manual operations potentially unreliable, 

the facilities also do not conduct physical surveys of manually processed flats volumes.106

This makes both values used to calculate manual sorting productivity (volumes and 

workhours) unreliable.

Starting in FY 2016, the Postal Service replaced physical manual volume surveys with socalled “allowances.” Id. The Postal Service states that these allowances represent maximum 

fractions that can be applied to each facility’s automated flats volumes to estimate 

manually processed flats. Id. The Commission has followed up with the Postal Service to 

better understand whether application of allowances produced accurate estimates of 

manually sorted flats at mail processing facilities.107

In its response, the Postal Service explains that the determination of facility-specific

allowance starts with the same baseline fraction of 7 percent applied to facility’s automated 

flats flows, but also describes certain additional nuances in the estimation of manually 

processed flats volumes at the facility level. Id. questions 2.b., 2.d.-e. For example, if facility 

A sends its loose or reject flats to facility B for manual processing, facility A can choose to 

not report manual volumes, but facility B is unable to report more than the maximum 

fraction of its own automated flats flows as manually processed. Id. In addition, the 

documentation that the Postal Service cites for calculation of the final facility-specific 

manual volumes suggests that Postal Service Headquarters reviews and approves the final 

manual volume percentages and counts for each facility, without any further details on the 

final review process (e.g., the extent of consultation with facility management).

108

The Commission is concerned that capping the estimate at 7 or any other percent109 and 

not letting facilities report manual volumes might mask potentially increasing volumes that 

need manual processing. The Commission is also concerned about the specific instance of 

machine-incompatible volumes, which most facilities reportedly have been receiving for 

years, with some facilities seeing increases in these volumes. Because the allowances are 

applied only to automated workloads, they do not capture the machine-incompatible 

volumes that bypass automated processing.

The Postal Service claims that the allowance method has led to a reduction in the estimated 

manual flats for “a majority of facilities” compared to previous manual flats estimates, 

when volumes were counted. Id. question 2.g. However, the Postal Service also states that 

“[a]ll manual flats volume flows were considered and analyzed by the MODS coordinators 

in July 2015 and accounted for in the calculation for manual flat volumes,” implying that 

machine-incompatible volumes were accounted for when allowances were determined in 

106 Docket No. ACR2021, Library Reference USPS-FY21-23, December 29, 2021, PDF file “USPS-FY21-23.Preface.pdf,” at 1 (FY 2021 MODS 

Productivity Preface).

107 Response to CHIR No. 7, question 2.

108 United States Postal Service, Management Operating Data System, Handbook M-32, September 2018, at 12.

109 Response to CHIR No. 7, question 2.b.
Docket No. SS2022-1 - 67 -

2015. Id. question 2.f. This does not address the question of whether allowances based on 

operations in July 2015 adequately capture increasing manual flats volumes.

In Docket No. ACR2022, the Postal Service states that the significant decreases in manual 

flat productivities since FY 2016, when compared to prior years, imply that the allowances 

underestimate flats workloads at mail processing sites.110 The Postal Service continues to 

describe manual flat productivities as “sufficiently unreliable” and does not recommend 

their use. Id. at 2.

Without reliable data, reliable analysis of manual processing productivity is not possible.

The Commission notes that the lack of actual counts of flats that are manually processed 

prohibits accurate analysis of the extent of inefficient manual sorting that automation flats 

receive, or the associated impacts on mail processing cost.111 Observations from facility 

visits and the Postal Service’s responses to Chairman’s Information Requests (CHIRs)

suggest that the implications of manual processing productivity require further research.

d. Productivity and Service Issues in Allied Operations

Sorting activities are referred to as “pure distribution” while activities associated with 

handling mail between sorting operations are part of allied operations.

The Commission has previously reported on the cost implications and negative impacts on 

service performance of inefficiencies in allied operations112

Preparation for bundle processing. Most staff at P&DC sites described assessing bundle 

integrity by visually inspecting flats drop shipments when mailers’ trucks first arrived at 

the facility. Staff similarly inspected bundles arriving from upstream mail processing 

facilities, whether on postal vehicle transportation or on contracted highway contract route 

(HCR) transportation.

Staff at P&DCs described only occasional issues at arrival, mostly related to bundles being 

improperly secured during transportation and breaking, or their wrapping/strapping 

material becoming loose. Staff clarified that this was because most bundles arrived at their 

facilities either in cardboard containers or secured directly on pallets, which provided good 

support for bundles.

Staff at NDCs described issues with bundle integrity upon arrival that differed from those at 

P&DCs. One of the NDCs visited received about 50 percent of bundles in sacks, the other 50 

110 Docket No. ACR2022, Library Reference USPS-FY22-23, December 29, 2022, PDF File “USPS-FY22-23.Preface.pdf,”at 1-2 (FY 2022 MODS 

Productivity Preface).

111 The Area In-Plant Support uses the End Of Run data to calculate the volume for each MODS facility which is then submitted to the Postal 

Service’s headquarters for approval. The percentages used in the calculation for manual flats vary by mail level and site. See Docket No. 

ACR2022, Library Reference USPS-FY22-NP18, December 29, 2022, folder “USPS-FY22-NP18,” folder “USPS-FY22-NP18 MODS Data,” PDF file 

“M-32 MODS Handbook.pdf,” at 11-16, 113-39. See also Response to CHIR No. 7, question 2.

112 See FY 2015 ACD at 173-74; FY 2016 ACD at 167; FY 2017 ACD at 178-79; FY 2018 ACD at 218-19; FY 2019 ACD at 171-72; FY 2020 ACD at 

256-57; FY 2021 ACD at 258-59.
Docket No. SS2022-1 - 68 -

percent on pallets. Staff at another NDC said that about 20 percent of its bundles came in 

sacks. Management at both NDCs explained that bundles transported in sacks were more 

likely to have bundle integrity issues than bundles transported in containers or on pallets. 

The Postal Service has proposed eliminating sacks as containers for flats.113

Another difficulty staff at NDCs described was that facility staff could not assess bundle 

integrity before handling or emptying sacks. Any bundles with compromised integrity may 

have broken during sack handling by NDC employees. Bundle integrity was further 

compromised during the sack shake out process.

NDCs devoted a substantial number of employees to manual inspection of individual 

bundles that did not break during unloading and the sack shake out process. Bundles that 

NDC staff deemed not able to withstand processing on automated bundle sorting 

equipment and/or subsequent transportation through the network were stabilized. For 

example, NDC staff added additional strapping when they considered existing strapping 

insufficient for the bundle size or content, and many bundles (such as those arriving 

strapped with rubber bands or bundles for which strapping became loose during 

transportation) were re-strapped.

NDC employees specifically mentioned co-mail bundles as requiring close attention, 

because they tend to be larger, heavier, and the pieces in the bundles are less uniform.

At one NDC, Commission staff saw what the employees described as “super bundles”—

three or four smaller bundles tied into what appeared to be one individual bundle. Facility 

staff explained that bundling of bundles was not permitted by the DMM and that identifying 

these bundles was very challenging because “super bundles” appeared no larger than 

single large bundles. As the NDC staff opened one such “super bundle,” commission staff 

observed that each of the four bundles included in it destinated in a different state. The 

employees explained that all the bundles would be routed to the address on the first bundle 

which meant that three out of the four bundles would be misrouted.

Staff at the facilities added that they recognize which mailers ship “super bundles” and comail bundles and that facility management assigns additional staff on days shipments from 

those mailers were expected.

Preparation for individual piece processing. Another allied operation is preparing mixed 

pieces from broken, loose, and reject bundles (loose flats) for individual flats processing on 

automated equipment.

113 Removal of Sacks—USPS Marketing Mail and Periodicals Flats, 87 Fed. Reg. 63,985 (Oct. 21, 2022) (to be codified at 39 C.F.R. pt. 111).
Docket No. SS2022-1 - 69 -

Picture III-12

A Bin with Mixed Pieces from Broken Bundles

Facility staff explained that loose flats from bundles that had been pre-sorted to the 3-digit 

level had to be first manually sorted to the 3-digit level, and then sorted to the 5-digit level

on AFSM equipment if possible.114 However, the operational expert stated that in many 

cases once a bundle breaks the individual flat will be sorted to its final destination in 

manual operations rather than automated ones.

Mail processing network design. Staff at mail processing facilities and transportation hubs 

visited by Commission staff performed operations limited to only certain shapes of mail, or 

mail classes, or sort levels, or some combination of mail attributes. The more narrow the 

range of facilities’ operations, the more critical it was that mail arrived in time to align with 

planned processing windows.

One site (P&DC 7) was in a group of three mail processing facilities (the group included 

P&DC 2 and an NDC). These three facilities shared processing jobs and moved mail 

frequently between the different sites. Below, the Commission provides a simplified 

illustrative example of how destinating USPS Marketing Mail flats flow between the three 

facilities. See Figure III-10. A more detailed description of the flow is included in Appendix 

A, Section III.B.4.d. Analysis.

114 The Postal Service explains that these activities were charged to mail preparation operations associated with the machine and sort type for 

which they were being manually prepared. January 13 Response to CHIR No. 5, questions 1.a.-d., f. These workhours are not included in the 

Postal Service’s calculated productivity values for machine equipment and represent workhours spent in allied operations. Response to CHIR 

No. 1, questions 5.c.-d.
Docket No. SS2022-1 - 70 -

Figure III-10
Docket No. SS2022-1 - 71 -

The collaboration and division of processing jobs between the three sites is more complex 

than depicted in the simplified example above and requires frequent transportation 

between facilities. Another similar group of facilities referred to “shuttle transportation” 

running between their interconnected operations.

Facility staff stated that this workload sharing made planning difficult. Management at 

P&DC 7 noted that bundle breakage rates at the upstream NDC or FSS reject rates at P&DC 

2 could not be projected, which made daily workload unpredictable. This impacted timely 

processing of the flats that did not have any irregularities or cause any inefficiencies.

Another facility processed only outgoing parcels and destinating flats bundles on its APPS 

equipment. Management stated that the bundle processing window was too long (8 a.m. to 

11:30 a.m.) for the low bundle volumes that the facility received. Management described 

situations in which it ran out of flats bundles by 10 a.m. and switched to parcel processing. 

For bundles that were dropshipped at the facility between 10 a.m. and 11 a.m. (i.e., within 

the CET for the described bundle processing window), the staff either delayed processing 

of the flats bundles, or allow APPS and employees to be idle when there were no bundles to 

process. In the first instance, service performance scores for the affected flats that arrived 

within the CET suffered.

Difficulty accurately projecting workload and impact on timely operations. Management 

frequently described a great deal of uncertainty associated with volumes included in 

scheduled drop shipments. One site gave an example of mailers who indicated they were 

shipping 120 pallets of bundles at the time of scheduling but actually shipped only 60 

pallets. Another example involved mailers who indicated there would be Periodicals 

bundles in their shipments (which management stated they were obligated to accept any 

time that the facility was staffed) but only parcels were included on the arriving trucks. 

Management explained that because of separate sort plans for parcels and bundles, such 

deviations disrupted planned operations and necessitated decisions that increased time 

spent in allied operations either for flats bundles or for parcels.

Despite discussions with Postal Service management, it is not clear what causes the 

discrepancies described above’ It is also not clear whether the Postal Service routinely 

tracks their occurrence, or whether it charges mailers for any costs that it incurs as a result 

of accepting these drop shipments.115

e. Transportation Issues at Mail Processing Facilities and 

Hubs

As described in Sections III.B.3.a.-b., every mail processing facility and transportation hub 

visited by Commission staff performed operations that were limited to certain activities.

115 See United States Postal Service, Publication 804, Drop Shipment Procedures for Destination Entry, October 2013, available at 

https://about.usps.com/publications/pub804.pdf.
Docket No. SS2022-1 - 72 -

A complex surface transportation network connects operations performed at different 

facilities. Any deviations from planned operations—whether deviations from projected 

volumes or delayed arrival of scheduled shipments—result in increased trip frequency 

between these sites. Management at the visited facilities described prioritizing service 

performance, i.e., they dispatched mail on scheduled transportation and ordered additional 

Postal Vehicle Service (PVS) trips for delayed mail. When delayed mail was intended for 

HCR transportation, facilities either tried to put this mail on outbound HCR trucks 

departing from nearby plants or scheduled extra transportation.116

As noted in Section III.B.1.b. and Section III.B.3.b., the Postal Service’s network included 13 

STCs in FY 2021 and FY 2022.117 The main functions of STCs are to consolidate mail in 

containers and increase truck space utilization by containers. Fuller containers, 

transported on fuller trucks, represent more efficient transportation operations and lower 

unit transportation cost.

At one STC, Commission staff learned that efforts to better fill mail container space on 

surface trucks were constrained by the fact that only mail of the same mail class and with 

the same destination could be combined in containers. The Postal Service representative at 

the STC added that as flats volumes declined, the task became more difficult.

Picture III-13

Stacked Cardboard Containers (on the left) and 

All-Purpose Container (APC) (on the right) Filled with Flats Tubs

 

116 See Docket No. N2021-1, Direct Testimony of Stephen B. Hagenstein on Behalf of the United States Postal Service (USPS-T-3), April 21, 2021, 

at 8 n.3. for an estimate of cost per mile for regularly scheduled HCR transportation in 2021; see also Docket No. N2021-1, Responses of the 

United States Postal Service to Questions 1-11, 13-34 of Presiding Officer’s Information Request No. 1, May 17, 2021, question 17.d. for 

estimates of cost per mile for extra transportation in 2021.

117 Commission staff learned during STC visits that all 13 STCs are contracted operations, with some Postal Service staff employed on each site 

full time. Commission staff also learned that the Postal Service employees coordinate between the contractors and the Postal Service 

Headquarters. For the remainder of the discussions related to STC site visits, the Commission will refer to the Postal Service employees with 

whom Commission staff discussed STC operations, as Postal Service representatives.
Docket No. SS2022-1 - 73 -

Cardboard containers are widely used on long-distance trucks because they can be stacked 

and represent better use of truck space. However, because of low flats volumes, cardboard 

containers are often not filled to capacity with flats tubs. In such cases, it is not possible to 

stack them because the bottom container would not support the weight of the container 

placed on top and would collapse. The Postal Service representative at one of the visited 

STCs explained that for that reason, it frequently used APCs or over-the-road (OTR) 

containers when cardboard container could not be filled to capacity. However, while using 

APCs and OTR containers improved container space used when flats volumes were low,

they also resulted in less cubic space used on trucks, since APCs and OTR containers cannot 

be stacked. The operational expert that the Commission worked with noted past efforts to 

replace cardboard containers with reusable and collapsible plastic containers that are 

stackable. The expert added that plastic containers would reduce material costs, since 

plastic is a more durable material than cardboard, and would allow better cubic space 

utilization on surface trucks because they are always stackable.

As for truck space utilization, staff at the mail processing facilities stated that they generally 

combined mail shapes and classes on trucks. The complexity and interconnected nature of 

the processing and transportation networks did not allow for meaningful discussion of the 

details of what happens when mail shapes and/or mail classes did not share truck space.

During one facility visit, Commission staff learned that STCs can operate as origin or as 

destination aggregation centers. The Postal Service explains that origin STCs consolidate 

mail that originates within their local service areas, and dispatch consolidated mail onto 

long-distance trucks through the surface transportation network.118 The Postal Service 

further explains that destination STCs consolidate mail that arrives on inbound longdistance transportation, and dispatch consolidated mail to its local area processing 

facilities. Id.

At a destination STC, the Postal Service representative described frequent transportation to 

local area mail processing facilities, included in two 3-digit ZIP Code areas, and not more 

than a 2-hour drive time from the STC. The representative also described operating about 

10 long-distance HCR contracts, with daily trips, including coast-to-coast trips. The 

representative explained that all its HCR trips were round trips.

It is not clear why any STCs would consolidate destinating mail onto short-distance truck 

trips to local mail processing sites. Transporting miscellaneous letters and flats on 

expensive, long-distance transportation represents a very costly and inefficient operation. 

As trip frequency increases, whether to mitigate impacts of processing delays on service 

performance, insufficient capacity on departing trucks, or due to interconnected operations 

performed in separate facilities, trucks are at a lower capacity. This increases 

transportation cost per transported mailpiece, with cost increases substantially higher for 

ad-hoc transportation.

118 Responses of the United States Postal Service to Questions 6-8 of Chairman’s Information Request No. 5, January 18, 2023, question 7

(January 18 Response to CHIR No. 5).
Docket No. SS2022-1 - 74 -

f. Last Mile Delivery – Inefficiencies Identified at DDUs

The Commission has reported on delivery costs, and more specifically on costs associated 

with manually casing of flats, each year since FY 2015.119 In its FY 2021 ACD, the 

Commission noted that the 50-percent reduction in flats volumes coincided with an 

insignificant decline in costs associated with manual casing of flats between FY 2008 and 

FY 2021. FY 2021 ACD at 260-61. In FY 2008, all flats were manually cased because the 

Postal Service did not have FSS equipment. FY 2015 ACD at 179. In FY 2021, about 100 FSS 

machines were operational for sorting flats to DPS, in 47 locations.120

Mail processing facilities that processed mail for the three DDUs that the Commission staff 

visited operated FSS equipment at the time of the visits. Below, the Commission describes 

how the numerous mail irregularities discovered at mail processing sites impacted 

operations at the DDUs, including casing of flats.

Manual sortation of automation flats. As described above, every mail processing site visited 

had been receiving regular shipments of machine-incompatible flats, for many years. These 

shipments were originally intended for FSS processing to DPS. Therefore, DDUs expected to 

receive them sorted to DPS and thus requiring no manual sorting by clerks or casing by 

carriers. In other words, letter carriers at these DDUs were expected to merely pick up 

these trays as they were leaving the office for delivery.

Picture III-14

Flats That Arrived from an Upstream P&DC Sorted to DPS

119 FY 2015 ACD at 177-80; FY 2016 ACD at 168-69; FY 2017 ACD at 180-81; FY 2018 ACD at 221-22; FY 2019 ACD at 173-74; FY 2020 ACD at 259-

60; FY 2021 ACD at 260-62.

120 United States Postal Service, Office of Inspector General, Report No. SM-WP-15-001, Challenges in Controlling Costs with Standard Mail Flats 

and Periodicals, February 26, 2015, at 8, available at https://www.oversight.gov/sites/default/files/oig-reports/sm-wp-15-001_0.pdf (OIG 

Report No. SM-WP-15-001).
Docket No. SS2022-1 - 75 -

The largest of the three DDUs visited had only FSS zones. However, the manager there 

described that between 10 and 20 percent of flats come from the upstream P&DC carrier 

routes, and that the DDU receives about two pallets of Periodicals per week that need 

manual sorting to carrier routes. On the day of our visit, Commission staff saw four pallets 

of Periodicals that required manual sorting to carrier routes. The pieces, shown on Picture 

III-15, were too thick for FSS or AFSM equipment.

Picture III-15

One of the Pallets with Machine Incompatible Magazines

The labels on all pallets indicated that the pieces should have been sorted to DPS at the 

upstream P&DC. The postmaster confirmed that the individual flats pieces were too thick 

and incompatible with FSS equipment. The pallets included bundles sorted to 5-digit ZIP 

Codes, and destinating in the DDU’s two largest ZIP Codes. The postmaster noted just one 

of the destinating ZIP Codes included nearly 30 percent of this DDU’s carrier routes. The 

postmaster explained that all bundles needed to be opened, and their pieces manually 

sorted to the carrier route by clerks. The postmaster added that their delivery would 

necessarily be delayed because the DDU did not have sufficient clerk staff to manually sort 

this mail within its service standard window. To explain how common such shipments 

were, the postmaster described receiving about two pallets of machine-incompatible flats 

per week, over the course of several years.

Other volumes that needed manual sorting to carrier route and manual casing to DPS 

included shipments of flats that neither FSS (if applicable) nor AFSM could process. These 

included “no-read” flats, or flats with sample inserts that neither machine type could 

handle and were rejected.
Docket No. SS2022-1 - 76 -

The postmasters at two of the three visited DDUs described increasing volumes of flats 

rejects coming from upstream P&DCs. Additionally, they explained that they have been 

increasingly receiving First-Class Mail mixed with USPS Marketing Mail in recent years. The 

postmasters clarified that combining letter- and flat-shaped mail of different mail classes 

does not present issues for carriers, but added that when packages are included in 

containers with a mix of mail classes and shapes, they could delay letter carriers for 

delivery because of the time needed to separate packages from other mail shapes. The 

postmasters described this issue as more concerning during peak time when package 

volumes were high. Postmasters explained that for mail carriers to deliver all daily volumes 

during peak time, carriers made two trips per day for certain carrier routes—one in the 

early morning to deliver packages only, and a regular trip to deliver the rest of the daily 

mail. Separating packages from letter and flat mail in such mixed mail shape containers 

caused delays in carriers’ early morning departures from the office, which in turn delayed 

their departures for regular deliveries.

The visits to mail processing sites and DDUs revealed that flats mail irregularities impacted

operations at DDUs significantly because they increased requirements for manual 

workhours, which DDUs could not plan for or did not have sufficient staffing to perform in 

a timely manner. The impacts were more profound for high delivery point density DDUs

than they were for lower density DDUs.

Manual casing of flats. All carrier-routed flats were manually cased at DDUs. For high 

delivery point density areas, flats not processed to DPS at P&DCs substantially increased 

the time needed to manually case them.

DDUs are not able to increase staffing to accommodate large increases in daily workload. Of 

the three DDUs visited, the DDU that was most impacted by the inefficient processing of 

flats had more than 200 full-time employees. Yet, this DDU described an acute shortage of 

staff and reported difficulty delivering mail insufficiently processed at the upstream mail 

processing facilities in a timely manner. The operation expert that the Commission worked 

with commented that DDUs of this size are few and are not representative of typically sized 

DDUs.

5. Summary of Newly Identified Causes of 

Inefficiencies

True prevalence of bundle breakage is unknown. The Postal Service states that it does not 

track bundles that do not receive scans on bundle sorters. Response to CHIR No. 4, 

questions 4.b., 4.d., 5.d., 5.f. That means that the reported bundle breakage reflects only the 

percentage of bundles that were inducted onto bundle sorters and were not finalized on 

the equipment because they broke during sortation.

The Postal Service does not track bundles that break during transportation, when 

unloading from trucks, or while moving bundles from docks to mail processing floor, all 

situations that occur before they could be inducted to bundle sorting equipment. Neither 
Docket No. SS2022-1 - 77 -

does the Postal Service track loose bundles, which bypass machine processing and are 

treated as broken. Bypassing machine processing may prevent bundle machine stoppages 

and prevent reporting of breakage, but it does not prevent the inefficient manual

processing that these bundles receive.

Lack of relevant data prevents effective communication and corrective action. One of the 

efforts that the Postal Service has made to address bundle breakage was the 

implementation of the Mailer Irregularity Application (MIA).121 The MIA was intended to 

record the specific irregularities associated with bundles that caused inefficient bundle 

processing.122 The Postal Service described that it intended to use these data to 

communicate with mailers about correcting the specific irregularities associated with their 

shipments prior to entry of any new pieces into the postal network. Id. at 19.

However, Commission staff did not observe consistent recording of bundle irregularities 

during site visits, and some facilities stated that they simply did not record such data. A site 

that was among those that did not record bundle irregularities processed large volumes of 

co-mail bundles.123 Management consistently described co-mail bundles as the worst in 

terms of bundle preparation quality, leading to inefficient processing.

The Commission followed up with the Postal Service on the recorded data and the actual 

process the Postal Service has in place to improve mail preparation quality by mailers. The 

Postal Service notes that since implementation of MIA in FY 2020 and through FY 2022, 

“7,382 individual mailers incurred irregularities.”124 The Postal Service states that 

irregularity data “can be” recorded at all processing stages but that staff in mail processing 

operations “does not identify every incident.” Id. questions 1.a., 3.c. The Postal Service 

clarifies that “irregularities are categorized into one of five irregularity types: Piece, 

Bundle, Pallet, Sack, and Tray.” Id. question 1.a. The recorded irregularities “are not limited 

to flat-shaped mail.” Id. For example, the MIA might include a record for a mailpiece for 

which polywrap did not have sufficient strength. However, the record does not indicate the 

shape of the mailpiece.

Mail irregularities might be identified at various stages between mail induction to the 

postal network and final piece processing. Id. question 1.a. For example, broken bundle 

strapping could be identified between unloading from mailer’s truck and final bundle 

sorting operation, but a lotion sample that may have been included in a catalogue might 

only be identified after an entire catalogue shipment was processed and rejected by both 

FSS and AFSM machines.

121 The Postal Service implemented the MIA in FY 2020. See Docket No. ACR2021, Library Reference USPS-FY21-29, December 29, 2021, PDF file 

“FY21-29 Service Performance Report.pdf,” at 18 (Docket No. ACR2021, FY 2021 Service Performance Report).

122 Docket No. ACR2021, FY 2021 Service Performance Report at 18.

123 The management at this site stated that they considered a certain amount of breakage to be expected and part of the process.

124 Response to CHIR No. 6, question 3.a.
Docket No. SS2022-1 - 78 -

The MIA replaced a previously used system for recording mail irregularities—Electronic 

Mail Improvement Reporting (eMIR). Id. question 2. Based on the Postal Service’s 

description, it is reasonable to suggest that eMIR collected data with more relevant details, 

such as mailpiece description, mail class, processing category, transportation, etc. Id. 

However, eMIR was retired, and its data are no longer accessible. Id. It is unclear why the 

Postal Service replaced eMIR, which recorded irregularities at a more granular level, with 

the MIA, which does not even identify the shape of the mailpiece for which an irregularity is 

recorded. Id.

During facility visits, private presort mailers emphasized the importance of effective 

communication between the Postal Service and the industry. On the topic of bundle and 

flats preparation, mailers expressed willingness to do their part but explained that if any 

mail preparation irregularities stemmed from their operations, the information that the 

Postal Service provided on their shipments did not allow them to track shipments to their 

operations. Without relevant data, they could take no corrective action.

In support of their arguments, mailers attributed the success and efficiency of their 

operations to effective communication with their own customers, describing customer 

education on mail preparation as a high-return investment. For the Postal Service, mailers 

stressed the necessity to understand the sources of inefficiencies in its operations. They 

expressed frustration about the numerous initiatives, costly investments, and nation-wide 

network changes, which failed to provide the projected savings and many of which 

introduced new inefficiencies.

The Postal Service facilities’ staff questioned the value of recording mail irregularities, 

including their scanning practices. Every mail processing facility visited has received 

regular shipments of machine-incompatible and low-quality mail for many years. The work 

that mail processing facilities and DDUs’ clerks, mail handlers, mail carriers perform might 

be inefficient, but there might also be no efficient way to process irregular mail, whether 

the mail’s irregularity stems from mailers not complying with mail preparation standards 

enumerated in the DMM or from DMM standards not accurately reflecting machines’ 

capabilities. As these employees described recording and reporting on irregularities and 

specific shipments to the Postal Service Headquarters, without action or support in return, 

they also expressed feeling unsupported in their difficult jobs. At a few facilities, 

management pleaded for support, describing staff quitting because of the difficult jobs 

expected of them. Hiring new, low-skill staff to process inadequately prepared mail further 

decreases the Postal Service’s overall processing efficiency.

Without recording relevant data, providing the data to the origin mailer, and holding repeat 

offenders accountable, no improvements in the efficiency of flats processing operations can 

be achieved.

Irregular mail possibly receives upgraded service. Several facilities explained that they 

combined flats from broken/loose/reject USPS Marketing Mail and Periodicals bundles 

(loose flats) with MMP flats. They described the MMP as including First-Class Mail Flats and 
Docket No. SS2022-1 - 79 -

some other 2- to 3-day service standard volumes. The Commission followed up with the 

Postal Service to better understand MMP and the implications that merging loose mail with 

MMP mail might have for flats processing and costs.

In its response, the Postal Service confirms that loose mail is typically processed with MMP 

mail, and that “with the focus on shape-based processing, MMP flats can include some 

Periodicals and Marketing Mail as well as First-Class.” Response to CHIR No. 7, questions 

3.b., g. Merging low-preparation quality flats with MMP flats potentially results in 

inadequately prepared mail, particularly outgoing mail, receiving more expedited and more 

expensive service.

The Postal Service describes the MMP as a distribution system, which includes First-Class 

Mail, destinating in specific ZIP Codes. Id. question 3. The Postal Service also refers to the 

routing of MMP flats as being “defined in the National Distribution Labeling List [(NDLL)] 

logistic orders” but does not explain what this means, and how this routing differs from the 

routing approved for other-than MMP flats. Id.

The Commission notes that the NDLL logistics orders likely include information on 

approved transportation modes between specified origin and destination processing 

facilities in the country. During visits to STCs, Commission staff learned that First-Class 

Mail Flats approved for surface transportation mode are routed through STCs. STCs 

consolidate First-Class Mail from several origin facilities to transport it on fuller trucks, 

traveling long distances. The unclear reference to logistics orders and NDLL-defined 

routing might suggest that MMP mail that is not routed through STCs is approved for air 

transportation.

The impact of treating loose mail as MMP mail is an area that requires further research to 

understand the implications for flats processing efficiency and cost.

Processing network (re-)design. The limited number of operations that facilities performed 

made their operations interdependent. Any deviations from projected daily volumes or 

arrival of scheduled drop shipments at one facility had cascading impacts on operations for 

other facilities, which scheduled their operating windows based on expected mail arrival 

from interconnected facilities.

The Postal Service describes a shift toward a shaped-based processing network. Id.

questions 1.b., 4.a., 4.b. The exact implications of the many initiatives, pursued and 

implemented concurrently in the complex postal network, are difficult to definitively 

predict.

Flats processing operations span both letter/flat and package processing networks. This is 

because bundles are sorted on package processing equipment. Commission staff saw sites 

relying on frequent transportation between operations where bundles were processed on 

package processing equipment and operations where individual flats were processed.
Docket No. SS2022-1 - 80 -

However, Commission staff saw shifts in processing operations that were not related to 

mail shapes. Commission staff visited sites for which operations were closely tied to 

operations in several other sites within a geographic area. Each facility performed very 

specific operations. This collaboration and division of processing jobs between sites made 

projecting daily volumes and operations planning very difficult. It also required frequent 

postal transportation between facilities likely being underutilized. Some facilities referred 

to shuttle transportation running between their interconnect operations. The complex 

operations between sites likely resulted in frequent processing delays, at least for some of 

the mail.

Revenue deficiency assessments. The Postal Service states that it does not charge mailers 

additional postage to recuperate costs associated with inefficient processing of 

inadequately prepared flats bundles or for manually processing automation flats. January 

13 Response to CHIR No. 5, question 4.b.; Response to CHIR No. 6, questions 6.a.-d., 7.a.-d., 

8.a.-d.

As discussed earlier, the Postal Service does not record relevant data that would be needed 

to estimate the costs imposed by the inefficient processing of inadequately prepared mail. 

Without understanding cost implications, the Postal Service cannot exercise the option of 

charging mailers supplemental fees, that would reflect the difference between the costs 

incurred and costs recovered from revenues received for mailers’ pieces.

Estimation of manually processed flats. The Postal Service and the Commission rely on the 

reported volumes and workhours in the various operations to analyze trends in 

productivities and to recommend initiatives for improvements that might seem necessary.

As described in Section III.B.4.c., most facilities do not track employees’ time as employees 

move between activities and only focus on clocking in and out of base operations at the 

beginning and end of employees’ shifts. This might imply that no reported productivity 

values are reliable and should not be used as a basis for any new initiatives to improve 

processing productivities of the various operations.

However, the Postal Service also indicates that for machine processing, employees are 

frequently moving between the assigned base operation and another closely associated 

operation.125 For example, an employee’s base operation assigned for the shift is to prepare 

mail for processing on an automated flats sorting equipment (e.g., AFSM AI/ATHS). Such an 

employee will likely move between preparing mail for induction and operating the 

equipment once flats are inducted to the machine for sorting.

125 See, e.g., Response to CHIR No. 2, question 2.c.; Responses of the United States Postal Service to Questions 1-7 of Chairman’s Information 

Request No. 3, December 21, 2022, question 7 (Response to CHIR No. 3); Docket No. RM2020-13, Petition of the United States Postal Service for 

the Initiation of a Proceeding to Consider Proposed Changes in Analytical Principles (Proposal Six), September 15, 2020, Proposal Six at 4 

(Docket No. RM2020-13, Petition); Docket No. RM2020-13, Petition, PDF file “LCRA_MP Variability Report.pdf,” at 6-9.
Docket No. SS2022-1 - 81 -

For manual sorting operations, however, mail volumes are not recorded by data collection 

systems, as they are for machine processing. The Postal Service explains that for all 

facilities that operate automated flats sorting equipment, “the same fraction of 7 percent” is 

applied to the total volumes that each facility processes on automated equipment to 

estimate the amount of flats that are manually processed. Response to CHIR No. 7, question 

2.b. The Postal Service’s response indicates that there are additional nuances involved and 

that facility specific percentages are used as well.

This method was implemented in FY 2016 and replaced physical surveys of manually 

processed flats.126 The Postal Service explains that the new method led to a reduction in the 

estimated manual flats volumes for “a majority of facilities.” Response to CHIR No. 7, 

question 2.g. However, DDUs described increasing volumes requiring manual sorting, 

related to mailpiece irregularities.

With no data on bundles and individual mailpieces that cause inefficient operations, and no 

clear method to estimate manually processed flats volumes, the Postal Service is unable or 

unwilling to develop new tools designed to improve the efficiency of flats processing.

Staff support and training. Many facilities described low employee retention rates and staff 

shortages resulting in high proportions of newly hired, low-skilled employees for some 

facilities.

To explain the low retention rate, management described that the fewer training 

opportunities that were available to staff, the harder their jobs were to complete 

successfully, and the more likely staff were to quit. Management described the workload as 

too high, and inefficient processing of flats that required manual work contributed to that 

workload. Management also added that the numerous network changes implemented in 

recent years were too difficult to follow and adjust to successfully. Management further 

emphasized the importance of understanding the workload associated with poor mail 

quality when interpreting employee productivity.

The operational expert commented that the shutdown of FSS will require increased staffing 

at DDUs and the training of DDUs staff in scheme knowledge. Additionally, the expert noted 

the delivery routes will have to be restructured and carriers’ office time will increase, 

resulting in a decrease in available street time.

6. Impact of Facility Management Decisions on 

Efficiency: Case Studies

Bundle breakage. Certain management decisions impacted bundle volumes that received 

inefficient manual processing where automated processing without breakage might have 

been possible.

126 Docket No. ACR2022, Library Reference USPS-FY22-23, December 29, 2022, PDF file “USPS-FY22-23.Preface.pdf,” at 1.
Docket No. SS2022-1 - 82 -

Specifically, management at several facilities stated that staff sometimes but not always restrapped and/or re-wrapped loose bundles. Re-strapping or re-wrapping loose bundles 

would increase the number of bundles processed on automated equipment and reduce 

bundle volumes bypassing it and needing inefficient manual handling.

Staff at facilities that operated the APPS and the ADUS had an option to feed bundles into 

the machine manually, through side feeders. Feeding loose bundles manually meant placing 

bundles onto a conveyor belt, instead of having them fall 2 or 3 feet from the dumper onto 

the conveyor belt. Staff at a facility that operated the SPSS described manual feeding of 

bundles into the machine as the only way to control the high bundle breakage for the 

SPSS.127 However, the facility did not consistently use that option.

Discussions with staff at sites that operated more than one type of bundle processing 

equipment suggested that the decisions about which equipment type facilities should use 

for packages and flats bundles, including bundles of different pre-sort levels, were made by 

the Postal Service Headquarters and not facility management. However, facilities’ staff and 

management provided no additional details on the basis for these decisions.

Recording of bundle and mailpiece irregularities. Management described recording of 

bundle and mailpiece irregularities inconsistently, or only when irregular mail disrupted 

planned processing operations. Management at some sites described no recording at all. At 

a few facilities, management described recording irregularities consistently, but the 

Commission staff did not observe any employee doing so during the site visits.

As noted in Section III.B.5., the MIA includes an insignificant number of records on 

mailpiece and bundle irregularities, suggesting that the inconsistent irregularity recording 

applies to the entire postal network.128 The observations from site visits and the MIA data 

indicate that the Postal Service makes minimal efforts to understand the sources of flats 

processing inefficiencies or to track volumes that cause inefficient operations, which in 

turn prevents potential improvements in flats processing.

Deviations from schedules and impact on all operations. Commission staff saw differences in 

how management dealt with late arriving mail. Management at some sites reported they 

accepted and processed only timely drop shipments, i.e., those that arrived within 

applicable CETs. At other facilities, management included buffers to their CETs and 

accepted mail that arrived between half an hour and three hours past CETs. At sites where 

late drop shipments or delayed mail from upstream postal facilities were accepted, 

management disrupted current operations to move late mail up the line for processing.

127 Of bundle sorting equipment that the Commission staff observed, SPSS was described as one with the longest vertical drop from the dumper 

to the conveyor belt—3 feet.

128 See Section III.B.6.; Response to CHIR No. 6, question 3.a., Excel file “MIA Irregularities.xlsx.”
Docket No. SS2022-1 - 83 -

At one visited site, parcels and flats bundles were processed on the same equipment. 

However, sort plans for parcels and bundles were not identical, and the facility staff could 

not combine them on machine runs. As a result, separate operating windows were 

scheduled to process packages and to process bundles. Any deviations in scheduled bundle 

or parcels processing meant the facility management had to make trade-offs between 

delaying bundles or packages. When faced with such trade-offs, management said it used 

other factors to decide on the best use of available resources and staff.

Decisions related to flats volume declines and machine capacity. In individual flats 

processing, management reported sometimes combining committed volume (Periodicals) 

with non-committed volume (USPS Marketing Mail) to increase mail volumes in incoming 

sort plans, and in turn increase productivity of automated equipment processing. Only one 

facility’s management stated that it never combined pieces from different mail classes in 

any of its operations, machine processing, or allied operations.

Facilities’ management indicated treating flats from broken, loose, or reject bundles (loose 

flats) as MMP flats. The MMP includes First-Class Mail Flats. Merging loose flats with FirstClass Mail Flats in outgoing flows likely meant upgrading inadequately prepared USPS 

Marketing Mail and Periodicals flats, which caused inefficient operations, to the First-Class 

Mail network, with expedited service and more expensive transportation options. 

However, this area is not clearly understood and requires further analysis.

A few facilities’ staff described making decisions about whether to sort destinating flats 

manually or on automated equipment on days when flats volumes were low. By manually 

sorting automation flats, the facility staff avoided lowering its AFSM equipment’s 

productivity. However, it is not clear how the facility staff determined volumes that would 

be more efficiently processed if processed manually, and whether sorting them manually 

was less costly than sorting them on automated equipment.

Management at some facilities explained they varied the start time for certain operations, 

specifically mentioning outgoing primary operations. With clear information regarding the 

volume on hand, the machine throughput capability of the AFSM and ultimately the cutoff 

time129 required to be on the scheduled outbound transportation, it was possible to delay 

the start of the operation. This structured delay in the start of the operation resulted in a 

single continuous flow of the operation and improved productivity compared to a 

start/stop operation begun at the original scheduled time.

Transportation scheduling. Management at many sites explained their commitment to 

service performance. They focused on having transportation from their facility reach 

destination facilities in accordance with their CET. In order to achieve this, their primary 

effort was to ensure outgoing processing operations were completed in accordance with 

129 Cutoff time is “[t]he latest time that mail can be accepted for processing to meet service standards for the specific mail class or product.” See

United States Postal Service Publication 32 - Glossary of Postal Terms, available at: 

https://about.usps.com/publications/pub32/pub32_terms.htm.
Docket No. SS2022-1 - 84 -

the cutoff time that resulted in the mail being transported on the dispatch of value.130 If 

they had significant delays in processing, they were willing to use unscheduled 

transportation, while keeping in mind the need to keep additional cost under control. The 

key was to maximize the volume shipped on the dispatch of value so that the destinating 

facility could begin its inbound processing operations in a timely manner and then only 

have to fill in with the volume arriving on the extra transportation.131

Assignment of staff at delivery units. DDUs were faced with decisions to assign available staff 

to the various operations when workload exceeded expectations. Management at the 

visited DDUs described significant increases in daily workload associated with flats 

received from upstream mail processing sites not sorted to the carrier route level and/or to 

DPS. For DDUs with an insufficient number of employees, the decision involved preparing 

some of the daily mail for timely delivery and delaying the delivery of other mail.

C. Inefficiencies in Flats Collection and 

Processing: Data Analysis

1. Bundle Breakage During Mail Preparation, 

Collection, and Bundle Processing

a. Introduction

Bundle processing is often the first step taken by the Postal Service when flats mailpieces 

are inducted into the Postal Service network. In FY 2021, each bundle of Periodicals flats 

contained 17.4 mailpieces, on average, and each bundle of USPS Marketing Mail flats 

contained 26.1 mailpieces on average.132 Bundles that contain mailpieces that have been 

presorted to the 3-digit level are sorted on bundle processing equipment. Bundles 

containing pieces of 5-digit sortation or finer do not require sortation on bundle processing 

machines. Bundles most frequently break while being processed on bundle processing 

equipment. If a bundle breaks, a mail processing facility has to process all the individual 

mailpieces separately as opposed to processing a single bundle. Consequently, bundle 

breakage increases inefficiencies and mail processing costs. According to interviews with 

facility management, most bundle breakage occurs as a result of improper handling while 

being processed on bundle processing equipment. Breakage occurs due to two fundamental 

reasons: (1) poor quality bundling by the mailer; and (2) the ”drops” that occur at the 

induction into the bundle sorting system and at the output to the sort bins. See Section III.B.

130 Dispatch of value is “[t]he last dispatch of the day that is loaded on transportation in time to meet the service standard for the mail class or 

destination.” See id.

131 Sites ordered extra transportation for mail that should have been transported on scheduled transportation.

132 Docket No. ACR2021, Responses of the United States Postal Service to Questions 1-3 of Chairman’s Information Request No. 10, February 9, 

2022, question 1 (Docket No. ACR2021, Response to CHIR No. 10); Docket No. ACR2021, Response to CHIR No. 10, Excel file 

“ChIR.10.Q1.Resp.Attach.xlsx.”
Docket No. SS2022-1 - 85 -

b. Data Quality Issues

The Postal Service provides bundle breakage data to the Commission annually as part of 

the ACR.133 For the purposes of this report, the Commission aggregated the Postal Service 

data. This aggregated dataset contains the number of processed bundles and the number of 

broken bundles by every facility in every fiscal quarter. The Commission has identified 

numerous concerns with the quality of the data the Postal Service provided. These issues, 

discussed below, include, but are not limited to, missing data for a notable number of 

processed bundles and lack of the unique identifiers for the facilities in which the bundle 

breakage occurred. Data quality issues make it difficult for the Postal Service to identify 

and correct inefficiencies.

(1) Missing Bundles

Figure III-11 compares the number of processed Periodicals bundles as provided in the 

billing determinants dataset and in the Postal Service’s bundle breakage dataset for every 

year from FY 2018 through FY 2021.134 The billing determinants dataset lists the volume of 

bundles in every level of workshare by quarter. Mailers submitting USPS Marketing Mail or 

Periodicals can choose to presort or dropship their mail to earn a discount on postage. See 

FY 2021 ACD at 14-15, 17-25.

133 Docket No. ACR2022, Library Reference USPS-FY22-NP31, December 29, 2022, Excel file “FY18_FY22.Bundle.Brkge.E1_NonPublic.xlsx."

134 The billing determinants dataset is provided in Docket No. ACR2021, Library Reference USPS-FY21-4, December 29, 2021, Excel file “FY21 

Periodicals BDs.xlsx” and the bundle breakage dataset is provided in Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file 

“FY17_FY21.Bundle.Brkge.E1_NonPublic.xlsx.”
Docket No. SS2022-1 - 86 -

Figure III-11

Annual Quantity of Periodicals Bundles in Billing Determinants

and Bundle Breakage Datasets, FY 2018–FY 2022135

The blue line illustrates the annual sum of Periodicals bundles obtained from the billing 

determinants dataset, while the orange line illustrates the total number of Periodicals 

bundles from the bundle breakage dataset. As seen in the figure, there are more bundles 

recorded in the billing determinants than there are in the bundle breakage dataset for any 

given year, the bundle breakage dataset only contains 57 to 66 percent of the bundles 

recorded in the billing determinants dataset. Put differently, at least one-third of all 

bundles are missing from the bundle breakage dataset annually. In addition, it is important 

to note that the billing determinants exclude 5-digit bundles as these bundles bypass mail 

processing on bundle sortation equipment, so the discrepancy is likely larger.

When responding to the questions about the observed difference, the Postal Service states 

that the bundle breakage dataset only counted bundles with a full-service Intelligent Mail 

barcode (IMb). Response to CHIR No. 4, question 7.c. The IMb is a barcode sticker that 

mailers have the option of affixing to their mailings.136 When a mailer executes the option 

to affix an IMb sticker to their mailings, it expands their ability to track pieces. Id. There are 

three IMb options: non-automation, basic automation, and full-service. Id. IMbs are scanned 

135 Source: Docket No. ACR2022, Library Reference USPS-FY22-4, December 29, 2022, Excel file “FY22 EOY Periodicals BDs Final.xlsx;” Docket 

No. ACR2021, Library Reference USPS-FY21-4, Excel file “FY21 Periodicals BDs.xlsx;” Docket No. ACR2020, Library Reference USPS-FY20-4, 

December 29, 2020, Excel file “FY20 Periodicals BDs.xlsx;” Docket No. ACR2019, Library Reference USPS-FY19-4, December 27, 2019, Excel file 

“FY19 Periodicals BDs.xlsx;” Docket No. ACR2018, Library Reference USPS-FY18-4, December 28, 2018, Excel file “FY18 Periodicals 

BDsFinal.xlsx.” See Docket No. ACR2022, Library Reference USPS-FY22-NP31, Excel file “FY18_FY22.Bundle.Brkge.E1_NonPublic.xlsx.”

136 United States Postal Service, Mailing Services Intelligent Mail Barcode, available at https://postalpro.usps.com/mailing/intelligent-mailbarcode.

 -

 50

 100

 150

 200

 250

 300

FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Bundles (Millions)

Fiscal Year

Billing Determinants Bundle Breakage Dataset

2018 2019 2020 2021 2022
Docket No. SS2022-1 - 87 -

by mail processing equipment, and thereby added to the bundle breakage dataset, every 

time a bundle is processed. Any bundles which are missing an IMb or do not have a fullservice IMb are excluded from the bundle breakage dataset.

During the facility visits, several facility managers informed Commission staff that clerks 

sometimes break bundles on purpose. See Section III.B.4.a. This is because after visually 

inspecting a bundle, a clerk may assume that the bundle is likely to break when being 

processed on bundle processing equipment. Id. As a result, the clerk may choose to break 

the bundle by hand instead of attempting to use bundle processing equipment. Any bundles 

broken this way are also excluded from the bundle breakage dataset. Response to CHIR No. 

4, question 7.

As a result of issues in the data collection process, the Postal Service lacks a significant 

portion of bundle breakage data. If these data were collected, they could be actionable. 

Unfortunately, many recurrent patterns of bundle breakage likely persist because 

inadequate data collection means problems are not identified.

(2) Bundle Breakage Facility is not Properly Distinguished

Another important piece of information missing from the bundle breakage dataset is 

identification of the network location where each bundle broke. Mailers have the option of 

dropshipping their bundles at the destination NDC, destination P&DC, or the delivery unit. 

Depending on where mailers dropship their bundles, each bundle may be processed in one 

or more downstream facilities before it is intentionally broken and its individual pieces are 

processed into finer levels of sortation. Id. question 3. The Commission is concerned that 

for bundles that accidentally break, the bundle breakage dataset does not report on where 

the bundle actually broke. Instead, this dataset only provides information on the first-scan 

facility. For example, if a mailer dropships bundles at the destination NDC, these bundles 

might be sorted at an NDC and sorted again at a P&DC. Id. Whether these bundles broke 

accidentally at the NDC or the downstream P&DC, the bundle breakage dataset would only 

identify the NDC as the first-scan facility. Any bundle that breaks in subsequent machine 

processing is not distinguished in the bundle breakage dataset. Id. question 2.

c. The Postal Service is not Meeting Its Goals to Reduce

Bundle Breakage Rates

Reducing bundle breakage rates has long been a goal of Postal Service management. In 

response to a FY 2019 ACD directive, the Postal Service stated “[it had] focused its efforts 

on lowering the incidence of bundle breakage at the individual level.”137 The Postal Service 

has also acknowledged its goals of improving data collection and communication with 

mailers. As part of its annual submission of flats data in the FY 2021 ACD, the Postal Service 

stated “[o]ngoing attention has yielded an increase[d] internal awareness of bundle 

breakage occurrences and recordation in order to trigger efforts to abate/reduce bundle 

breakage. Such efforts include reviewing both internal operational processes and customer 

137 See Docket No. ACR2019, Response of the United States Postal Service to Commission Requests for Status Reports in the FY 2019 Annual 

Compliance Determination, July 15, 2020, at 4.
Docket No. SS2022-1 - 88 -

communication practices.”138 Though the data on bundle breakage provided have 

limitations, they continue to show goals are not being met.

(1) Bundle Breakage Rates Overall

Figure III-12 displays bundle breakage rates for Periodicals, USPS Marketing Mail, and both 

mail classes combined.

Figure III-12

Annual Bundle Breakage Rates for Periodicals and USPS Marketing Mail, FY 2016–FY 2022

138 See Docket No. ACR2021, Library Reference USPS-FY21-45, folder “Rule 3050.50 Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder 

“e.9 Trend Narrative.PRC.LR.9 Update,” PDF file “FY21 PRC Rule 3050.50(e.9) Narrative.pdf,” at 1 (Docket No. ACR2021, FY 2021 Section e.9 

Narrative).

0%

1%

2%

3%

4%

5%

6%

7%

8%

FY2016 FY2017 FY2018 FY2019 FY2020 FY2021 FY2022

Fiscal Year

All Bundles Overall Periodicals Marketing Mail

2016 2017 2018 2019 2020 2021 2022

USPS Marketing Mail
Docket No. SS2022-1 - 89 -

Figure III-12 demonstrates that the rates of bundle breakage on the machines have 

increased in every fiscal year since FY 2017. Bundle breakage rates for both Periodical 

bundles and USPS Marketing Mail bundles have steadily increased. When questioned about 

this increase in the FY 2021 ACD, the Postal Service stated that the COVID-19 pandemic had 

slowed efforts to improve communications with mailers regarding mail irregularities that 

result in bundle breakage.139 However, the Postal Service has had several years since the 

start of the pandemic to implement its goals, and rates of bundle breakage continue to 

increase. The Commission's operational expert's opinion was that this explanation was not 

likely the case. He claims, these trends could result from any of the following changes:

• changes in the Postal Service processing network that have shifted bundles to 

sortation systems with either higher induction or output heights

• changes in the Postal Service network that cause more handlings on the bundles 

sorting systems

• continual improvement in reporting system that shows increase due to better 

reporting, not an actual increase in the problem

Figure III-13

Annual Bundle Breakage Rates for Bundle Processing Machines, FY 2016–FY 2022140

139 Docket No. ACR2021, FY 2021 Section e.9 Narrative at 1-2; see FY 2021 ACD at 245.

140 See Docket No. ACR2022, Library Reference USPS-FY22-NP31, Excel file “FY18_FY22.Bundle.Brkge.E1_NonPublic.xlsx;” Docket No. ACR2020, 

Library Reference USPS-FY20-NP31, December 29, 2020, Excel file “FY16_FY20.Bundle.Brkge.E1_NonPublic.xlsx.”

0%

1%

2%

3%

4%

5%

6%

7%

8%

FY2016 FY2017 FY2018 FY2019 FY2020 FY2021 FY2022

Fiscal Year

SPBSTS APPS

2016 2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 90 -

The problem of increasing rates of bundle breakage is not isolated to a particular variety of 

bundle processing equipment. Figure III-13 demonstrates that bundle breakage rates 

across machines have been increasing since FY 2016.141 The similarity between the bundle 

breakage rates for different machines suggests that certain bundle preparation methods 

increase the likelihood that bundles will break on the machines.

(2) Communication with Mailers

The Postal Service previously stated that one of its goals was to increase communication 

with mailers.142 Such communication is conducive to reducing bundle breakage rates. This 

is because when mailers are notified that their preparation standards lead to broken 

bundles, mailers can work to change the way they prepare bundles prior to inducting them 

into the mail network system. For FY 2022 alone, the Postal Service reported 21 million 

broken bundles.143 This value does not include bundles that broke before they could be 

sorted on automated equipment or bundles that bypassed equipment because they were 

expected to break.

In FY 2020, the Postal Service implemented the MIA to provide mailers with specific 

information on mail preparation issues.144 As evidenced by increasing rates of bundle 

breakage, the MIA is limited in its ability to produce any measurable effect in improving 

mail preparation.

The Commission followed up with the Postal Service regarding recorded irregularities in 

the MIA, which the Postal Service implemented in FY 2020.145 The irregularity description 

in the MIA includes more than 80 rows overall, and the irregularities are recorded 

separately for “five irregularity types” (i.e., bundles, pallets, sacks, trays, and pieces).

146 For 

bundles, the MIA worksheet provided by the Postal Service includes 25,161 irregularity

records. Id. Excel file “MIA Irregularities.xlsx.”

141 Figure III-13 was created using the bundle breakage data submitted by the Postal Service. This dataset only includes bundles that broke 

during machine processing.

142 Docket No. ACR2021, FY 2021 Section e.9 Narrative at 1, 2; see FY 2021 ACD at 242, 245.

143 Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 Flats,” 

“Paragraph (e) -- Pinch Point Reports,” folder “e.1 Bundle Breakage Visibility,” Excel file “FY18_FY22Bundle.Brkge. E1_Public.xlsx,” tab “E1 -

Nation by FY,” cell E62.

144 Docket No. ACR2021, FY 2021 Section e.9 Narrative at 1; see FY 2021 ACD at 244.

145 The Postal Service described that the MIA was implemented to “effectively identify mail irregularities,” communicate them to the mailers, 

and eventually reduce costs associated with handling poorly prepared mail or with mailpieces with quality issues. See Docket No. ACR2021, FY 

2021 Service Performance Report at 18-19.

146 Response to CHIR No. 6, question 3 a.; Excel file “MIA Irregularities.xlsx.” Not all irregularities from the description list are applicable to 

bundles or other irregularity types. Id.
Docket No. SS2022-1 - 91 -

2. Analysis of Productivity and Other Issues in 

Automated Flats Operations

a. Introduction

Mail processing costs account for a large share of all Postal Service costs. A single flats 

mailpiece may be processed at several mail processing facilities between its origination 

point and its destination. At each mail processing facility, flats mail is processed on mail 

processing machines that sort it to even finer levels until it is sorted finely enough for 

delivery. The unit mail processing costs of the majority of flats products have increased 

every year since FY 2019. See FY 2021 ACD at 264; see also Section IV.D., supra. One 

important factor that affects mail processing cost is labor productivity, which is calculated 

by dividing workhours spent to process mail by the volume of mailpieces processed. As 

labor productivity declines, unit attributable cost increases because fewer pieces are being 

processed per workhour. The inability to match workhours to volume in order to maintain 

high levels of productivity leads to inefficient operations. Labor productivity has declined 

in recent years.147

b. AFSM Productivity

In past ACDs, the Commission used the MPV dataset provided by the Postal Service to 

analyze the relationship between volume and productivity for automated flats processing 

machines (including the AFSM equipment).148 However, that dataset excludes a large share 

of workhours associated with mail processing on automated machines. For the reasons 

discussed below, in the instant report, the Commission calculates labor productivity using 

those previously excluded workhours.

AFSM equipment is not homogenous. There are two modifications available for the AFSM: 

the AI modification assists clerks in feeding mailpieces into the AFSM, and the ATHS 

modification assists clerks in handling trays once mailpieces have been processed.149

AFSMs might not have any modifications at all or have any combination of the described 

modifications. Therefore, there are four types of AFSMs: AFSM, AFSM AI, AFSM ATHS, and 

AFSM AI ATHS. The four types differ in terms of their volume and labor productivity.

147 Shawn Sprague, What can labor productivity tell us about the U.S. economy? Beyond the Numbers: Productivity, vol. 3, no. 12 (U.S. Bureau of 

Labor Statistics, May 2014), available at https://www.bls.gov/opub/btn/volume-3/what-can-labor-productivity-tell-us-about-the-useconomy.htm.

148 See Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “NONPUBLIC MP Variance FY17_21.xlsb.”

149 United States Postal Service, Office of Inspector General, Report No. DA-AR-07-005, Automated Flat Sorting Machine 100 Enhancements, 

September 10, 2007, at 1-2, available at https://www.uspsoig.gov/reports/audit-reports/automated-flat-sorting-machine-100-enhancements

(OIG Report No. DA-AR-07-005).
Docket No. SS2022-1 - 92 -

Figure III-14

Annual Labor Productivity by AFSM Type in FY 2022150

Figure III-14 displays the average labor productivity by AFSM type in FY 2022. Figure III-14 

was created by summing the total volume and the total workhours for every AFSM type 

then dividing the total annual volume by the total annual productivity. Figure III-14 

demonstrates that the AFSM with no modifications has the lowest labor productivity. The 

AFSM-AI and AFSM-ATHS have roughly the same labor productivity, while the AFSM with

both modifications has a much higher productivity.

The Commission previously concluded that total pieces fed (TPF) is a reliable metric for 

measuring the volume of mail processed on a single mail processing machine. TPF, which is 

generated directly from the mail processing machine, accurately captures the volume 

processed on an individual machine.151 There is no ambiguity with regard to which 

machine processed which volume. However, the same cannot necessarily be said for the 

workhour data. The Commission previously concluded that while “the quality of data in 

MODS ha[d] generally improved, the workhours data [might] still be subject to 

measurement error. Order No. 6096 at 11. Within MODS (that provides data for the MPV), 

clerks assign labor hours to MODS codes that correspond to specific mail processing 

activities.152 The workhours from MODS codes attributable to each AFSM type (as listed in 

Response to CHIR No. 1) are undoubtably related to mail processing activities associated 

with using specific AFSMs. For example, MODs operation 462 describes workhours related 

150 Source: Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv.”

151 See Docket No. RM2020-13, Order on Analytical Principles Used in Periodic Reporting (Proposal Six), January 26, 2022, at 15, 18 (Order No. 

6096).

152 The Postal Service provided a full list of MODS codes attributable to each AFSM type. See Response to CHIR No. 1, question 5.c.; id. question 

5.d., Excel file “ChIR1_Q5d.xlsx.”

0

500

1000

1500

2000

2500

3000

AFSM 100 AFSM-AI AFSM-ATHS AFSM-AI/ATHS

Labor Productivity
Docket No. SS2022-1 - 93 -

to the outgoing secondary sortation on the AFSM AI. Similarly, MODS operation 401 

describes workhours related to outgoing secondary sortation on the AFSM ATHS. Id. Within 

the MPV, the Postal Service had calculated labor productivity by grouping workhours using

these MODS operations in the FY 2019, FY 2020, and FY 2021 ACDs. Id.

In previous ACDs, the Commission noted a seemingly spurious correlation between 

workhours and volume. In the analysis the Commission performed in this study, and by 

applying the Postal Service’s methodology153 to aggregate workhours from the last three 

ACDs, the Commission noted a few facilities that exhibited a negative correlation between 

volume and workhours on a single machine over time. In its Response to CHIR No. 3, the 

Postal Service explains that the negative correlation may be occurring because some 

relevant workhours were not included in the analysis and recommended that the 

Commission include flats preparation workhours.

154 The Commission added time spent on 

flats mail preparation for AFSMs with the AI modification to the workhours.155 In previous 

ACDs, the Commission excluded mail preparation workhours from the analysis of 

automatic flats mail processing for two reasons. First, the Commission identified certain 

mail preparation activities as a part of allied operations (see Section III.C., supra) and 

discussed it separately in relevant subsections of the ACD. Second, flats mail preparation 

workhours were omitted from the MPV dataset because they could not be directly 

attributed to one AFSM type. These workhours could be related to either an AFSM AI or an 

AFSM AI ATHS. This specification runs contrary to other MODS labor codes which are 

directly attributable to one type of AFSM.

In this study, the Commission analyzes labor productivity using workhour data 

encompassing additional activities related to processing volumes on automation 

equipment.156 The Commission used the MODS data that groups AFSM types into two AFSM 

groups to encompass all mail-processing related workhours: productivity for the AFSM AI 

and the AFSM AI ATHS (AFSM AI group), and for the AFSM and the AFSM ATHS (AFSM nonAI group).

c. Analysis of the Relationship Between the Processed Flats 

Mail Volume and Mail Preparation Workhours

Figure III-15 shows the share of mail preparation workhours in the total workhours by 

AFSM group in FY 2022.

153 The Postal Service’s methodology was to divide workhours by volume for only those MODS operations that were directly attributable to one 

type of AFSM, excluding mail preparation activities. See Response to CHIR No. 1, question 5.

154 Response to CHIR No. 3, question 7; Library Reference USPS-SS2022-1/NP3, December 21, 2022, PDF file 

“SS22.1.NP3.ChIR.3.Preface.Response.pdf.”

155 This is MODS operation 140. Id.

156 To accomplish this, the Commission includes MODS operation 140 for flats mail preparation on AFSMs with the AI modification, MODS 

operation 035 for flats mail preparation on AFSMs without the AI modification, and MODS operation 530 for flats mail preparation on the FSS 

machine.
Docket No. SS2022-1 - 94 -

Figure III-15

Total Workhours by AFSM Group in FY 2022157

Figure III-15 illustrates that for the AFSM-AI equipment, approximately two-thirds of 

workhours are related to flats mail preparation, while for the AFSM-nonAI equipment the 

share of workhours related to mail preparation is less than one-third. Figure III-15 

corroborates the assumption that mail preparation labor hours need to be included when 

analyzing the relationship between flats mail processing volume and labor productivity. 

Figure III-15 also demonstrates the stark difference in the composition of labor hours for 

two groups of AFSMs. The findings from Figure III-15 echo the findings from a Postal 

Service OIG report in 2007. OIG Report No. DA-AR-07-005 at 4. In this report, the Postal 

Service OIG noted that the Postal Service did not achieve its intended cost savings from 

AFSM modifications. Id.

157 Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv.”

67.2%

32.8%

AFSM-AI

Mail Prep All Other Workhours

31.3%

68.7%

AFSM-nonAI

Mail Prep All Other Workhours
Docket No. SS2022-1 - 95 -

Figure III-16

Relationship between AFSM-AI Volume and Workhours (with Mail Preparation Hours 

Excluded and Included) in FY 2022158

The scatter plot on the left illustrates the relationship between workhours and volume 

when mail preparation hours are excluded, whereas the scatterplot on the right illustrates 

the similar relationship when mail preparation hours are included. Figure III-16 

demonstrates there is a much stronger relationship between volume and workhours when 

mail preparation workhours are included. The correlation between volume and workhours 

is about 0.70 when mail preparation hours are excluded, and when mail preparation 

workhours are included, the correlation increases to 0.93. When repeating this analysis for 

FSS and AFSM-nonAI machine groups, the correlations also increase when mail preparation 

hours are included.

d. Errors in Workhour Data

Measures of volume processed are generated directly from the mail processing machine 

and incorporated into MODS via the Web End-of-Run system. Order No. 6096 at 18. 

However, as noted above, workhours can be less reliable. As clerks in mail processing 

facilities switch operations, they are required to record the switch by clocking out of the 

first operation and into the second one. For example, if a clerk spends 3 hours preparing 

mail for the AFSM AI, then spends 1 hour working with the FSS machine, they need to 

record workhours for each operation in MODS. Otherwise, 4 workhours will be attributed 

to the mail preparation operation on the AFSM-AI and 0 workhours will be attributed to 

the FSS during that day. The misallocation of workhours to incorrect operations lead to 

inaccuracies in labor productivity. While it can be difficult to ascertain whether any 

workhour data are erroneous, some observations in the MODS dataset seem more likely to 

contain errors.

158 Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv.”
Docket No. SS2022-1 - 96 -

Figure III-17

Mail Preparation and Other AFSM-Related Workhours at P&DC 8, FY 2016–FY 2021159

Figure III-17 visualizes the sum of mail preparation labor hours and other AFSM labor 

hours, and AFSM volumes since FY 2016 at facility 8. Facility 8 provides a good illustration 

of how non-mail-preparation workhours increased every year since FY 2017 while volume 

decreased over this time period. The total height of the bars in each figure mimics each 

other very closely, indicating a high correlation between total workhours and volume. 

Figure III-17 shows that the share of mail preparation hours as a portion of all AFSMrelated workhours has decreased over the last 5 years. In FY 2017, mail preparation labor 

hours were 60 percent of all AFSM-related labor hours, but in FY 2021 mail preparation 

labor hours were only 8 percent of all AFSM-related labor hours. Id. In summary, mail 

preparation workhours should be included in the mail processing workhours when 

analyzing labor productivity.

When questioned about the decreasing share of mail preparation workhours as a portion of 

all workhours, the Postal Service states that workhours previously clocked to the mail 

preparation operation were now being recorded to other AFSM-related operations.160

159 Response to CHIR No. 3, question 7; Library Reference USPS-SS2022-1/NP3, Excel file “CHIR3.Q7.AFSM.xlsx.”

160 Responses of the United States Postal Service to Questions 1-6 of Chairman’s Information Request No. 8, February 1, 2023, question 6 

(Response to CHIR No. 8); Library Reference USPS-SS2022–1 - NP6, February 1, 2023, PDF file “SS22.1.NP6.ChIR.8.Preface.Responses.pdf.”

60 

49 

69 

78 78 

87 

71 

74 

46 28 

17 7 

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 100

 120

 140

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 60

 80

 100

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 140

2016 2017 2018 2019 2020 2021

Volume (millions)

Workhours (thousands)

Fiscal Year

Other AFSM Workhours Mail Prep Workhours Volume
Docket No. SS2022-1 - 97 -

Errors in workhour data can take many forms. Sometimes employees are clocking too 

many workhours into the mail prep operation of a single machine. For facilities with both 

types of AFSMs, sometimes employees can clock hours for the wrong type of AFSM. These 

different types of errors in workhour data can make it difficult for the Postal Service to 

correct errors in workhour data once erroneous data have been recorded. The only way to 

avoid errors in workhour data with absolute certainty is to record workhours correctly.

e. Trends in Labor Productivity

Productivity for both AFSM groups, AFSM-AI and AFSM nonAI, has declined over the last 5 

years. Figure III-18 displays annual labor productivity for each AFSM group.

Figure III-18

Annual Labor Productivity, AFSM, FY 2017–FY 2022161

161 Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv;” Docket No. ACR2021, Library Reference USPSFY21-NP18, December 29, 2021, Excel file “mods2021tour-np.csv;” Docket No. ACR2020, Library Reference USPS-FY20-NP18, December 29, 

2020, Excel file “mods2020tour-np.csv;” Docket No. ACR2019, Library Reference USPS-FY19-NP18, December 27, 2019, Excel file 

“mods2019tour-np.csv;” Docket No. ACR2018, Library Reference USPS-FY18-NP18, December 28, 2018, Excel file “mods2018tour-np.csv;” 

Docket No. ACR2017, Library Reference USPS-FY17-NP18, December 29, 2017, Excel file “mods2017tour-np.csv.”
Docket No. SS2022-1 - 98 -

Figure III-19 was generated by summing all labor hours and all volumes from AFSM-related 

MODS codes at all facilities by year.162 It is difficult to conclude whether these facilities 

were not productive or workhours at these facilities were not recorded correctly. Figure 

III-19 demonstrates a steady decline in labor productivities for both groups of AFSM 

machines.

Figure III-19

Annual Workhours and Volume, Total AFSM, FY 2017–FY 2022163

Figure III-19 displays the total annual workhours and volume for all AFSMs. Workhours for 

the AFSM-AI and AFSM-nonAI machine groups were summed together, because each 

machine group exhibited a similar pattern. Figure III-19 demonstrates that the main 

problem with labor productivity is when workhours do not keep pace with declines in 

volume. For the last 3 fiscal years, workhours have increased even as the total processed 

volume has decreased.

162 Annual sums were used instead of taking the average labor productivity by year, because there were a few facilities with extremely high 

labor productivities.

163 Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv;” Docket No. ACR2021, Library Reference USPSFY21-NP18, Excel file “mods2021tour-np.csv;” Docket No. ACR2020, Library Reference USPS-FY20-NP18, Excel file “mods2020tour-np.csv;” 

Docket No. ACR2019, Library Reference USPS-FY19-NP18, Excel file “mods2019tour-np.csv;” Docket No. ACR2018, Library Reference USPSFY18-NP18, Excel file “mods2018tour-np.csv;” Docket No. ACR2017, Library Reference USPS-FY17-NP18, Excel file “mods2017tour-np.csv.”

8

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8

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15

2017 2018 2019 2020 2021 2022

Volume (billions)

Workhours (millions)

Fiscal Year

Workhours (millions) Volume (billions)
Docket No. SS2022-1 - 99 -

f. Transition from FSS to AFSM

On March 23, 2021, in its “Delivering for America” plan the Postal Service announced that 

“[d]ue to the dramatic decline of flat mail, [it would] replace flat sorting equipment as 

appropriate....”164 On April 20, 2021, the Postal Service announced that it would begin 

dismantling FSS equipment in several facilities across the country.165 And in a revision to 

the DMM effective November 7, 2022, the Postal Service stated it planned, “to remove Flat 

Sequencing System (FSS) scheme preparation standards.”166 To explore the progress the 

Postal Service has made on decommissioning the FSS machine and the impact this could 

have on flats processing the Commission analyzed the change in the number of AFSMs and 

FSSs and the labor productivity of these operations.

164 United States Postal Service, Delivering for America: Our Vision and Ten-Year Plan to Achieve Financial Sustainability and Service Excellence, 

March 23, 2021, at 28, available at https://about.usps.com/what/strategic-plans/delivering-for-america/assets/USPS_Delivering-ForAmerica.pdf.

165 Letter from Debby Szeredy, Executive Vice President, American Postal Workers Union, AFL-CIO, to Lamont Brooks, Director, Clerk Division, 

American Postal Workers Union, AFL-CIO (Apr. 21, 2021) transmitting Letter from Shannon R. Richardson, A/Manager, Contract Administration 

(APWU), United States Postal Service, to Mark Dimondstein, President, American Postal Workers Union, AFL-CIO (Apr. 20, 2021), available at 

https://www.21cpw.com/wp-content/uploads/2021/05/2021-4-21-Notification-No.-GCCC20210149-USPS-Will-Discontinue-and-Dismantle-FSSMachines-In-Several-Facilities-Across-the-Country.pdf.

166 See United States Postal Service, Postal Bulletin No. 22607, Policies, Procedures, and Forms Updates, DMM Revision: FSS Scheme 

Preparation Discontinued, September 22, 2022, available at https://about.usps.com/postal-bulletin/2022/pb22607/html/updt.htm.
Docket No. SS2022-1 - 100 -

Figure III-20

Annual Workhours and Volume, FSS167

Figure III-20 displays the total annual workhours and volume for all FSS machines. Figure 

III-20 illustrates a similar pattern on the FSS machine as was observed on the AFSM. Even 

though total workhours have not been increasing, they have been decreasing at a slower 

rate than volume from FY 2019 through FY 2022. In FY 2022, volume dropped by 13 

percent while workhours dropped by 4 percent. The result of these trends is a decline in 

FSS labor productivity.

The Postal Service has also been reducing its fleet of AFSMs; however, this rate of reduction 

has been slower than the rate of volume decrease.

167 Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv;” Docket No. ACR2021, Library Reference USPSFY21-NP18, Excel file “mods2021tour-np.csv;” Docket No. ACR2020, Library Reference USPS-FY20-NP18, Excel file “mods2020tour-np.csv;” 

Docket No. ACR2019, Library Reference USPS-FY19-NP18, Excel file “mods2019tour-np.csv;” Docket No. ACR2018, Library Reference USPSFY18-NP18, Excel file “mods2018tour-np.csv;” Docket No. ACR2017, Library Reference USPS-FY17-NP18, Excel file “mods2017tour-np.csv.”

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5

6

2017 2018 2019 2020 2021 2022

Volume (billions)

Workhours (millions)

Fiscal Year

Workhours (millions) Volume (billions)
Docket No. SS2022-1 - 101 -

Figure III-21

AFSM Count and Total Volume Processed, FY 2017–FY 2022168

Figure III-21 displays the annual count of all AFSMs and the annual sum of volume 

processed on AFSMs. All AFSM types are summed because data on the count of machines 

for every AFSM type was not available. Figure III-21 shows that, while volume processed 

has declined by 8.6 percent, the count of AFSMs has not changed significantly in FY 2020 

through FY 2022.169 The stable count in AFSMs could be a result of the Postal Service’s 

decision to instead decommission a significant number of FSS machines during that period 

or it could precipitate from the Postal Service’s need to leave AFSMs in regions with 

declining mail volumes to maintain the Universal Service Obligation.

168 Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv;” Docket No. ACR2021, Library Reference USPSFY21-NP18, Excel file “mods2021tour-np.csv;” Docket No. ACR2020, Library Reference USPS-FY20-NP18, Excel file “mods2020tour-np.csv;” 

Docket No. ACR2019, Library Reference USPS-FY19-NP18, Excel file “mods2019tour-np.csv;” Docket No. ACR2018, Library Reference USPSFY18-NP18, Excel file “mods2018tour-np.csv;” Docket No. ACR2017, Library Reference USPS-FY17-NP18, Excel file “mods2017tour-np.csv;” 

Response to CHIR No. 8, question 3, Excel file “ChiR 8 Q3 2016_2022.xlsx.”

169 Commission calculations based on total volume processed in all AFSM operations. See Docket No. ACR2022, Library Reference USPS-FY22-

NP18, Excel file “mods2022tour-np.csv;” Docket No. ACR2020, Library Reference USPS-FY20-NP18, Excel file “mods2020tour-np.csv.”

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2017 2018 2019 2020 2021 2022

Total Volume Processed (billions)

Count of AFSMs

Fiscal Year

AFSM count Volume (billions)
Docket No. SS2022-1 - 102 -

Figure III-22

Annual Counts of AFSM and FSS Machines, FY 2017–FY 2023170

Figure III-22 shows annual counts of AFSM and FSS machines from FY 2017 to FY 2022. FY 

2017 through FY 2019 saw a constant number of FSS machines while AFSM machines 

slowly declined. Conversely, FY 2020 through FY 2022 saw a relatively stable count of 

AFSM machines and a dramatic decrease in FSS machines, which is not surprising 

considering the Postal Service’s plan to eliminate the FSS in 2023. This all suggests the 

substitution of FSS with AFSM equipment is underway.

g. Trends in Machine Productivity

Another way to measure productivity is to observe machine runtime and TPF. This 

measurement of productivity (machine productivity) is independent of labor; it measures 

only the number of mailpieces processed by a machine over a fixed time period.

170 Response to CHIR No. 8, question 3, Excel file “ChiR 8 Q3 2016_2022.xlsx.”

0

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360

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FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022 FY 2023

FSS Count

AFSM Count

Fiscal Year

AFSM count AFSM Forecast FSS count FSS Forecast

2017 2018 2019 2020 2021 2022 2023
Docket No. SS2022-1 - 103 -

Figure III-23

Trend in AFSM Machine Productivity, FY 2017–FY 2022171

Figure III-23 displays machine productivity as measured by volume of flats mailpieces 

processed per workhour. The productivity and volume data in Figure III-23 are generated 

using volumes and productivity measurements from the incoming secondary operation on 

the AFSMs. This operation accounts for the largest share of all volume processed on the 

AFSMs. This measure of productivity has also seen declines in recent years; however, it 

follows volume very closely.

h. Conclusion

Labor productivity of automated flats operations should be measured by including mail 

preparation workhours (even though they are part of allied operations); including these 

workhours provides a more complete picture of all flats mail processing activities. Labor 

productivity of automated flats operations has been declining every year, with steeper 

declines occurring in FY 2019 through FY 2022. Reducing the count of AFSMs may improve 

productivity; however, in FY 2020 through FY 2022, AFSM count was relatively stable 

while the count of FSS machines fell precipitously. The full effect of FSS decommissioning 

on AFSM productivity remains unknown, although facilities with no FSS exhibit higher 

median AFSM productivity than their counterparts. Machine productivity, as measured in 

volume per hour, has also been declining at a rate consistent with volume declines.

171 Docket No. ACR2022, Library Reference USPS-FY22-23, Excel file “YRscrub2022.xlsx;” Docket No. ACR2021, Library Reference USPS-FY21-23, 

folder “USPS-FY21-23,” Excel file “YRscrub2021.xlsx;” Docket No. ACR2020, Library Reference USPS-FY20-23, December 29, 2020, Excel file 

“YRscrub2020.xlsx;” Docket No. ACR2019, Library Reference USPS-FY19-23, December 27, 2019, Excel file “YRscrub2019.xlsx;” Docket No. 

ACR2018, Library Reference USPS-FY18-23, December 28, 2018, folder “USPS-FY18-23.Files,” Excel file “YRscrub2018.xlsx;” Docket No. 

ACR2017, Library Reference USPS-FY17-23, December 29, 2017, folder “USPS-FY17-23,” Excel file “YRscrub2017.xlsx.”

0.0

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5.0

6.0

7.0

 -

 500

 1,000

 1,500

 2,000

 2,500

2017 2018 2019 2020 2021 2022

Volume (billions of pieces)

Productivity (pieces per hour)

Year

ASFM Productivity Volume (billions)
Docket No. SS2022-1 - 104 -

3. Analysis of Allied Operations

Allied operations, which occur throughout the mail processing and delivery workflow, 

represented 27.7 percent and 27.5 percent of flats costs in FY 2021 and FY 2022, 

respectively.172 The Postal Service employs Work in Process (WIP) cycles, or cycle time, to 

gain insight into allied operations. WIP is the amount of time mail spends in mail 

processing operations.173 The Postal Service measures processing operations using WIP 

cycles. Because mail processing operations generally run on planned schedules, service 

failures may occur due to any additional time spent in one operation before the next 

operation. Id. at 3-4.

Cycle time performance has been improving since the third quarter of FY 2021 after 

declining for several years due to COVID-19 related employee non-availability and the 

gridlock ensuing from the surge in package volume. Id. at 4. The Postal Service credits 

increased network capacity and the hiring of additional employees for the improvement. Id. 

Figure III-24 shows the WIP cycle time for the various flats mail processing operations. 

There were marked improvements in WIP cycles for all the processing operations in FY 

2022.

172 Docket No. ACR2021, Library Reference USPS-FY21-45, folder “USPS-FY21-45.zip,” folder “FY21.45.Files.zip,” folder “Rule 3050.50 Flats,” 

folder “Paragraph (b) -- Financial Report,” Excel file “FY21.Rule.3050.50.Para.B.xlsx, ” tab “Item b11;” Docket No. ACR2022, Library Reference 

USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 Flats,” folder “Paragraph (b) -- Financial Report,” Excel 

file “FY22.Rule.3050.50.Para.B.xlsx,” tab “Item b11.”

173 Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files,” folder “Rule 3050.50 Flats,” folder 

“Paragraph (e) -- Pinch Point Reports,” folder “e.9 Trend Narrative.PRC.LR.9 Update,” PDF file “FY22.Paragraph.e9.Narrative.pdf,” at 3 (FY 2022 

Section e.9 Narrative).
Docket No. SS2022-1 - 105 -

Figure III-24

Cycle Time, FY 2021–FY 2022174

The Commission notes the Postal Service’s continuous efforts to enhance the WIP cycle 

time of allied operations using its visualization timeline tool called GRID for spotting delays 

in scheduled mail processing processes, and the use of the Cycle Time report in Informed 

Visibility dashboards for providing real time data visualization of processes to support 

decision making. See Figure III-24.

4. Low Productivity in Manual Sorting Operations

a. Introduction

Manually sorting is an inefficient operation. In some cases, flats are nonmachinable and 

must be sorted manually. These flats pay rates that reflect the additional costs incurred 

from manual sorting. However, there are also a number of flats that pay automation rates 

but end up being sorted manually. These flats represent a significant inefficiency in Postal 

Service operations. The reported productivity of manually sorting flats was 282 pieces per 

hour in FY 2022.

175 As the operational expert told the Commission, this is an exceptionally 

low productivity, which, most likely, reflects inaccurate data for workhours or volumes. For 

comparison, the average productivity of an AFSM is 2,000 pieces per hour.176 The Postal 

Service would save on mail processing costs by manually sorting as few mailpieces as 

174 Docket No. ACR2022, Library Reference USPS-FY22-NP31, folder “USPS-FY22-NP31.zip,” folder “FY22.NP31.Files,” folder “Rule 3050.50 

Flats,” folder “Paragraph (e) – Pinch Point Nonpublic Reports,” folder “e.4 Work in Process,” Excel file 

“E4_NonPublic_New_WIP_FY19.FY22.xlsx.”

175 As discussed in the following section, the measure may not be the most accurate, but is the best reported data available on manual 

productivity. Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv.”

176 Based on Incoming Secondary Sortation on AFSM in FY 2022. See Docket No. ACR2022, Library Reference USPS-FY22-23, Excel file 

“YRscrub2022.xlsx.”

0

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50

60

70

Bundle to Piece SV Unload First

Automation

SV Unload to

Bundle

SV Unload to

Tray

Tray to Next

Automation

Hours

FY 2021 FY 2022
Docket No. SS2022-1 - 106 -

possible. However, as discussed below, poor data quality presents significant barriers to 

ameliorating manual sortation.

Figure III-25 shows the change in unit mail processing cost of a manually handled piece of 

flat-shaped mail and letter-shaped mail.

Figure III-25

Change in Unit Mail Processing Cost for Manually Processed Letters and Flats,

FY 2017–FY 2022177

In FY 2022, the Postal Service overturned all the progress it made lowering the manual 

mail processing costs in FY 2021. See Figure III-25. While manual mail processing costs of 

both letters and flats fell in FY 2021, in FY 2022, costs for both shapes increased even 

higher than in FY 2020. The growth of letters unit cost was 11.0 percent, while the growth 

of flats cost was 12.6 percent (or 1.6 percentage points higher).

b. Data Quality Issues

As discussed in Section III.C.2., labor productivity is calculated by dividing workhours by 

volume. Upon reviewing materials available from other studies and CHIR responses, the 

Commission has found both the numerator and the denominator of this ratio to be 

unreliable. Therefore, the resulting calculated productivity of manual sortation of flats is 

likewise unreliable.

177 Source: Docket No. ACR2020, Library Reference USPS-FY20-45, December 29, 2020, Excel file “eFlash.FY16_FY20.xlsx;” Library Reference 

USPS-FY22-45, Excel file “eFlash.FY17_FY22.xlsx.”

-10%

-5%

0%

5%

10%

15%

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

Letters Unit Cost Growth Flats Unit Cost Growth

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 107 -

Several studies conducted by the Postal Service OIG have indicated errors in workhour 

data. In 2020, the Postal Service OIG conducted studies on two mail processing facilities 

with very different reported manual mail processing productivities.178 In FY 2019, the 

national average of manual flats productivity was 332 pieces per hour. The Birmingham, AL 

P&DC reported its manual flats productivity as 100 pieces per hour, while the Tucson, AZ 

P&DC reported its manual flats productivity as 992 pieces per hour. Id. After conducting 

visits to each facility, the Postal Service OIG concluded that neither facility was recording 

workhours correctly, and that the difference in reported productivity occurred as a result 

of erroneous workhour data as opposed to any observable difference in the way flats 

mailpieces were handled. Id. While conducting a facility visit to the Birmingham, AL P&DC, 

the Postal Service OIG auditors noted that employees that were clocked into the manual

flats processing operation were working in other operations. OIG Report No. 20-161-R20 at 

2-3. In the Birmingham, AL P&DC, labor hours were overreported, causing manual 

operations to seem less productive. Id. While conducting a facility visit to the Tucson, AZ 

P&DC, the Postal Service OIG auditors identified 149 occurrences where postal employees 

processed manual flats volumes without recording any workhours. OIG Report No. 20-163-

R20 at 2. In this case, the underreporting of workhours had the consequence of making the 

facility appear to be more productive than it was in reality. Id. at 2-3. In both cases, 

variation in manual productivity occurred as a result of misrepresentation of workhours.

Another study conducted by the Postal Service OIG took an in-depth look at manual 

productivity across nine different mail processing facilities. OIG Report No. 21-131-R21 at 

9. In this study, the Postal Service OIG found that postal employees did not log their 

workhours to the correct operation at eight of the nine facilities visited. Id. The most salient 

example of erroneous workhour data was observed during the site visit to the Los Angeles 

P&DC. At this facility, the Postal Service OIG staff found that 12 employees were clocked 

into the manual sorting operation but did not observe any employees working in the 

performing manual sorting. Id. The Postal Service OIG went on to state that “management 

did not monitor on a daily basis the timekeeping practices of employees to ensure they 

were using the correct operation codes to account for the work performed.” Id. Findings 

from the Postal Service OIG studies are consistent with the findings from the Commission’s 

facility visits, wherein facility supervisors confirmed manual workhours were not 

scrutinized.

Volume measurement for automation operations is generated directly from the mail 

processing machine, but manual volume measurements are not substantiated by any 

volume counts. As stated in Section III.B.4.c., the Postal Service replaced its manual volume 

surveys with “allowances” in FY 2016. Response to CHIR No. 7, question 2. The Commission 

finds that the Postal Service's process of estimating manual volume as a percentage of 

178 Compare United States Postal Service, Office of Inspector General, Report No. 20-161-R20, Manual Flats Processing Operations at the 

Birmingham, AL, Processing and Distribution Center, February 12, 2020, at 3, available at https://www.uspsoig.gov/reports/auditreports/manual-flats-processing-operations-birmingham-al-processing-and-distribution (OIG Report No. 20-161-R20), with United States Postal 

Service, Office of Inspector General, Report No. 20-163-R20, Manual Flats Processing Operations at the Tucson, AZ, Processing and Distribution 

Center, March 9, 2020, at 2-3, available at https://www.uspsoig.gov/reports/audit-reports/manual-flats-processing-operations-tucson-azprocessing-and-distribution (OIG Report No. 20-163-R20).
Docket No. SS2022-1 - 108 -

automation volume is more prone to error than using a direct measurement technique, 

such as surveying.

Given the unreliable measurements of both workhours and volumes in manual flats sorting, 

the Commission is reluctant to perform rigorous data analysis of labor productivity of 

manual operations using MODS data. The lack of reliable volume or workhour data 

represents a tremendous loss of opportunity to track or use this data in any meaningful 

way. If reliable data were available, the Postal Service could use this data to make more 

informed decisions about mail processing costs.

Figure III-26 displays manual volumes and manual productivities for flats by fiscal year.

Figure III-26

Flats Manual Volumes and Manual Productivity, FY 2017–FY 2022179

Figure III-26 shows that manual productivity, as calculated by the Commission using MODS 

data, has been declining since FY 2019. While, as discussed above, this data may be 

unreliable, the trend in reported productivity is concerning if accurate. In FY 2022 and FY 

2021, manual productivities fell at a faster rate than manual volumes. It is possible that the 

data are so unreliable that there is no basis to draw a conclusion.

179 Source: Docket No. ACR2022, Library Reference USPS-FY22-NP18, Excel file “mods2022tour-np.csv;” Docket No. ACR2021, Library Reference 

USPS-FY21-NP18, Excel file “mods2021tour-np.csv;” Docket No. ACR2020, Library Reference USPS-FY20-NP18, Excel file “mods2020tournp.csv;” Docket No. ACR2019, Library Reference USPS-FY19-NP18, Excel file “mods2019tour-np.csv;” Docket No. ACR2018, Library Reference 

USPS-FY18-NP18, Excel file “mods2018tour-np.csv;”; Docket No. ACR2017, Library Reference USPS-FY17-NP18, Excel file “mods2017tournp.csv.”

250

260

270

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290

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310

320

330

340

0

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0.6

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1

1.2

2017 2018 2019 2020 2021 2022

Manual Productivity

Volume (billions)

Fiscal Year

Volume (billions) Manual Productivity
Docket No. SS2022-1 - 109 -

D. Inefficiencies in Transporting and Delivery 

of Flats Mail: Data Analysis

1. Transportation

The Postal Service provides SV data related to transportation and reports from its SVWeb 

application that analyzes the SV data.180 The Postal Service uses the reports from the 

SVWeb to both track the usage of transportation resources and identify opportunities for 

mitigating costs. Id. at 62. One of the important measures included in the SV is a scan 

compliance rate, which is the level at which employees use SV to scan barcodes on trailers, 

handling units, and containers as mail moves through the mailstream.181 The SV scan 

compliance in FY 2022 was 94.7 percent, increasing from approximately 92.8 percent in FY 

2021. FY 2022 Section e.9 Narrative at 7. As seen in Table III-1 that shows the on-time 

departure, on-time arrival, and average load for the period from FY 2018 to FY 2022, the 

percentages of both the on-time departure and arrival declined in FY 2022 when compared 

to FY 2021, however, the average load continues its upward trend, reaching the highest 

level in the reporting period.

The Postal Service reports that it ended the strict trips-on-time narrow initiative in FY 

2022, which led to the observed reduction in on-time departures and arrivals, and replaced 

the initiative with a broader focus on overall service performance. FY 2022 Section e.9 

Narrative at 7. The Postal Service attributes the increased load percentages to multiple 

successful initiatives. Id.

180 See Docket No. ACR2015, Postal Service Third Response at 58-62. SV is “a mobile-scanning application that allows postal personnel to track 

mail as it is transported across the surface network. Postal personnel use handheld mobile devices to scan barcodes on trailers, handling units, 

and containers used to transport mail between facilities, as they move across the surface network.” Id. at 58. The SVWEB application provides 

near real-time data, and enables “managers to pull reports presenting Area, District, and facility data, such as the number of trips that have 

arrived and departed over a given period of time, the percentage of the load on each trip (utilization), and the on-time performance for each 

trip.” Id. at 61-62.

181 FY 2022 Section e.9 Narrative at 7. The scan compliance expressed as a percentage is calculated by dividing the actual scan by the expected 

scan. Whereas the Postal Service is “committed to improving manual scan compliance at each facility to as close to 100 percent as possible, the 

visibility that can be gained from any data system is limited to the extent it relies on human intervention.” See Docket No. ACR2015, Postal 

Service Third Response at 22, 63-64, 73.
Docket No. SS2022-1 - 110 -

Table III-1

On-Time Departure, On-Time Arrival, and Average Load, FY 2018–FY 2022182

Metric Goal FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

On-time Departure 100% 70.50% 72.60% 87.20% 84.60% 82.33%

On-time Arrival 100% 62.00% 63.40% 74.70% 73.14% 71.88%

Average Load 60% 32.10% 32.10% 38.60% 39.75% 42.89%

The Commission has examined the available data related to on-time performance of surface 

trips, truck capacity utilization, and the number of misrouted containers, all of which are 

indicators of the efficiency of transportation operations.

Trips’ on-time performance. The Postal Service has reported the following percentages for 

on-time performance of arriving and departing trips, for FY 2013 through FY 2022.

Figure III-27

National On-time Arrival and Departure Percentages, FY 2013–FY 2022183

182 Source: Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files,” folder “Rule 3050.50 Flats,” 

folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx,” tab “First Set.”

183 Source: Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 

Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx;” Docket No. 

ACR2019, Library Reference USPS-FY19-45, December 27, 2019, folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” 

Excel file “Public SV Data_FY15_FY19.xlsx;” Docket No. RM2018-1, Response of the United States Postal Service to Commission Information 

Request No. 1, December 4, 2017, questions PP5-2.d.i.-ii. (Docket No. RM2018-1, Response to CIR No. 1).

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

National On-time arrival percentage National On-time departure percentage

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 111 -

As seen in Figure III-27, the on-time departures generally follow the trend of on-time 

arrivals, although a higher percentage of departing trips are reported as being on-time. 

This might suggest that PVS and/or contracted transportation does not include sufficient 

drive times for scheduled routes, since fewer trips (by about 10 percentage points) arrive 

on time at destination than are dispatched on time from origin. However, assuming that 

inbound trips carry mail on their return portions (i.e., assuming that every inbound trip is 

recorded as an outbound trip upon return), the data depicted in Figure III-27 could also 

indicate that the Postal Service builds in some buffer to accommodate delays in round-trip 

transportation.

At the mail processing sites and STCs, when discussing on-time arrivals and on-time 

departures of the scheduled transportation with management, Commission staff learned 

that in general, for round trips, delayed inbound trips (i.e., delayed arrivals) lead to delayed 

departures of trucks on the outbound portions of trips. However, management also 

commented that for some of the delays in truck arrivals, they can “catch-up” on the delays 

during processing operations and dispatch trucks on time for the return portions of their 

trips. Staff clarified that the longer the trips, the more likely that the inbound trips would 

be delayed. Additionally, delays that accumulate over long-haul inbound trips are less likely 

to be accommodated by receiving facilities, and thus, more likely to lead to delayed 

outbound trips. Lastly, many staff described delayed mail processing operations at 

previous sites as the leading cause of delayed arrivals, and they described delayed 

processing or HCR driver delays as most frequently leading to delayed departures.

The Commission asked the Postal Service additional questions regarding the causes of 

delayed arriving and departing trips that were related to the Postal Service operations, 

HCR contractors, or other causes.184 The Postal Service provided the numbers of late 

arriving and departing trips, including reasons for delays.

As illustrated in Figure III-28, the data provided showed a similar pattern as the on-time 

arrival and departure percentages shown in Figure III-27.

184 Chairman’s Information Request No. 5, January 6, 2023, question 6.b. (CHIR No. 5).
Docket No. SS2022-1 - 112 -

Figure III-28

Number of Late Inbound (Arriving) and Outbound (Departing) Trips, FY 2017–FY 2022185

Figure III-29 illustrates that while in FY 2017, more than half of delayed inbound trips were 

due to delays in postal operations (namely, mail processing and dock operations), by FY 

2022, only about one-fifth of delayed inbound trips were caused by postal delays, and over 

70 percent were attributed to HCR contractors’ fault. In FY 2022, the Postal Service’s data 

attribute 50 percent of inbound trips’ delays to “[c]ontractor [f]ailure,” but, the Postal

Service does not explain what constitutes “[c]ontractor [f]ailure.”186

The Postal Service explains that fault was “determined at point of instance or occurrence” 

and by personnel, or it was based on discussions between the personnel and the drivers, 

including “knowledge of local events such as weather, road construction and civil events or 

unrest.” January 18 Response to CHIR No. 5, question 6.c.iv.

185 Source: January 18 Response to CHIR No. 5, question 6.b., Excel file “ChIR No. 5_Q6b_Response.xlsx.”

186 January 18 Response to CHIR No. 5, question 6.b., Excel file “ChIR No. 5_Q6b_Response.xlsx,” tab “Root Causes,” cell B18.

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

Number of late inbound trips Number of late departing trips

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 113 -

Figure III-29

Proportions of Delayed Inbound Trips by Reason for Delay, FY 2017–FY 2022187

187 Source: January 18 Response to CHIR No. 5, question 6.b., Excel file “ChIR No. 5_Q6b_Response.xlsx.”

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

CONTRACTOR DELAY: Other CONTRACTOR DELAY: Unrecorded

CONTRACTOR DELAY: Traffic/Weather/Mechanical issue CONTRACTOR DELAY: Contractor Failure

POSTAL DELAY: Other POSTAL DELAY: Delayed arrival at previous site

POSTAL DELAY: Mail processing operations POSTAL DELAY: Dock operations

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 114 -

The data included in Figure III-30 similarly illustrate proportions of delayed outbound trips 

attributed to postal- and contractor-driven causes.

Figure III-30

Proportions of Delayed Outbound Trips by Reason for Delay, FY 2017–FY 2022188

The data shown in Figure III-30 suggest that the Postal Service’s operations were the cause 

of over 60 percent of delayed outbound trips in FY 2017, with an “improvement” by FY 

2022, when postal operations caused delays in about 35 percent of outbound trips. The 

data also suggest that 6 percent of delayed outbound trips in FY 2022 were due to postalcaused delays for inbound trips, which would leave 29 percent of delayed return trips 

caused by operations performed at postal facilities dispatching them.

The Commission inquired about the assessment of penalties for HCR contractors, since 

significant proportions of delayed trips were attributed to contractors’ fault, and since the 

Postal Service is extending its surface transportation network to reach coast-to-coast, as it 

attempts to divert mail volumes from the air to the surface transportation network. 

Response to CHIR No. 7, question 4.a.

The Postal Service’s response indicates that HCR contractors “can submit” a late slip to the 

Postal Service for payment if it was the Postal Service’s operations that caused delays on 

the inbound legs of round trips. January 18 Response to CHIR No. 5, question 6.c.i. The 

Postal Service also states that it is “responsible for paying the HCR contractor” for the 

188 Source: January 18 Response to CHIR No. 5, question 6.b., Excel file “ChIR No. 5_Q6b_Response.xlsx.”

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2017 2018 2019 2020 2021 2022 Fiscal Year

CONTRACTOR DELAY: Other CONTRACTOR DELAY: Unrecorded

CONTRACTOR DELAY: Traffic/Weather/Mechanical issue CONTRACTOR DELAY: Contractor Failure

POSTAL DELAY: Other POSTAL DELAY: Delayed inbound trip

POSTAL DELAY: Mail processing operations POSTAL DELAY: Dock operations
Docket No. SS2022-1 - 115 -

associated delays on the outbound legs of round trips. Id. question 6.d. The Postal Service 

does not clarify to what extent HCR contracts request payments for postal-caused delays.

For delays caused by HCR contractors, the Postal Service states that further action “can be 

taken” to “eliminate HCR contractors with ongoing failures to operate as contracted” but it 

does not provide whether it assesses penalties nor does it provide specifics on the extent of 

failures that would be sufficient to terminate HCR contracts or have HCR contractors 

operate as previously contracted. Id. questions 6.c., d. The lack of clarity with respect to 

HCR contracts terms and whether or which party enforces them, makes assessing the cost 

implications of transportation delays impossible.

Extra transportation. During facility visits and in response to CHIRs, Commission staff 

learned about instances when facilities order extra transportation. These include situations 

such as when HCR drivers do not show up and extra transportation is needed to transport 

mail ready for dispatch to destination facility. Or they include situations when a facility is 

informed about a delay for an inbound truck, which is severe enough that it cannot be 

recovered by speeding up the unloading of mail from the truck upon arrival and the 

dispatch of mail loaded onto the truck for the outbound portion of the trip, so as to ensure 

the truck’s arrival at destination by applicable CET. Facility staff explained that in such 

cases, the scheduled outbound trips are considered cancelled or omitted, and are replaced 

with extra trips. Extra trips are also ordered when truck space on a scheduled trip is filled, 

and more mail remains for the route. This can lead to dispatching low volumes of the 

remaining mail on expensive extra trips, which can significantly increase the transportation 

cost per transported mailpiece. Such situations were described as relatively frequent by a 

representative of an STC. The Postal Service states that if less than 15 percent of the truck 

floor is used, it “may decide against operating the extra trip due to cost” and transport the 

remaining mail on a later trip. January 18 Response to CHIR No. 5, question 6.e. The Postal 

Service also describes ordering extra transportation in cases when operations at the 

processing facility are over capacity and some mail needs to be processed at a different 

facility. Id.

Figure III-31 illustrates proportions of outbound scheduled trips that were performed and 

those that were cancelled between FY 2016 and FY 2022.
Docket No. SS2022-1 - 116 -

Figure III-31

Percentage of Outbound Scheduled Trips Performed and Cancelled 

Between FY 2016 and FY 2022189

The data depicted in the above figure suggest increases in the proportions of scheduled 

trips that were cancelled between FY 2016 and FY 2022.

In Figure III-32, the Commission examined all outbound trips that the Postal Service 

provided data for—those that were performed and those that were not (were cancelled). 

The performed trips shown in the figure below include additional separations for 

performed trips—trips that were scheduled and departed on time, trips that were 

scheduled and departed late, and trips that were not scheduled and ordered as needed 

(extra trips). This was done to examine whether the provided trip data show associations 

between changes in proportions of extra trips, cancelled trips, and late departing trips.

189 The Commission notes that the Postal Service’s data reporting is inconsistent and does not allow for comparisons of the number of trips 

across fiscal years. The underlying trip data depicted in Figure III-31 include outbound trips for 0:00 to 7 a.m. in FY 2019, outbound trips for 24-

hour days for FY 2020 through FY 2022, with no detail available on the time(s) of day to which trips reported for FY 2016 through FY 2018 

pertain. See Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 

Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx,” tab “Natl Trips on 

Time,” cells A28:A29. See also Docket No. ACR2019, Library Reference USPS-FY19-45, folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 

Surface Visibility,” Excel file “Public SV Data_FY15_FY19.xlsx,” tab “Natl Trips on Time.” As such, the Commission shows the percentages of trips 

with different attributes rather than numbers of trips for the provided data. Source: Docket No. ACR2022, Library Reference USPS-FY22-45, 

folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 

Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx;” Docket No. ACR2019, Library Reference USPS-FY19-45, folder “Paragraph (e) --

Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY15_FY19.xlsx.”

93% 94% 92% 94% 92% 90% 89%

7% 6% 8% 6% 8% 10% 11%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FY 2016 FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

% of Scheduled Trips Performed % Scheduled Trips Cancelled

2016 2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 117 -

Figure III-32

Proportions of Outbound Trips That Were Scheduled and Departed on Time, Scheduled and 

Departed Late, Scheduled but Cancelled, and Not Scheduled (Extra Trips), FY 2018–FY 2022190

Figure III-32 does not suggest that the increases in trips’ cancellations, or in proportions of 

late departing trips, were associated with increases in the proportions of extra trips.

However, the Commission notes that it is difficult to assess whether the Postal Service 

excluded relevant trips from the provided trips data because the Commission does not 

have access to the raw data from which trips shown in the above figures were extracted. 

For example, the Postal Service explains that the outbound trips, which are depicted in 

Figures III-31 and III-32, include both HCR and PVS trips, and that they include only trips 

“departing selected [National Performance Assessment] NPA sites.” Response to CHIR No. 

1, question 3.a. The Postal Service states that it is “Logistics Operations” that determines 

the sites to be included, and that some sites, such as “non-Postal sites, select annexes, and 

[delivery unit] hubs” are excluded. Id. question 3.d. The data that the Postal Service 

provides in the ACR dockets also suggest that the number of sites for which the Postal 

190 Source: Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files,” folder “Rule 3050.50 Flats,” 

folder “Paragraph (e) –-- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx.”

71% 75% 74% 71% 69%

17%

15% 14% 17% 17%

8% 6% 8% 10% 10%

3% 4% 4% 3% 3%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Performed trips that were unscheduled (extra trips)

Scheduled trips that were cancelled (were not performed)

Performed trips that were scheduled and departed late, or for which no leave time was recorded

Performed trips that were scheduled and departed on time
Docket No. SS2022-1 - 118 -

Service provides trips data changes every year.191 Moreover, the Postal Service did not 

include trips for certain routes, or trips it labeled as “Go-Anywhere trips,” or “Air to Surface 

Diversion” trips, in the outbound trips data shown in Figures III-31 and III-32. Id. However, 

during site visits, Commission staff learned that STCs relied frequently on extra 

transportation. Since STCs are contracted, and not postal operated sites, STCs might be 

among the excluded “non-Postal” sites.

The Commission followed up with the Postal Service to request data on mileages driven in 

the surface transportation network. CHIR No. 5, question 8. The Postal Service explains that 

mileages were not recorded prior to April 2021. January 18 Response to CHIR No. 5, 

question 8. The Commission combined FY 2022 data on the number of trips and surface 

network mileages, to determine whether there is any difference in average trip distance for 

extra trips and for regularly scheduled trips.

Figure III-33

Average Trip Distance (Miles) for Regular and Extra Trips in FY 2022, by HCR Contract 

Category192

The provided data for FY 2022, shown in Figure III-33, indicate that extra trips are between 

11 and 37 percent longer, on average, than regularly scheduled trips. As such, the potential 

cost impact of inefficient transportation operations stems not only from higher cost per 

mile for extra trips compared to cost per mile for scheduled trips, but also from extra trips 

being potentially routed differently and being longer than the scheduled trips they replace. 

See id. question 6.e.

191 See Docket No. ACR2022, Library Reference USPS-FY22-NP31, folder “USPS-FY22-NP31.zip,” folder “FY22.NP31.Files.zip,” folder “Rule 

3050.50 Flats,” folder “Paragraph (e) -- Pinch Point Nonpublic Reports,” folder “e.6 Surface Visibility,” Excel file “NonPublic NPA_Trips on Time 

Data_FY18_FY22.xlsx,” tabs “FY18 SV NPA Data,” “FY19 SV NPA Data,” “FY20 SV NPA Data,” “FY21 SV NPA Data,” and “FY22 SV NPA Data.”

192 Source: January 18 Response to CHIR No. 5, question 8.

0

200

400

600

800

1,000

regular extra

Inter NDC Intra NDC Inter P&DC Intra P&DC
Docket No. SS2022-1 - 119 -

Truck space utilization. The Postal Service provides data on “load percentage,” which is 

calculated as follows:193

sum of the base area of containers scanned as loaded onto departing trucks (ft2)

sum of the floor area of departing trucks (ft2)

The Postal Service’s data on load percentage for FY 2013 through FY 2022 are shown in 

Figure III-34.

Figure III-34

National Average Load Percentage, FY 2013–FY 2022194

The Commission notes that the Postal Service’s load percentages might represent 

overestimates, based on the example calculation that the Postal Service provided, which is 

replicated in Table III-2.

193 Response to CHIR No. 1, questions 2.b.i., c.

194 Source: Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 

Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx;” Docket No. 

ACR2019, Library Reference USPS-FY19-45, folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV 

Data_FY15_FY19.xlsx;” Docket No. RM2018-1, Response to CIR No. 1, question PP5-2.d.iv.

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

FY 2013 FY 2014 FY 2015 FY 2016 FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 120 -

Table III-2

Example of How Load Percentages are Calculated195

Container Type Container 

Base Area, ft2

Container 

Count

53 ft Trailer 

Floor Area, ft2

Load Percentage

Hamper 7.23 2 450.5 (7.23 ft * 2) / 450.5 ft = 3.2%

OTR196 22.53 3 450.5 (22.53 ft * 3) / 450.5 ft = 15.0%

FSS CASTR197 7.56 5 450.5 (7.56 ft * 5) / 450.5 ft = 8.4%

Gaylord 4FT 17.33 6 450.5 (17.33 ft * 6) / 450.5 ft = 23.1%

Pallet 17.33 9 450.5 (17.33 ft * 9) / 450.5 ft = 34.6%

Specifically, discussions with staff at visited sites suggested that Gaylord containers must 

be transported on pallets. In that case, of the nine pallets that are included in the calculated 

load percentage, six pallets are used to support the Gaylord containers, and including them 

represents double counting their combined square foot areas in the calculated load 

percentage. Another situation when such calculated load percentages might lead to 

overestimates of load percentages would be when mail containers are stacked, which the 

Postal Service staff described as attempting to do, to better utilize cubic space on trucks.

Figure III-35 includes data that the Postal Service provided on the percentage of truck 

space utilization by container type.

195 Source: Response to CHIR No. 1, question 2.d.

196 Over-the-Road container.

197 Flats Sequencing System Carrier Automated Street Tray Rack.
Docket No. SS2022-1 - 121 -

Figure III-35

Truck Space Utilization by Container Type, FY 2017–FY 2022198

The Commission notes that of the container types included in Figure III-35, only Gaylord 

containers (and pallets on which they are transported) are stackable and allow better use 

of trucks’ cubic spaces.199 However, the data suggest that most of the space on trucks is 

used for containers that cannot be stacked. Id. The operational expert clarified that Gaylord 

containers can be made of cardboard or plastic, and that while stacking of cardboard 

containers might be dependent on conditions described above, plastic Gaylord containers 

can always be stacked.

198 Source: Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 

Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx;” Docket No. 

ACR2019, Library Reference USPS-FY19-45, folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV 

Data_FY15_FY19.xlsx.”

199 See generally United States Postal Service, Mail Transport Equipment, Handbook PO-502, June 2017, available at 

https://apwu.org/sites/default/files/po502_0.pdf.

5.2% 5.3% 5.3% 5.3% 5.5% 5.5%

2.5% 2.5% 2.5% 2.5% 2.5% 2.5%

10.9% 11.1% 11.0% 9.8% 8.9% 8.9%

3.2% 3.3% 3.4%

3.3% 3.4% 3.4%

2.3% 2.4% 2.4%

2.4% 2.5% 2.5%

4.5% 4.6% 4.6%

4.6% 4.5% 4.4%

3.9% 3.9% 3.8%

3.8% 3.8% 3.9%

0%

5%

10%

15%

20%

25%

30%

35%

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

PALLET

GAYLORD 4FT

FSS CASTR

Eastern Regional Mail Container

Bulk Mail Container Over The Road Container: Heavy and Light Duty

Hamper

Rigid Wire Container With Wheels

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 122 -

Misrouted containers. The Postal Service provides data on the numbers of misrouted 

containers, which are containers unloaded from trucks at “unexcepted” sites.200 These data 

do not represent total annual misrouted container counts, but rather, container counts 

during “comparable” 4-week periods in each fiscal year from FY 2017 through FY 2022.201

The provided counts for the last 6 fiscal years are presented in Figure III-36.

Figure III-36

Number of Misrouted Containers During Comparable 4-Week Periods 

in FY 2017 Through FY 2022202

During site visits, the facilities’ staff explained that they generally directed misrouted 

containers to their intended facilities. This might lead to added trips and mileages in the 

network, for which the Postal Service incurs associated transportation costs, especially for 

containers with mail that is subject to tighter service standard windows, although 

according to the Commission’s operational expert, this may not occur frequently. In 

addition, misrouting mail containers has implications on service performance, as it delays 

mail arrival at intended processing facilities by CETs.

The Commission examined facility level data to see whether the numbers of misrouted 

containers that the facilities receive are more-or-less evenly distributed. The data depicted 

in Figure III-37 illustrate that most sites for which the Postal Service provided data 

200 See, e.g., Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 

Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx,” tab “First Set,” 

cell B17.

201 Id. tab “Request,” cells B34:B36. See also Docket No. ACR2019, Library Reference USPS-FY19-45, folder “Paragraph (e) -- Pinch Point 

Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY15_FY19.xlsx,” tab “Request,” cells B34:B35.

202 Source: Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 

Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder “e.6 Surface Visibility,” Excel file “Public SV Data_FY18_FY22.xlsx.”

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 123 -

received up to 1,000 misrouted containers during the 4-week periods, and that many fewer 

sites received more than 1,000 misrouted containers.

Figure III-37

Number of Facilities by the Number of Misrouted Containers,

Shown in 1,000 Container Increments, in FY 2017 Through FY 2022203

FY 2017 – 1,530 sites included FY 2018 – 1,688 sites included

FY 2019 – 2,000 sites included FY 2020 – 2,027 sites included

FY 2021 – 399 sites included FY 2022 – 389 sites included

203 Source: Docket No. ACR2022, Library Reference USPS-FY22-NP31, Excel file “NonPublic SV Data_FY18_FY22.xlsx;” Docket No. ACR2019, 

Library Reference USPS-FY19-NP31, December 27, 2019, Excel file “NonPublic SV Data_FY15_FY19.xlsx.”
Docket No. SS2022-1 - 124 -

The data depicted in the above figures suggest that the number of sites for which the Postal 

Service provided misrouted container data has decreased from over 1,500 in FY 2017, and 

more than 2,000 in FY 2020, to only 389 sites in FY 2022. Moreover, the data suggest that 

the number of misrouted containers did not decrease as the number of sites included in the 

reported data decreased. On the contrary, the 404,710 containers in FY 2017 pertained to 

1,530 sites while the 622,132 containers in FY 2022 were unloaded at just 389 sites. That 

suggests an increase from an average of 265 misrouted containers per site in FY 2017 to an 

average of 1,599 misrouted containers per site in FY 2022. The impact of routing these 

containers to their intended facilities on transportation costs is potentially large, 

considering possibly separate trip for each misrouted container that a facility unexpectedly 

receives and sends to its intended site.

The Commission notes that the analysis presented in this section is meant to explain the 

efficiency of the Postal Service’s overall transportation operations. This is because the 

Postal Service generally combines mail products with similar service standards, and with 

the same origin and destination points, on shared transportation.204 This is also because 

the trip and container data provided by the Postal Service and analyzed in this section do 

not include information on mail products transported on trips and in containers.

The Postal Service uses the Transportation Cost System (TRACS) to develop distribution 

keys, which are then used to allocate costs incurred on purchased and postal vehicle 

transportation to mail products.205 The distribution keys are estimated by sampling trucks 

and truck stops, as well as mail included on sampled trucks, for several categories of trips. 

Id. As such, inefficiencies in transportation operations, such as trips which operate solely to 

transport flats products sorted on an FSS equipment from an NDC directly to respective 

destination DDUs, would appear in a representative sample, their transported volumes 

would be reflected in estimated distribution keys, and in turn, in transportation costs 

distributed to flats products. Id.

204 See, e.g., Docket No. N2021-2, United States Postal Service Request for an Advisory Opinion on Changes in the Nature of Postal Services, 

June 17, 2021, at 7-8.

205 See generally Docket No. ACR2022, Library Reference USPS-FY22-36, December 29, 2022, PDF file “USPS_FY22_36_TRACS-Preface.pdf.”
Docket No. SS2022-1 - 125 -

2. Last Mile Delivery

The Last Mile occurs during the time a mailpiece is in transit from its final mail processing 

plant sortation or delivery unit bundle handling to its delivery by postal personnel.

The Postal Service uses last mile impact (LMI) quarterly scores to monitor the service 

impact of last-mile delivery. The Postal Service defines LMI as “an estimate of the 

percentage of mail which moved from on-time after the last processing scan to late after 

delivery.”206 The LMI report includes the overall on-time score, on-time score at last 

processing, and the LMI for all flat-shaped products at each service standard.207 As seen in 

Table III-3, compared to FY 2021, the LMI quarterly scores in FY 2022 showed varying 

levels of performance with regard to the products. The annual LMI scores for various flats 

categories (but those in the USPS Marketing Mail High-Density Saturation and Bound 

Printed Matter categories), generally improved from FY 2021 to FY 2022. The Postal 

Service’s national target for LMI is 1.0 percent.208

206 See Docket No. RM2018-1, Response to CIR No. 1, question PP6-4.d. The Postal Service states that some of the measurement systems under 

the Transit Time Measurement System (TTMS) provides the calculations of the LMI for flats. Id. question PP6-4.b.

207 The Commission had proposed the rules for the data reporting requirements as part of 39 C.F.R. § 3050.50. See Order No. 5004 at 11, 20.

208 See Docket No. ACR2019, Responses of the United States Postal Service to Questions 1-41 of Chairman’s Information Request No. 4, January 

24, 2020, question 15.k.
Docket No. SS2022-1 - 126 -

Table III-3

Last Mile Impact: Change Year Over Year, FY 2022–FY 2021209

Product Service Standard

Change Year Over Year (FY 22-FY 21)

Q1 Q2 Q3 Q4

Presort First-ClassTM Flats

Overnight 1.1 0.8 0.8 0.2

Two-Day 0.3 0.9 0.7 0.4

3-5 Day 1.0 1.1 1.9 1.8

Single Piece First-ClassTM Flats

Overnight N/A

Two-Day 0.1 0.3 0.1 0.2

3-5 Day -0.2 -0.2 0.3 0.3

USPS Marketing Mail Flats

Destination Entry 1.5 1.5 1.5 1.2

End-to-End 0.1 -0.4 0.0 0.2

USPS Marketing Mail Carrier Route

Destination Entry 1.4 1.8 1.5 1.1

End-to-End 0.3 0.4 0.3 1.6

USPS Marketing Mail EDDM-Retail Destination Entry N/A

USPS Marketing Mail HD and Sat 

Flats

Destination Entry -0.4 0.1 0.0 -0.4

End-to-End -0.2 -0.4 -0.8 0.3

Periodicals-Within County 0.1 0.4 0.8 0.7

Periodicals-Outside County

Destination Entry 0.2 0.4 1.1 0.6

End-to-End 0.0 -0.5 0.1 0.1

Bound Printed Matter Flats

Destination Entry 0.3 -0.5 -0.5 0.3

End-to-End -0.1 -0.9 0.3 0.3

209 Source: Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 

Flats,” folder “Paragraph (e) -- Pinch Point Reports,” folder “e.9 Trend Narrative.PRC.LR.9 Update,” Excel file “CH 6 Data and Tables 

2022.PRC.LR.9 Update.xlsx,” tab “LMI Indicators.” The colors in the cells of the table indicate LMI quarterly scores at varying levels of 

performance with regards to the products in FY 2022, in comparison to FY 2021. Considering that the Postal Service’s national target for LMI is 

1.0 percent, the green color shows a performance that is close to or higher than the national target (darker/brighter shades of green indicate a 

better performance). The yellow color shows a medium level performance, and the red/orange color shows a poor level performance (where 

red colors characterize the poorest performance).
Docket No. SS2022-1 - 127 -

As discussed in Section III.B.4.f., during mail processing site visits, the Commission learned 

that DDUs received regular shipments of flats, which were not sorted at the upstream mail 

processing facilities according to the price categories they qualified for, and required 

manual sorting to carrier route level and/or manual casing, by DDUs’ staff. The Commission 

followed up with the Postal Service to request mail class-specific data on destinating flats 

volumes received by DDUs for delivery, the amount of sorting they received at the 

upstream mail processing facilities, as well as the volumes and workhours recorded in 

manual flats distributions. CHIR No. 5, question 9.

The Postal Service explains that no mail class information for flats received by DDUs for

final delivery was available. January 13 Response to CHIR No. 5, questions 9.a.-b. The Postal 

Service also explains that no data for total destinating flats volumes were available, and 

only data for flats destinating on city carrier routes were available. Id.

For flats’ sort levels, the Postal Service could only provide flats volumes that DDUs received 

in DPS, following FSS processing at upstream mail processing sites and could not provide 

data for flats sorted to other levels. Id. question 9.d.

The data provided by the Postal Service indicate that of the 18,691 DDUs, as identified by 

unique finance numbers, no data on destinating flats volumes were available for 11,068 

units. See Figure III-38.

Figure III-38

Number of DDUs210

210 Source: January 13 Response to CHIR No. 5, question 9; Library Reference USPS-SS2022-1/NP4, January 13, 2023, Excel file 

“ChIR_5_Q9_a.b.d_DOIS.xlsx.”

11,068

7,623

Volume not available

Volume available for city carrier routes
Docket No. SS2022-1 - 128 -

Of the 7,623 DDUs for which volumes destinating on city carrier routes are available, the 

number of DDUs that handled FSS mail fluctuated between FY 2017 and FY 2021, declining 

more sharply in FY 2022, as illustrated in Figure III-39. This likely is related to a large 

extent to the decommissioning of FSS operations at mail processing facilities, which the 

Postal Service started in FY 2021.211 See Section III.B.4.b.

Figure III-39

Number of DDUs for Which the Postal Service Provided Data on

Flats Volumes Destinating on City Carrier Routes, FY 2017–FY 2022212

In Figure III-40, the Commission illustrates that most (about 75 percent) of the provided 

destinating flats volumes were received by DDUs that did not handle FSS mail in the 

respective fiscal years. The figure provides additional separation for volumes received by 

DDUs that handled FSS mail, by whether the received volumes were sorted to DPS at the 

upstream mail processing facility or not.

211 Docket No. ACR2021, Library Reference USPS-FY21-45, folder “USPS-FY21-45.zip,” folder “FY21.45.Files.zip,” folder “Rule 3050.50 Flats,” 

folder “Paragraph (f) -- Operational Changes Report,” PDF file “FY21 Paragraph (f) Report.pdf,” at 4-5; Docket No. ACR2022, Library Reference 

USPS-FY22-45, folder “USPS-FY22-45.zip,” folder “FY22.45.Files.zip,” folder “Rule 3050.50 Flats,” folder “Paragraph (f) -- Operational Changes 

Report,” PDF file “FY22 Paragraph (f) Flats Operational Initiatives Report.pdf,” at 4-5.

212 Source: January 13 Response to CHIR No. 5, questions 9.a.-b., d.; Library Reference USPS-SS2022-1/NP4, Excel file 

“ChIR_5_Q9_a.b.d_DOIS.xlsx.”

6,280

6,300

6,320

6,340

6,360

6,380

6,400

6,420

1,160

1,180

1,200

1,220

1,240

1,260

1,280

1,300

1,320

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Number of DDUs that did not handle FSS mail

Number of DDUs that handled FSS mail

Fiscal Year

Number of DDUs that handled FSS flats Number of DDUs that did not handle FSS flats

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 129 -

Figure III-40

Flats Volumes (Millions) Provided by the Postal Service as Destinating on City Carrier Routes, 

FY 2017–FY 2022213

Of the volumes included in Figure III-40, about 25 percent were received by DDUs that 

handled FSS flats. However, the DDUs that handled FSS flats represented only about 17 

percent of DDUs for which destinating flats volumes were provided by the Postal Service. 

This suggests that DDUs that handled FSS flats also handled higher overall flats volumes 

per year than the DDUs that did not handle FSS flats. This is depicted in Figure III-41.

213 Source: January 13 Response to CHIR No. 5, question 9; Library Reference USPS-SS2022-1/NP4, Excel file “ChIR_5_Q9_a.b.d_DOIS.xlsx.”

0

100,000

200,000

300,000

400,000

500,000

600,000

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

volume sorted to DPS and received by DDUs that handled FSS flats

volume not sorted to DPS and received by DDUs that handled FSS flats

volume received by DDUs that did not handle FSS flats

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 130 -

Figure III-41

Flats Volumes Received for Delivery on City Carrier Routes Per Fiscal Year Per DDU,

FY 2017–FY 2022214

In FY 2017, DDUs that handled FSS flats received about 64 percent more flats for final 

delivery on city carrier routes, on average. By FY 2022, the DDUs that handled FSS flats 

received about 85 percent more flats for delivery than DDUs that did not handle FSS flats.

This analysis confirms that the Postal Service deployed FSS equipment at mail processing 

facilities that served high delivery volume DDUs, with likely high delivery point densities. 

The analysis also suggests that flats volume declines have not been evenly distributed in 

the postal network. Specifically, data included in the above figure suggest that flats which 

destinated in higher-density areas, included in FSS zones, have not declined as sharply as 

have volumes that destinated in non-FSS zones. This not only confirms that the impact of 

FSS removal on the workload associated with the need to manually case all flats will be 

more severe for DDUs serving high-density urban areas, but also suggests that high 

delivery-point density DDUs might not experience as much relief in casing workload due to 

volume declines as will DDUs serving lower density areas. In fact, lower delivery point 

density DDUs that the Commission staff visited already described decrease in workloads 

related to casing of flats which was related to flats volume declines.

The Commission does not have data that would allow examining flats volumes that should 

have been processed on FSS and those that were processed on FSS, at the delivery unit 

level. As noted in Section III.B.5., the Postal Service does not track data on flats that bypass 

automated processing at mail processing sites due to mailpiece irregularities. As such, the 

214 Source: January 13 Response to CHIR No. 5, question 9; Library Reference USPS-SS2022-1/NP4, Excel file “ChIR_5_Q9_a.b.d_DOIS.xlsx.”

0

20,000,000

40,000,000

60,000,000

80,000,000

100,000,000

120,000,000

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

DDUs that handled FSS mail DDUs that did not handle FSS mail

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 131 -

Commission requested data on volumes and workhours recorded in manual flats 

operations at DDUs. CHIR No. 5, questions 9.e.-f. The data provided by the Postal Service in 

response to this request are depicted in Figures III-42 and III-43.

Figure III-42

Distribution of Flats Volumes Recorded in Manual Flats Distributions Between DDUs That 

Handled FSS Mail and Those That Did Not, FY 2017–FY 2022215

Figure III-42 suggests that about 30 percent of flats recorded in manual distributions 

pertained to DDUs that handled FSS mail, while these DDUs received 25 percent of flats 

volumes for which the Postal Service provided data (see Figure III-40).

Figure III-43 shows similar proportions of workhours recorded in manual flats 

distributions between DDUs that handled FSS flats and those that did not.

215 Source: January 13 Response to CHIR No. 5, question 9; Library Reference USPS-SS2022-1/NP4, Excel files “ChIR_5_Q9_a.b.d_DOIS.xlsx” and 

“ChIR 1_Q9 Manual Flt Vol_hrs FY 17_FY22.xlsx.”

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

DDUs that did not handle FSS flats DDUs that handled FSS flats

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 132 -

Figure III-43

Workhours Recorded in Manual Flats Distributions216

As noted above and depicted earlier in this section in Figure III-41, DDUs that handled FSS 

flats handled between 64 and 85 percent more destinating flats per delivery unit, on 

average, than DDUs that did not handle FSS mail.

Analysis of flats volumes handled in manual distributions on a per delivery unit basis 

reveals that DDUs that handled FSS flats processed between 81 and 105 percent more flats 

in manual distributions than DDUs that did not handle FSS flats. This is illustrated in Figure 

III-44.

216 Source: Library Reference SS2022-1-NP4, January 13, 2023, Excel files “ChIR_5_Q9_a.b.d_DOIS.xlsx” and “ChIR 1_Q9 Manual Flt Vol_hrs FY 

17_FY22.xlsx.”

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

DDUs that did not handle FSS flats DDUs that handled FSS flats

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 133 -

Figure III-44

Flats Recorded in Manual Distributions per DDU and Fiscal Year217

The data analyzed in this section confirm what the Commission staff observed during DDU 

site visits and what was discussed in Section III.B.4.f. Specifically, Commission staff 

observed that the DDUs that served FSS zones reported more severe increases in workload 

related to inadequately processed flats received from the upstream mail processing 

facilities than the DDU that did not serve any FSS zones.

The Commission and the operational expert both note the need to understand the 

implications that sub-optimal FSS operations have had in the past, as illustrated in the 

above data analysis, as well as the need to continue monitoring the implications of FSS 

removal on DDUs’ operations, costs, and service performance related to last mile impact.

217 Source: Library Reference SS2022-1-NP4, January 13, 2023, Excel files “ChIR_5_Q9_a.b.d_DOIS.xlsx” and “ChIR 1_Q9 Manual Flt Vol_hrs FY 

17_FY22.xlsx.”

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Fiscal Year

DDUs that handled FSS mail DDUs that did not handle FSS mail

2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 134 -

CHAPTER IV. IMPACTS OF DIFFERENT 

FACTORS ON FLATS COST

A. Impact of Volume Trends on Flats Cost

1. Analysis of Volume Trends and Unit Attributable 

Costs at the Product Level for NonCompensatory Flats Products218

Figure IV-1 compares the volume and unit attributable cost trends of a group of noncompensatory and compensatory flats products.219 Unit attributable costs are adjusted for 

inflation using FY 2021 as the base year,220 which are represented by the solid lines in the 

figure. The dotted lines represent nominal unit attributable costs. The decrease in the 

volume of the group of non-compensatory flats is due to decreases in all three flats 

products in the group: USPS Marketing Mail Flats, In-County Periodicals, and Outside 

County Periodicals. The volume of the group of compensatory flats is stable until the last 3 

years, which sees a decline in volume due to a decrease in volume of USPS High Density and 

Saturation Flats and Parcels. Unit attributable costs of the group of compensatory products 

remain relatively stable over the years, while non-compensatory flats products have 

experienced a large increase in real unit attributable costs between FY 2016 and FY 2021.

218 As in Chapter II, non-compensatory flats products considered in this Chapter are flats products for which their revenue did not cover their 

attributable cost in FY 2021.

219 This figure shows the volume and unit attributable cost for flats that have been non-compensatory or compensatory for the entire period 

shown in the graph. First-Class Mail Flats and Carrier Route Flats are excluded because First-Class Mail Flats was non-compensatory in FY 2021 

only and Carrier Route Flats became non-compensatory in FY 2019. EDDM-R is excluded because it was not added to a product list until FY 

2013.

220 This adjustment uses FY consumer price index for all urban consumers (CPI-U). See United States Bureau of Labor Statistics, available at 

www.bls.gov.
Docket No. SS2022-1 - 135 -

Figure IV-1

Volume and Unit Attributable Cost221 Trends of a Group of Non-Compensatory

and Compensatory Flats,222 FY 2008–FY 2022223

Figures IV-2 through IV-4 show that for each flats products that were non-compensatory in 

FY 2021, the volume decrease has been persistent and steady; volume was decreasing 

almost every year since FY 2008. In FY 2016, there was a migration of Carrier Route Flats 

to the USPS Marketing Mail Flats product due to the implementation of FSS-specific prices. 

FY 2016 ACD at 48 n.59. See Figure IV-3. In FY 2017, the Postal Service proposed, and the 

Commission approved, the elimination of these FSS prices. Id. Therefore, the volume and, 

consequently, unit attributable cost data for FY 2016 reflect a different mail mix than 

volume and unit attributable cost data for other years. Id.

221 Unit attributable costs have been adjusted for inflation using FY 2021 as the base year. The dotted line represents the un-adjusted, nominal 

unit attributable costs.

222 The group of non-compensatory flats includes USPS Marketing Mail Flats, In-County Periodicals, and Outside County Periodicals. The group 

of compensatory flats includes USPS High Density and Saturation Flats and Parcels and Bound Printed Matter Flats. See n.219 for explanation.

223 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report; FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 

Public CRA Report; FY 2008 Public CRA Report.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20,000

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Volume (millions)

Unit Cost (dollars)

Fiscal Year

Non-Compensatory Flats Volume Compensatory Flats Volume

Non-Compensatory Flats Unit Cost (Nominal) Compensatory Flats Unit Cost (Nominal)

Non-Compensatory Flats Unit Cost (Inflation-Adjusted) Compensatory Flats Unit Cost (Inflation-Adjusted)
Docket No. SS2022-1 - 136 -

Figure IV-2

Volume of First-Class Mail Flats, FY 2008–FY 2022224

224 Source: FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 Public CRA Report; FY 2018 Public CRA 

Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 Public CRA Report; FY 2013 Public CRA 

Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public CRA Report; FY 2008 Public CRA 

Report.

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Volume (millions)

Fiscal Year

First-Class Mail Flats
Docket No. SS2022-1 - 137 -

Figure IV-3

Volume of USPS Marketing Mail Flats and USPS Carrier Route Flats,

FY 2008–FY 2022225

225 Source: FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 Public CRA Report; FY 2018 Public CRA 

Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 Public CRA Report; FY 2013 Public CRA 

Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public CRA Report; FY 2008 Public CRA 

Report.

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Volume (millions)

Fiscal Year

Carrier Route Flats Marketing Mail Flats
Docket No. SS2022-1 - 138 -

Figure IV-4

Volume of Periodicals Products, FY 2008–FY 2022226

Figures IV-5 through IV-7 show the unit attributable costs (inflation-adjusted and nominal) 

of flats products that were non-compensatory in FY 2021. The unadjusted unit attributable 

costs are represented by the dotted lines. First-Class Mail Flats has a significantly higher 

unit attributable cost than any other non-compensatory flats products. In the FY 2021 ACR, 

the Postal Service stated that the increase in the unit attributable cost of First-Class Mail 

Flats between FY 2020 and FY 2021 was driven by increases in mail processing and surface 

transportation unit costs.

227 The unit attributable cost of First-Class Mail Flats has been 

increasing since FY 2014, and its real unit attributable cost has increased by 33 cents from 

FY 2014 to FY 2021. USPS Marketing Mail Flats and Outside County Periodicals have the 

next highest unit attributable costs. Until FY 2022, the unit attributable cost of USPS 

Marketing Mail Flats had been increasing since FY 2016, while Outside County Periodicals 

unit attributable cost remained relatively stable until it increased sharply in FY 2020 and 

226 Source: FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 Public CRA Report; FY 2018 Public CRA 

Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 Public CRA Report; FY 2013 Public CRA 

Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public CRA Report; FY 2008 Public CRA 

Report.

227 FY 2021 ACR at 9. First-Class Mail Flats’ mail processing unit costs increased on average by 6.4 percent annually between FY 2017 and FY 

2021. Id. The Postal Service explains that as flat-shaped products’ volumes decreased, the productivities for various mail processing operations 

also declined, resulting in higher mail processing costs. Id. In regard to higher transportation costs, the Postal Service attributes this to the 

higher variabilities approved in Docket No. RM2021-1 as well as the possibility that declining volumes resulted in fewer average pieces per 

container and thus higher transportation unit attributable costs. Id.

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Volume (millions)

Fiscal Year

In-County Periodicals Outside County Periodicals
Docket No. SS2022-1 - 139 -

FY 2021.228 Carrier Route Flats and In-County Periodicals have lower unit attributable 

costs but have also experienced large proportional increases in unit attributable costs.229

Figure IV-5

Unit Attributable Costs of First-Class Mail Flats: Inflation-Adjusted and Nominal,

FY 2008–FY 2022230

228 The Postal Service ascribes the increase in the unit attributable cost of USPS Marketing Mail Flats to higher unit mail processing costs due to 

decreases in USPS Marketing Mail Flats volume. It states that “[b]ecause setup and breakdown activities are largely invariant to processed 

volume, the continued volume declines necessarily lead to higher unit mail processing costs.” FY 2021 ACR at 20.

229 The Postal Service notes that the increase in unit attributable cost of Carrier Route Flats between FY 2019 and FY 2020 is driven by higher 

delivery unit costs. FY 2020 ACR at 13. This increase is due in part to a costing methodology change. Id. It states that in addition, the declining 

volume caused a loss of economies of density, as there were fewer pieces to distribute to a steadily increasing number of delivery points. Id. at 

14.

230 Source: FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 Public CRA Report; FY 2018 Public CRA 

Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 Public CRA Report; FY 2013 Public CRA 

Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public CRA Report; FY 2008 Public CRA 

Report.

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Attributable Cost (dollars)

Fiscal Year

First-Class Mail Flats (Inflation-Adjusted) First-Class Mail Flats (Nominal)
Docket No. SS2022-1 - 140 -

Figure IV-6

Unit Attributable Costs of USPS Marketing Mail Flats and Carrier Route Flats: InflationAdjusted and Nominal, FY 2008–FY 2022231

231 Source: FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 Public CRA Report; FY 2018 Public CRA 

Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 Public CRA Report; FY 2013 Public CRA 

Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public CRA Report; FY 2008 Public CRA 

Report.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Attributable Cost (dollars)

Fiscal Year

Carrier Route Flats (Inflation-Adjusted) USPS Marketing Mail Flats (Inflation-Adjusted)

Carrier Route Flats (Nominal) USPS Marketing Mail Flats (Nominal)
Docket No. SS2022-1 - 141 -

Figure IV-7

Unit Attributable Costs of Periodicals: Inflation-Adjusted and Nominal,

FY 2008–FY 2022232

232 Source: FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 Public CRA Report; FY 2018 Public CRA 

Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 Public CRA Report; FY 2013 Public CRA 

Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public CRA Report; FY 2008 Public CRA 

Report.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Attributable Cost (dollars)

Fiscal Year

In-County Periodicals (Inflation-Adjusted) Outside County Periodicals (Inflation-Adjusted)

In-County Periodicals (Nominal) Outside County Periodicals (Nominal)
Docket No. SS2022-1 - 142 -

2. Econometric Analysis of the Impact of the 

Decreasing Flats Volumes on Unit Cost

Another way to investigate efficiency is to view the Postal Service as a natural monopoly 

and measure the potential loss of scale economies implied by the volume decline, in 

particular for flat-shaped mail.233 Economies of scale are the cost advantages that may be 

reaped from producing more so that costs are spread over more pieces. In this section, the 

degree of scale economies (DSE) is measured at an organization-wide level and at product 

levels and then compared. This section also includes a prediction of the future flat-shaped 

mail marginal costs based on the extrapolation of current volume trends. Finally, this 

section discusses the challenges posed by the analysis, as well as potential solutions to 

those challenges.

a. Marginal Unit Cost Analyzed in this Section

In the context of a single-product firm, the measurement of the unit cost poses little to no 

conceptual problems. In a multiproduct firm such as the Postal Service, however, the 

definition of the unit cost is not straightforward.234 In this section, the Commission 

analyzes and econometrically predicts the marginal cost, “the cost of producing another 

unit of output,”235 of each of 4 flat-shaped mail products. In its annual Cost and Revenue 

Analysis (CRA) reports, the Postal Service provides data on unit volume variable cost (the 

ratio of volume variable cost to mail volume),236 which “is in fact equal to [the product’s] 

marginal cost.”237

The econometric analysis is performed after a firm-level investigation of the degree of scale 

economies (DSE). An investigation into scale economies involves both the marginal costs 

and the ratio of total operating (accrued) cost to total mail volume.

b. Data

Four flats mail products are considered in this analysis along with 10 other Market 

Dominant products or product categories, as well as one competitive mail category 

consisting of aggregated competitive products. There are 15 mail products or product 

categories in total.

233 Although the question regarding whether the Postal Service exhibits characteristics of a natural monopoly has been extensively debated, this 

debate has not reached clear and unequivocal conclusions.

234 See Docket No. RM2016-2, Order Concerning United Parcel Service, Inc.’s Proposed Changes to Postal Service Costing Methodologies (UPS 

Proposals One, Two, And Three), September 9, 2016, at 54, Appendix A (Order No. 3506); United States Postal Service, Office of Inspector 

General, Report No. RARC-WP-17-005, Examining Changes in Postal Product Costs, March 13, 2017, Appendix at 11, available at

https://www.uspsoig.gov/sites/default/files/reports/2023-01/RARC-WP-17-005_0.pdf.

235 Summary Description of USPS Development of Costs by Segments and Components, Fiscal Year 2021; Narrative Explanation of Econometric 

Demand Equations for Market Dominant Products Filed with Postal Regulatory Commission on January 20, 2022; Narrative E, July 1, 2022, 

folder “Summary Description FY2021,” file “APPH-21.docx,” at H-1-H-2 (FY 2022 Summary Descriptions).

236 See, e.g., Docket No. ACR2022, Library Reference USPS-FY22-1.

237 FY 2022 Summary Descriptions, Appendix H at H-1.
Docket No. SS2022-1 - 143 -

The flat-shaped mail products are:

• Flats (First-Class Mail)

• Flats (USPS Marketing Mail)

• In-County (Periodicals)

• Outside County (Periodicals)

The other mail products or categories are:

• Single-Piece Letters (First-Class Mail)

• Single-Piece Postcards (First-Class Mail)

• Presort Cards (First-Class Mail)

• Presort Letters (First-Class Mail)

• Enhanced Carrier Route238 (USPS Marketing Mail)

• Letters (USPS Marketing Mail)

• Parcels (USPS Marketing Mail)

• BPM Flats and Parcels (Package Services)

• Media and Library Mail (Package Services)

• Free Mail for the Blind and Otherwise Handicapped Persons & to service members

• Competitive Mail

To each of the 15 products or product categories corresponds a time series of volume, 

volume variable cost, and attributable cost data. The product-level time series data are 

annual observations over the 22 fiscal years, from 2000 to 2021. At the aggregate level, the 

time series of the overall accrued (or total operating) cost, total class-level volume, total 

mail volume, and total number of delivery points also range from FY 2000 to FY 2021.

c. The Econometric Analysis

(1) Introduction

The econometric analysis starts from the premise that flat-shaped mail cannot be isolated 

from mail of other shapes in the postal network, and therefore, it is important to place the 

analysis of the impact of volume declines on unit costs for flats mail in the general context 

of the loss of scale economies generated at the firm level by overall mail volume decline. 

Consequently, the connection between firm-level loss of scale economies and flats mail 

volumes should be clarified.

However, there are difficulties in defining the connection between flats mail volume and 

firm-wide loss of scale economies. The first difficulty is that there is no meaningful way to 

disaggregate the Postal Service cost function (the relationship between the cost and the 

output generating it) into a set of product-level or group-of-products-level cost functions. 

Consequently, the disaggregation of the degree of scale economies into single-product 

returns uses the relevant cost concept of incremental cost (now equivalent to attributable 

cost), whereas at the firm level, total operating cost is a more relevant cost concept. This 

238 This product category combines three products: High Density and Saturation Letters, High Density and Saturation Flats and Parcels, and 

Carrier Route.
Docket No. SS2022-1 - 144 -

makes the two measures difficult to compare unless total attributable cost is used to 

replace total operating cost at firm level.

The second difficulty comes from the challenge of controlling for relevant factors (e.g.,

inflation, mail mix, delivery points) that influence the relationship between the unit cost 

and the volumes in firm-level analysis. This difficulty is what motivates a more detailed 

analysis within an econometric framework. However, even the econometric approach is 

not without challenges, as explained below.

When the regression analysis employs the time series, the longer the time period covered 

by the analysis, the more robust the model is, and the more precise estimates will be. In the 

model used to estimate the relationship between the unit marginal costs and the volumes, a 

relative shortness of the time series (22 years) may represent an obstacle for econometric 

analysis. An additional question is whether the regression should be run separately for 

each flats mail product or jointly for all the considered flats.

The most important difficulty in this econometric analysis is the interpretation of the 

estimated relationship between the unit costs and volumes, as causal. The unit volume 

variable cost data, for example, are the outputs of upstream econometric estimations 

performed by the Postal Service and reported annually. The latter estimations seek to 

causally link cost variables to their drivers, while controlling for many relevant factors. 

Additionally, the estimation does not disentangle flats volume decline and flat mail 

processing workhour and overtime workhours. Consequently, re-estimating the temporal 

relation between the reported marginal costs and volumes, delivery points, and measures 

of volume mix, and interpreting the estimated marginal effects as causal is, to say the least, 

problematic. The emphasis here is placed on the joint predictive power of these variables, 

the objective being the forecasting of the marginal costs.

Based on the above observations, the analysis is organized in the following two parts.

Placing the flat-shaped mail in the general context of the scale diseconomies caused by mail 

decline. In the first part of the analysis, a firm-level metric for the DSE is defined based on 

the relevant economic literature and calculated using the available data. The DSE is also 

calculated for each of the flats mail products. The objective of this part is to clarify and 

measure the linkage between the rate of mail volume decline and the rate of cost decline. 

The general conclusion here is that although, over the considered period, flats mail volume 

has declined at a greater rate than Market Dominant mail volume, the magnitude of 

product-level DSE requires caution in concluding that flats mail volume decline has 

contributed more than other Market Dominant mail volume decline to the firm’s loss of 

scale economies.

Analyzing flats marginal costs from a predictive perspective. The second part of the analysis 

examines the linkage between flats unit volume variable costs (or marginal costs) and 

volumes while controlling for volume mix, delivery points, and inflation. An econometric 

model is built and estimated. The specific goal of this exercise is not to causally link unit 
Docket No. SS2022-1 - 145 -

cost to mail volumes, but to predict the marginal costs of flats for FY 2022 through FY 2026, 

after estimating the temporal correlational relationship between the marginal cost and the 

volume data over the time period of FY 2000 through FY 2021. So, the declines in volumes 

are taken as warning signs that may help determine the likely future trends in the flats 

products’ marginal costs.

(2) Part 1. Firm-Level and Product-Level Metrics for the 

Degree of Scale Economies and its Relation to Flats Mail

The notion of scale economies conveys the idea of a cost advantage induced by spreading 

the total operating cost over larger quantities of goods. The presence of economies of scale 

means that a proportionate increase in the output induces less than the proportionate 

increase in the cost with the effect that the cost per unit decreases.

239 The relevant metric is 

the DSE. The DSE can be interpreted as the elasticity of the composite output with respect 

to the cost needed to produce it. Returns to scale are increasing when the DSE is greater 

than one, constant when the DSE is equal to one, or decreasing when the DSE is less than 

one. BPW at 50. The DSE can be calculated in the context of the Postal Service as the ratio of 

total operating cost to total volume variable cost or, equivalently, the ratio of total 

operating (accrued) cost to total mail volume (this ratio is a proxy to average cost), divided 

by the average marginal cost (total volume variable cost divided by total mail volume). 

Because total operating cost is larger than volume variable cost, the magnitude of the 

metric is larger than one, i.e., returns to scale are increasing. The details of this calculation 

and the presentation of the metric are in Appendix A, Section IV.A.2. Analysis.

Figure IV-8 shows the curve of the firm-level degree of scale economies, the magnitude of 

which has fluctuated over the years while remaining well above one. In the presence of 

scale economies, the decline in volumes results in a comparatively slower decline in total 

costs. The specific contributions of flats mails to this loss of scale economies can be 

suggested by the relative volume decline for flats compared to other Market Dominant 

mail.

239 The concept and its measurement are discussed in William J. Baumol, John C. Panzar, & Robert D. Willig, Contestable Markets and the 

Theory of Industry Structure, Harcourt Brace Jovanovich, Inc. (1988 ed.) (hereinafter “BPW”).
Docket No. SS2022-1 - 146 -

Figure IV-8

Annual Degrees of Scale Economies (DSE)

1.75

1.80

1.85

1.90

1.95

2.00

2.05

2.10

2.15

2006 2008 2010 2012 2014 2016 2018 2020 2022

Fiscal Year
Docket No. SS2022-1 - 147 -

Table IV-1

Average Annual Growth Rate of Mail Volume, FY 2008–FY 2021

Mail Product Average Annual Growth Rate 

of Volume

First-Class Mail Flats -7.80%

USPS Marketing Mail Flats -9.16%

In-County Periodicals -4.65%

Outside County Periodicals -6.53%

Market Dominant Mail Total -3.81%

Competitive Mail Total 12.38%

Table IV-1 shows that the average rates of decline in volume have been higher for the four 

highlighted flats products than for Market Dominant mail on average. While this may 

suggest that the declines of flat-shaped mail volumes have notably contributed to the 

overall loss of scale economies, such a conclusion is implicitly assuming that firm-level DSE 

is the same as product-level DSE, which is not the case.

Product-specific returns to scale can be calculated as the ratio of the average incremental 

cost of the mail product to its marginal cost. BPW at 68. In the Postal Service’s costing 

methodology, product incremental cost is defined as the sum of its volume variable costs, 

its product specific costs, and those inframarginal costs calculated as part of a product's 

incremental costs. 39 C.F.R. § 3035.107(b).

Over the time period of FY 2017 through FY 2021, the DSEs for the four individual flats 

products have lied in the following ranges: First-Class Mail Flats [1.003-1.004], USPS 

Marketing Flats [1.003 -1.004], In-County Periodicals [1.000 -1.001], Outside County 

Periodicals [1.002-1.003]. The details are in the Appendix A, Section IV.A.2. Analysis. These 

magnitudes suggest that contrary to the conclusion suggested by the firm-level DSE, flats 

cost may have fallen almost as fast as volumes decline.

There are at least two limitations to the analysis conducted so far. The first is that the 

analysis does not isolate the impact of relevant factors, such as mail mix and delivery points 

(as a proxy for network factors). A second limitation is that the costs have not been 

adjusted for inflation. These two limitations are addressed in the second part of the 

analysis.

Part 2 of this analysis provides a more in-depth examination of the relationship between 

volume decline and flats mail unit cost, measured by marginal cost, within a predictive 

econometric setting.
Docket No. SS2022-1 - 148 -

(3) Part 2. Econometric Modeling and Estimation

As mentioned above, an econometric estimation of the observed temporal relationship 

between flats unit costs and their volumes, based on time-series data on unit cost and 

volumes cannot be properly interpreted as causal, because the cost variables are already 

obtained from the econometric estimations that are performed upstream by the Postal 

Service.

As noted above, this section is written from a predictive perspective. Its objective is to first 

estimate the temporal correlation between marginal costs and mail volumes, controlling 

for the effects of delivery points and mail mix, and accounting for the effect of inflation. 

Then, based on the estimation results, it seeks to predict the unit costs (taken here to be the 

marginal costs) of the four flats mail products based on extrapolating the observed trends 

in volumes, volume mix, and delivery points over the period FY 2000 through FY 2021. 

Both the model and the estimation method are presented in the Appendix A, Section IV.A.2. 

Analysis. The focus here is on out-of-sample prediction.

Volumes and delivery points are forecasted to serve as the inputs to the out-of-sample 

predictions of the inflation-adjusted marginal cost. To forecast the volume for each 

product, the annual growth rate of the volume is calculated for the period FY 2008 through 

FY 2021. Using the average annual growth rate or the compound annual growth makes 

negligible differences in the results. The calculated compound annual growth rate is 

successively applied to the annual volumes, beginning with the FY 2021 volume, and 

forecasting the volumes for the period running from FY 2022 through FY 2026. The same is 

done for mail class volumes and total volume. The volume shares are then calculated. For 

the delivery points, the extrapolation is also based on the data from FY 2008 to FY 2021. 

The resulting forecasts for the four flats mail products are shown in Table IV-2. Total 

volume and delivery points only depend on the fiscal year and, therefore, do not vary from 

one mail product to another.
Docket No. SS2022-1 - 149 -

Table IV-2

Forecasted Volumes and Delivery Points

Flat Mail Product FY Volume Mail Class Total Volume Delivery Points Total Volume

First-Class Mail Flats

2022 1,084.56 48,635.00 164.22 124,463.00

2023 999.99 46,466.10 165.35 120,183.00

2024 922.01 44,394.00 166.49 116,051.00

2025 850.12 42,414.20 167.63 112,060.00

2026 783.82 40,522.70 168.79 108,207.00

USPS Marketing Mail Flats

2022 2,606.30 64,215.90 164.22 124,463.00

2023 2,367.44 62,257.00 165.35 120,183.00

2024 2,150.46 60,357.90 166.49 116,051.00

2025 1,953.38 58,516.60 167.63 112,060.00

2026 1,774.35 56,731.60 168.79 108,207.00

In-County Periodicals

2022 426.36 3,446.24 164.22 124,463.00

2023 406.52 3,228.19 165.35 120,183.00

2024 387.60 3,023.93 166.49 116,051.00

2025 369.56 2,832.60 167.63 112,060.00

2026 352.36 2,653.37 168.79 108,207.00

Outside County Periodicals

2022 3,020.84 3,446.24 164.22 124,463.00

2023 2,823.60 3,228.19 165.35 120,183.00

2024 2,639.24 3,023.93 166.49 116,051.00

2025 2,466.92 2,832.60 167.63 112,060.00

2026 2,305.85 2,653.37 168.79 108,207.00

The out-of-sample predictions based on the extrapolation of the trends in the included 

observable explanatory variables are shown in Table IV-3, along with their standard errors 

(SE). Figure IV-9 displays the corresponding trends, historical and forecasted. The 

observed (non-predicted) numbers for FY 2022 are shown in the first (uncolored) row of 

Table IV-3 to allow their comparison with the forecasted figures for FY 2022. In Table IV-3, 

all the marginal costs (predicted and non-predicted) are in FY 2021 dollars.
Docket No. SS2022-1 - 150 -

The forecasts suggest that the continuous decline in mail volume will likely be 

accompanied by a continuous increase in the real unit cost, where the latter is measured by 

the marginal cost. Inflation would only worsen the upward trends if the marginal costs 

were expressed in nominal terms.

Table IV-3

Forecasted Marginal Costs Over FY 2022–FY 2026, in FY 2021 Dollars

FY/

Standard Error 

(SE)

First-Class 

Mail Flats

USPS Marketing 

Mail Flats

In-County 

Periodicals

Outside County 

Periodicals

Observed FY 2022 

Marginal Cost in 

FY 2021 Dollars

1.239 0.668 0.223 0.457

2022 1.279 0.713 0.237 0.456

SE 0.111899 0.112827 0.112337 0.112753

2023 1.296 0.726 0.245 0.455

SE 0.120742 0.121758 0.121163 0.121579

2024 1.311 0.738 0.252 0.454

SE 0.129795 0.13088 0.130197 0.130596

2025 1.324 0.750 0.260 0.454

SE 0.138847 0.139977 0.139229 0.139597

2026 1.335 0.761 0.269 0.454

SE 0.147919 0.149072 0.148287 0.148609
Docket No. SS2022-1 - 151 -

Figure IV-9

Historical and Forecasted Marginal Costs in FY 2021 Dollars

A shortcoming of the estimation, among other possible shortcomings, is the short (for 

purposes of econometric analysis) length of the time series, which probably has affected 

the precision of the estimations and, hence, the econometric forecasts. The prediction has 

also not attempted to disentangle flats volume decline and flat mail processing workhour 

and overtime workhour increases. These limitations are expected to be progressively 

mitigated as longer series become available in other uses of the model in the future.

(4) Conclusion

This econometric analysis has covered two related aspects of the linkage between the 

trends in flat-shaped mail volumes and marginal costs. The first aspect, which is discussed 

in Section IV.A.2.c.2., concerns the fact that flat-shaped mail cannot be operationally 

isolated from the other mail products and, therefore, share with all the other mail products, 

the burden of the loss of scale economies generated at the firm level by mail volume 

decline. The comparison of volume decline for individual flat-shaped mail products and 

general Market Dominant mail suggests that the declines in flats volumes have likely 

contributed to a greater extent than the declines in other Market Dominant mail volumes to 

the firm’s overall loss of scale economies, hence the increase in its unit costs. However, 

product-level DSEs, which are more relevant to this matter, suggest instead that this 

conclusion is too categorical and that the speed of cost decline may have matched that of 

volume decline for flat-shaped mails.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1995 2000 2005 2010 2015 2020 2025 2030

Unit Cost (dollars)

Fiscal Year

FC Flats Mark. Flats In County Outside County
Docket No. SS2022-1 - 152 -

To provide more insight about these suggestions, the effect of volume decline on unit costs 

is assessed after controlling for other possibly relevant factors, and this represents the 

second aspect of the above linkage. This second aspect, which is covered in Section 

IV.A.2.c.3., concerns the temporal relationship between flats mail volumes and their 

inflation-adjusted marginal costs. An econometric model has been proposed and estimated 

using data covering the period FY 2000 through FY 2021. The model controls for delivery 

points and mail mix. The estimation results were then used to forecast the unit costs of the 

four flat-shaped mail products under consideration, for the years FY 2022 through FY 

2026, based on the extrapolation of volume and delivery points trends. The forecasts are 

within reasonable margins of errors.

The key general lessons that emerge from all the analysis are the following:

• The continuous decline in mail volume, heavily impacted by the shift of hard copy 

communications to electronic media as the result of the development of the 

Internet, tends to continuously drive unit costs up, even when controlling for the 

effect of inflation. Mail products that experience faster declines in their volumes 

contribute more to the induced loss of scale economies at a firm level. Even though 

flats are among those mail products, caution should be exercised in concluding that 

their volume declines have contributed more than other Market Dominant products’ 

volume declines to the overall loss of scale economies. In this regard, it is worth 

noting that flat-shaped mail accounts for only a small percentage of total mail 

volume.

• Over time, flats real (inflation-adjusted) marginal costs continue to increase, while 

flats volumes decline. This suggests that the burden of the increase in unit costs will 

likely continue as the mail volumes continue to decline over the future years. Cost 

reduction programs must be established that at least match the rate of decline in 

order to stabilize marginal costs.

B. Analysis of Flats Unit Costs for Major 

Functional Categories by Dependent 

Component

For each product that consists of more than 80 percent flat-shaped mail, 39 C.F.R.

§ 3050.50(b)(2) requires the Postal Service to provide the unit attributable costs 

disaggregated into the following functional cost categories: mail processing, delivery, 

vehicle service driver, purchased transportation, window service, and other. 39 C.F.R. 

§ 3050.50(b)(2). These functional cost categories are identified as relevant to providing 

context to the "pinch points” discussed in Section III.B.4. Each of these functional cost 

categories contains costs from different dependent components. Specifically, dependent 

components costs are calculated for the major functional categories by adding the costs 

associated with supervisors and administration, service-wide benefits, and facility-related 

and equipment-related costs. Some dependent components contribute only to one 
Docket No. SS2022-1 - 153 -

functional cost category while others are relevant to several categories. For example, 

“Evaluated Route”240 is a dependent component, whose cost is entirely contained within 

the delivery functional cost category, while “Retiree Health Benefits” is a dependent 

component of all functional cost categories.241 Dependent component costs are used to 

calculate non-operational piggyback factors.242 Figure IV-10 lists the major dependent 

components for the three main functional cost categories.243 Major dependent components 

have at least 5 percent share of the costs of a functional category for a flats product. The 

costs of all other components are consolidated as other costs.244 Section IV.B.1. discusses 

the unit attributable cost associated with the functional cost categories for all flats products 

combined. Section IV.B.2. provides a detailed analysis of dependent components for each 

individual flats product separately.

240 Evaluated route is a dependent component associated with rural carriers. The dependent component contains the labor costs associated 

with evaluated routes. On an evaluated route, a rural carrier is paid based on the evaluated time of the route. The evaluated time is developed 

based on compensation categories for various carrier activities such as route length, and boxes served, as well as the volume by type delivered 

and collected. See Summary Description of USPS Development of Costs by Segments and Components, Fiscal Year 2021, July 1, 2022, folder 

“Summary Description FY2021,” file “CS10-21.docx.”

241 With the exception of Purchased Transportation.

242 See FY 2021 ACD at 262. Non-operational piggyback factors are employed in cost studies to augment labor cost estimates for the major 

functions by adding the costs associated with supervisors and administration, service-wide benefits, along with facility-related and equipmentrelated costs. See Docket No. ACR2021, Library Reference USPS-FY21-24, December 29, 2021, folder “USPS-FY21-24,” PDF file “USPS-FY21-

24.Preface.pdf.”

243 The vehicle service driver and window service functional cost categories are moved into the “other” category because they do not 

individually account for a large percentage of the total unit attributable cost. Purchased transportation cost category only has three dependent 

components, so they are all listed in Figure IV-10.

244 The mail processing functional category has more than 30 dependent components. Between FY 2008 and FY 2022, a number of dependent 

components have been added and removed but none which are of significance. See Docket No. ACR2022, Library Reference USPS-FY22-24, 

folder “USPS-FY22-24,” PDF file “USPS-FY22-24.Preface.pdf;” Excel file “FY22Public.PB.xlsx” (FY 2022 Piggybacks), tab “MailProc.” Delivery has 

more than 80 dependent components. Similar to mail processing, a number of dependent components have been added and removed between 

FY 2008 and FY 2022, but none contribute significantly to the functional category. See FY 2022 Piggybacks, tab “CityCarriers” for City Carriers, 

tab “Rural” for Rural Carriers. Examples of dependent components consolidated into the “other” category includes quality control, joint 

supervision clerks & carriers, higher level supervisors, custodial personnel, plant & building equipment maintenance, holiday leave, rents, fuel, 

utilities, equipment depreciation, and more.
Docket No. SS2022-1 - 154 -

Figure IV-10

Dependent Components in Each Major Functional Cost Category

Mail Processing 

Functional Cost 

Category

Mail Processing

Operating 

Equipment 

Maintenance

Retiree Health 

Benefits

Delivery Functional 

Cost Category

In-Office Direct 

Labor

(City Carriers)

In-Office General 

Support (City 

Carriers)

Delivery Activities 

(City Carriers)

Evaluated Routes 

(Rural Carriers)

Other Routes 

(Rural Carriers)

Retiree Health 

Benefits 

(City Carriers)

Retiree Health 

Benefits 

(Rural Carriers)

Purchased 

Transportation Cost 

Category

Domestic Air

Highway

Rail

Other Other

(Rural Carriers)

Other

(City Carriers)
Docket No. SS2022-1 - 155 -

1. Overall Flats Unit Attributable Costs by 

Functional Category (Mail Processing, Delivery, 

Purchased Transportation, and Other)

a. Cost Distribution Trend Across Major Functional 

Categories

Figure IV-11 shows how the unit attributable cost of all eight flats products is distributed 

across the three main functional cost categories between FY 2008 and FY 2022. Compared 

to the mail processing and delivery functional categories, the shares of purchased 

transportation and “other” costs remain relatively stable over the years.245 The functional 

category with the highest share in total flats attributable cost was the mail processing 

functional category prior to FY 2015 but changed to the delivery functional category in FY 

2015. See Figure IV-11. The delivery functional category’s share in total flats cost has been 

increasing since. As discussed in Section II.A., since FY 2014, the overall flats volume has 

declined and unit attributable costs have increased.246 Because Figure IV-11 provides the 

cost distribution trends for all flats products collectively, this cost distribution is affected 

by changes in the volume mix of flats products and the cost distributions of individual flats 

products. For example, USPS Marketing Mail High Density and Saturation Flats and Parcels 

has the highest volume of all flats products and experienced the lowest volume decline of 

all flats products.247 The Commission concludes that a part of this shift from mail 

processing to delivery costs can be attributed to the shift of the flats volume mix towards 

USPS High Density and Saturation Flats and Parcels (the flats product with a high share of 

delivery costs in its attributable cost e.g., 82.9 percent in FY 2022).248 Section IV.B.2., which 

discusses the functional costs for each flats product individually, shows that part of this 

shift is also due to increasing delivery costs for almost all flats products.

245 In FY 2021 and FY 2022, the proportion attributed to purchased transportation increased by a few percentage points.

246 As was illustrated by Figure II-5, total flats volume has been decreasing every year and unit attributable cost has been increasing.

247 See Section II.A., Table II-3.

248 See Section IV.B.2.a., Table IV-4.
Docket No. SS2022-1 - 156 -

Figure IV-11

Distribution of Attributable Cost across Functional Cost Categories, 

FY 2008–FY 2022249

249 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report; FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 

Public CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; Docket No. ACR2021, Library Reference USPS-FY21-24, folder “USPS-FY21-

24,” Excel file “FY21Public.PB.xlsx” (FY 2021 Piggybacks); Docket No. ACR2020, Library Reference USPS-FY20-24, folder “USPS-FY20-24,” Excel 

file “FY20Public.PB.xlsx” (FY 2020 Piggybacks); Docket No. ACR2019, Library Reference USPS-FY19-24, folder “USPS-FY19-24,” Excel file

“FY19Public.PB.xlsx” (FY 2019 Piggybacks); Docket No. ACR2018, Library Reference USPS-FY18-24, folder “USPS-FY18-24,” Excel file 

“FY18Public.PB.xlsx” (FY 2018 Piggybacks); Docket No. ACR2017, Library Reference USPS-FY17-24, folder “USPS-FY17-24,” Excel file 

“FY17Public.PB.xlsx” (FY 2017 Piggybacks); Docket No. ACR2016, Library Reference USPS-FY16-24, folder “USPS-FY16-24,” Excel file 

“FY16Public.PB.xls” (FY 2016 Piggybacks); Docket No. ACR2015, Library Reference USPS-FY15-24, folder “USPS-FY15-24,” ” Excel file 

“FY15Public.PB.xls” (FY 2015 Piggybacks); Docket No. ACR2014, Library Reference USPS-FY14-24, folder “USPS-FY14-24,” Excel file 

“FY14Public.PB.xls” (FY 2014 Piggybacks); Docket No. ACR2013, Library Reference USPS-FY13-24, folder “USPS-FY13-24,” Excel file 

“FY13Public.PB.xls” (FY 2013 Piggybacks); Docket No. ACR2012, Library Reference USPS-FY12-24, folder “USPS-FY12-24,” Excel file 

“FY12Public.PB.xls” (FY 2012 Piggybacks); Docket No. ACR2011, Library Reference USPS-FY11-24, folder “USPS-FY11-24,” Excel file 

“FY11Public.PB.xls” (FY 2011 Piggybacks); Docket No. ACR2010, Library Reference USPS-FY10-24, folder “USPS-FY10-24,” Excel file 

“FY10Public.PB.xls” (FY 2010 Piggybacks); Docket No. ACR2009, Library Reference USPS-FY09-24, folder “USPS-FY09-24,” Excel file 

“FY09Public.PB.xls” (FY 2009 Piggybacks); Docket No. ACR2008, Library Reference USPS-FY08-24, folder “USPS-FY08-24,” Excel file 

“FY08Public.PB.xls” (FY 2008 Piggybacks); Docket No. ACR2022, Library Reference USPS-FY22-2, December 29, 2022, Excel file “FY22Public Cost 

Segs and Comps.xlsx,” tab “CS14” (FY 2022 CS14); Docket No. ACR2021, Library Reference USPS-FY21-2, Excel file “FY21Public Cost Segs and 

Comps.xlsx,” tab “CS14” (FY 2021 CS14); Docket No. ACR2020, Library Reference USPS-FY20-2, Excel file “FY20Public Cost Segs and Comps.xlsx,” 

tab “CS14” (FY 2020 CS14); Docket No. ACR2019, Library Reference USPS-FY19-2, Excel file “FY19Public Cost Segs and Comps.xlsx,” tab “CS14” 

(FY 2019 CS14); Docket No. ACR2018, Library Reference USPS-FY18-2, Excel file “FY18Public Cost Segs and Comps.xlsx,” tab “CS14” (FY 2018 

CS14); Docket No. ACR2017, Library Reference USPS-FY17-2, Excel file “FY17Public Cost Segs and Comps.xlsx,” tab “CS14” (FY 2017 CS14); 

Docket No. ACR2016, Library Reference USPS-FY16-2, Excel file “FY16Public Cost Segs and Comps.xls,” tab “CS14” (FY 2016 CS14); Docket No. 

ACR2015, Library Reference USPS-FY15-2, Excel file “FY15Public Cost Segs and Comps.xls,” tab “CS14” (FY 2015 CS14); Docket No. ACR2014, 

Library Reference USPS-FY14-2, Excel file “FY14.2.Public Cost Segs and Comp.xls,” tab “CS14” (FY 2014 CS14); Docket No. ACR2013, Library 

Reference USPS-FY13-2, Excel file “FY13 Public.CS&CRpt.xls,” tab “CS14” (FY 2013 CS14); Docket No. ACR2012, Library Reference USPS-FY12-2, 

Excel file “FY12.Public CS&CRpt.xls,” tab “CS14” (FY 2012 CS14); Docket No. ACR2011, Library Reference USPS-FY11-2, Excel file “FY11Public 

CS&CRpt.xls,” tab “CS14” (FY 2011 CS14); Docket No. ACR2010, Library Reference USPS-FY10-2, Excel file “FY10 Public CS&C Rpt.xls,” tab “CS14” 

(FY 2010 CS14); Docket No. ACR2009, Library Reference USPS-FY09-2, Excel file “FY09 Public CS&C Rpt.xls,” tab “CS14” (FY 2009 CS14); Docket 

No. ACR2008, Library Reference USPS-FY08-2, Excel file “FY08.PubSeg&CompRpt.xls,” tab “CS14” (FY 2008 CS14).

51.0% 49.6% 47.8% 48.0% 47.9% 46.8% 46.8% 43.5% 43.3% 43.1% 42.2% 42.2% 41.3% 40.9% 39.6%

37.2% 39.2% 40.6% 40.6% 40.0% 41.1% 41.3% 44.5% 44.6% 45.4% 46.0% 45.9% 46.5% 47.1% 47.1%

7.6% 7.0% 7.4% 7.1% 7.6% 7.6% 7.6% 7.8% 8.3% 7.0% 7.5% 7.6% 7.6% 8.2% 9.6%

4.2% 4.2% 4.3% 4.3% 4.5% 4.5% 4.3% 4.2% 3.9% 4.5% 4.3% 4.4% 4.7% 3.9% 3.7%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Fiscal Year

Mail Processing Delivery Purchased Transportation Other
Docket No. SS2022-1 - 157 -

b. Flats Unit Attributable Cost Trends by Functional Cost 

Categories

For all flats products collectively, mail processing unit cost250 has not changed dramatically 

from FY 2008 to FY 2022. See Figure IV-12. While this cost has been increasing slightly 

since FY 2013, with larger increases between FY 2019 and FY 2021, it is more stable than 

delivery unit cost. Delivery unit cost of all flats products combined surpassed mail 

processing unit cost in FY 2015 and the gap between the unit costs of these two functional 

categories has been growing since then. See Figure IV-12. Additionally, purchased 

transportation cost of the flats products combined have increased since FY 2019.

There is a sudden jump in delivery unit cost from FY 2014 to FY 2015 which is due, in large 

part, to a methodological change approved in Docket No. RM2015-7. See Section IV.E. for 

details.251 However, in the years following, delivery unit cost continues to increase in a 

persistent manner which is unlikely to be a result of methodological changes.

250 Mail processing unit cost for all flats products collectively is the sum of mail processing costs for all flats products divided by total volume of 

flats products. In other words, this is equivalent to taking a weighted average of individual flats products’ mail processing unit costs, weighted 

by the proportion of the individual flats product’s volume in relation to total flats volume. Thus, flats products with high unit attributable costs 

and/or volumes will contribute more to the total flats mail processing unit cost.

251 This methodological change affected the unit attributable costs of USPS Marketing Mail High Density and Saturation Flats and Parcels and 

USPS EDDM-R the most. See Section IV.E.2., Table IV-9.
Docket No. SS2022-1 - 158 -

Figure IV-12

Total Flats Products Unit Attributable Cost by Functional Cost Category252

Figure IV-13 illustrates how each flats product contributes to the mail processing 

functional cost category. The distribution of mail processing cost across flats products has 

not changed significantly even as total mail processing unit cost increases and flats 

products volume mix changes.253

USPS Marketing Mail Flats accounts for the largest share of flats mail processing cost (34.4 

percent in FY 2022). In the last 4 years, the share of the First-Class Mail Flats mail 

processing cost in the total flats mail processing cost has increased slightly: from 23.0 

percent in FY 2018 to 25.7 percent in FY 2022. The share of the Outside County Periodicals 

mail processing cost in the total flats mail processing cost has decreased slightly: from 23.3 

percent in FY 2018 to 19.6 percent in FY 2022. The proportion of mail processing cost 

252 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report; FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 

Public CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 

Piggybacks; FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 

Piggybacks; FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 

CS14; FY 2017 CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY

2008 CS14.

253 With the exception of FY 2016, when some mail processing unit cost weight is shifted from USPS Marketing Mail Carrier Route to USPS 

Marketing Mail Flats. This is related to the shift of Carrier Route Flats to USPS Marketing Mail Flats in FY 2016 as discussed in Section IV.A.1.

0.128 0.131 0.130 0.132 0.130

0.120 0.122

0.122 0.124 0.125 0.128

0.133

0.142

0.146

0.143

0.093

0.103

0.111 0.111 0.108 0.105 0.108

0.125

0.127

0.132

0.140

0.145

0.160

0.169 0.169

0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.03 0.03

0.03

0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.01 0.01 0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Delivery Purchased Transportation Other
Docket No. SS2022-1 - 159 -

associated with USPS Carrier Route Flats and USPS Marketing Mail High Density and 

Saturation Flats and Parcels has remained steady (at approximately 11 to 14 percent and 

4.4 to 5.4 percent respectively) between FY 2018 and FY 2022. USPS Marketing Mail 

EDDM-R, In-County Periodicals, and BPM Flats have very small shares (less than 2 percent) 

in the total flats mail processing cost.254

Figure IV-13

Distribution of Mail Processing Unit Cost Across Flats Products, FY 2008–FY 2022255

Note: The share of the In-County Periodicals is less than 1 percent each year and the share of BPM Flats is between 1 and 2 percent. USPS 

Marketing Mail EDDM-R has zero mail processing costs.

254 USPS Marketing Mail EDDM-R has zero mail processing costs. See Figure IV-13; FY 2022 Piggybacks.

255 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report; FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 

Public CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 

Piggybacks; FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 

Piggybacks; FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks.

23.6% 26.1% 24.9% 25.3% 26.4% 25.3% 25.8% 24.3% 24.1% 24.7% 23.3% 22.8% 22.0% 21.9% 19.6%

26.0% 23.8% 26.1% 23.3% 21.6%

22.2% 21.2% 21.6% 21.0% 22.1% 23.0% 22.2% 24.7% 25.5%

25.7%

9.1% 8.4% 8.5% 9.9% 12.9%

14.1% 13.5% 12.5% 8.5%

11.6% 13.7% 14.1%

11.3%

11.9%

13.7%

37.4% 37.7% 35.8% 36.7% 33.8%

33.4% 33.9% 35.9% 40.7%

35.4% 32.9% 32.8%

34.8%

33.4% 34.4%

2.0%

2.1% 2.4% 2.6% 2.8%

2.7% 3.2% 3.2% 3.3% 3.7% 4.6%

5.4%

5.0%

4.9%

4.4%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Fiscal Year

USPS Marketing Mail High Density and Saturation Flats and Parcels USPS Marketing Mail Flats

USPS Marketing Mail Carrier Route First-Class Mail Flats

USPS Marketing Mail Every Door Direct Mail Retail Bound Printed Matter Flats

Outside County Periodicals In-County Periodicals
Docket No. SS2022-1 - 160 -

The distribution of delivery cost, on the other hand, varies more. See Figure IV-14. As the 

flats delivery cost increase, USPS Marketing Mail High Density and Saturation Flats and 

Parcels contribute more to the cost, and USPS Marketing Mail Flats contributes less.256

Since FY 2018, the combined share of the USPS Marketing Mail High Density and Saturation 

Flats and Parcels and USPS Marketing Mail Carrier Route products is more than half of the 

total flats delivery cost. In FY 2022, USPS Marketing Mail Flats and Outside County 

Periodicals each accounted for approximately 16 to 17 percent of the delivery cost. FirstClass Mail Flats only accounted for 8.2 percent of delivery cost in FY 2022, compared to 

25.7 percent of mail processing cost. USPS Marketing Mail EDDM-R, In-County Periodicals, 

and BPM Flats each accounted for less than 2 percent of delivery cost. These products have 

low volumes and, therefore, do not have large shares in total flats mail processing and 

delivery costs.257

Figure IV-14

Distribution of Delivery Unit Cost Across Flats Products, FY 2008–FY 2022258

Note: The share of In-County Periodicals is between 1 and 2 percent each year. The shares of BPM Flats and USPS Marketing Mail EDDM-R are 

approximately 1 percent each.

256 Again, this is with the exception of FY 2016, when the effect of the shift of volume from USPS Marketing Mail Carrier Route to USPS 

Marketing Mail Flats is seen in the shift of delivery unit cost weight from USPS Marketing Mail Carrier Route to USPS Marketing Mail Flats.

257 See Sections II.A.2. and IV.A.1. for volumes of these products.

258 Source: Commission calculations using data from FY 2022 Public CRA Report. FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report; FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 

Public CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018

Piggybacks; FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 

Piggybacks; FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks.

18.4% 20.1% 19.8% 19.2% 19.5% 18.5% 18.5% 17.1% 16.6% 16.7% 15.7% 15.7% 17.7% 17.2% 16.3%

11.5% 10.9% 11.1% 10.5% 11.0% 10.2% 9.8% 7.9% 8.1% 8.0% 7.9% 7.6%

24.6% 8.3% 8.0% 8.2% 24.1% 24.8% 25.6% 25.6% 28.1% 27.5% 26.1% 21.2% 23.6% 25.2% 24.7%

28.7% 23.1% 23.9% 24.4% 27.8% 26.9% 26.2% 24.2% 22.6% 22.6%

22.4% 26.6% 23.2% 20.9% 19.6%

17.2% 17.1% 16.8%

14.4%

14.9%

15.2% 16.4% 17.5% 17.3% 18.3%

23.0% 24.0% 25.1% 26.9% 28.9%

29.5%

29.6% 30.1%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Fiscal Year

USPS Marketing Mail High Density and Saturation Flats and Parcels USPS Marketing Mail Flats

USPS Marketing Mail Carrier Route First-Class Mail Flats

USPS Marketing Mail Every Door Direct Mail Retail Bound Printed Matter Flats

Outside County Periodicals In-County Periodicals
Docket No. SS2022-1 - 161 -

Figure IV-15 illustrates that purchased transportation unit cost has increased since FY 

2017 while distribution of purchased transportation cost across flats products has 

remained largely the same. Shares of purchased transportation costs vary by 

approximately 2 or 3 percentage points for all flats products except First-Class Mail Flats 

and Outside County Periodicals. The share of the First-Class Mail Flats purchased 

transportation unit cost in the total purchased transportation unit cost has increased by 

approximately 4 percent since FY 2015 while the share of Outside County Periodicals 

purchased transportation unit cost decreased by approximately 4 percent.

Figure IV-15

Distribution of Purchased Transportation Unit Cost Across Flats Products, FY 2008–FY 2022259

Note: The shares of USPS Marketing Mail High Density and Saturation Flats/Parcels and BPM Flats are each between 1 and 4 percent. In-County 

Periodicals and USPS Marketing Mail EDDM-R have no purchased transportation costs.

259 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 

CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

30.1% 29.6% 31.0% 30.2% 32.4% 32.2% 30.6% 30.9% 30.6%

26.8% 26.7% 27.9% 25.1% 25.7% 26.2%

33.2% 34.4%

33.4% 33.1%

32.0% 32.5% 30.6%

31.1% 31.8%

37.5% 32.7%

36.8% 38.6%

40.0%

35.0%

10.2% 7.4%

7.4% 7.5%

8.2% 8.4% 9.0%

7.1%

9.9%

8.7% 10.3%

8.3%

7.7%

7.2%

8.9%

23.3% 24.8%

24.7% 25.2%

22.8% 22.9% 24.6%

24.4%

23.2%

23.4%

26.2%

23.3%

24.3%

23.9%

24.7%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Fiscal Year

USPS Marketing Mail High Density and Saturation Flats/Parcels USPS Marketing Mail Flats

USPS Marketing Mail Carrier Route First-Class Mail Flats

USPS Marketing Mail Every Door Direct Mail Retail Bound Printed Matter Flats

Outside County Periodicals In-County Periodicals
Docket No. SS2022-1 - 162 -

2. Analysis of the Trends in Unit Attributable Costs 

by Major Functional Cost Category for NonCompensatory Flats Products260

a. Introduction

For all flats products, the mail processing dependent component makes up the highest cost 

in the mail processing functional category. This dependent component covers labor costs of 

clerks and mailhandlers performing mail processing activities.261 The delivery functional 

cost category consists of dependent components split by City Carriers and Rural 

Carriers.262 See Figure IV-16 for short descriptions of each major delivery dependent 

component.263 Unlike the other functional cost categories, purchased transportation cost 

does not include the piggyback factors and consists of only three dependent components: 

Domestic Air, Highway, and Rail. See FY 2021 ACD at 272.

Figure IV-16

Delivery Functional Category Major Dependent Components264

260 This subsection includes the discussion of flats products that were non-compensatory in FY 2021.

261 See Appendix A, Section IV.B. Analysis for more details.

262 City carriers corresponds to cost segments 6 and 7. Rural carriers corresponds to cost segment 10. See Appendix A, Section IV.B. Analysis for 

a short description of city and rural unit cost calculations.

263 See Cost Segment 6 Summary Description FY 2021; see Summary Description of USPS Development of Costs by Segments and Components, 

Fiscal Year 2021, July 1, 2022, folder “Summary Description FY2021,” file “CS07-21.docx” (Cost Segment 7 Summary Description FY 2021);

Summary Description of USPS Development of Costs by Segments and Components, Fiscal Year 2021, July 1, 2022, folder “Summary Description 

FY 2021,” file “CS10-21.docx” (Cost Segment 10 Summary Description FY 2021).

264 Major dependent components are any dependent components with more than 5 percent share of the costs of a functional category for a 

flats product.

City Carrier Major Dependent Components

•In-Office Direct Labor: Mail preparation (sequencing residual mail for delivery)

•In-Office General Support: Moving empty equipment, personal time, training

•Delivery Activities: Delivery and Collection of Mail

•Retiree Health Benefit: Normal cost of the retirement health benefits of active employees

Rural Carrier Major Dependent Components

•Evaluated Routes: Delivery and collection of mail on evaluated routes

•Other Routes: Relief routes for overburdened routes or other routes that cannot be handled by 

adding segments to existing routes

•Retiree Health Benefits: Normal cost of the retirement health benefits of active employees
Docket No. SS2022-1 - 163 -

Table IV-4

Distribution of Unit Attributable Cost Across Functional Category of Each Product, FY 2022265

Mail 

Processing Delivery

Purchased 

Transportati

on

Other

First-Class Mail Flats 55.1% 20.9% 18.1% 5.9%

USPS Marketing Mail High Density and 

Saturation Flats and Parcels

10.1% 82.9% 2.1% 4.9%

USPS Marketing Mail Carrier Route 29.7% 63.0% 4.7% 2.6%

USPS Marketing Mail Flats 55.4% 32.1% 9.6% 2.9%

Every Door Direct Mail Retail 3.6% 91.9% 0.4% 4.1%

In-County Periodicals 19.6% 78.3% 1.1% 1.0%

Outside County Periodicals 42.0% 41.4% 13.5% 3.0%

Bound Printed Matter Flats 48.2% 38.3% 10.2% 3.4%

While delivery cost outweighs mail processing cost for flats products overall, the 

distribution of unit attributable costs across functional categories differs depending on the 

product. Table IV-4 shows the FY 2022 distribution of each flats product’s unit attributable 

cost across the major functional categories, with the highest cost category highlighted in 

red. For half of the flats products, mail processing accounts for the highest share of unit 

attributable cost while for the other half, delivery accounts for the highest share. See Table 

IV-4.

Among flats products, where delivery is the highest cost category, delivery cost outweighs 

the next highest cost category (mail processing) by more than double.266 Delivery makes up 

between 63.0 percent and 91.9 percent of unit attributable costs for these products. For 

flats products that have the highest share of costs from mail processing, the range of the 

share is lower, between 42.0 percent and 55.4 percent. These products also have a higher 

share of attributable costs associated with purchased transportation costs than products 

for which the delivery category is the costliest: ranging from 9.6 percent to 18.1 percent 

compared to 0.4 percent to 4.7 percent.

265 Source: Commission calculations using data from Docket No. ACR2022, USPS-FY21-45, folder “FY22.45.Files,” folder “Rule 3050.50 Flats,” 

folder “Paragraph (B) – Financial Report,” Excel file “FY22.Rule.3050.50.Para.B.xlsx,” tab “Item b2;” FY 2022 Public CRA Report; FY 2022 

Piggybacks; Docket No. ACR2022, USPS-FY22-2, CS14.

266 Compare mail processing and delivery costs for USPS Marketing Mail High Density and Saturation Flats and Parcels, USPS Marketing Mail 

Carrier Route, USPS Every Door Direct Mail Retail, and In-County Periodicals in Table IV-4.
Docket No. SS2022-1 - 164 -

The next sections analyze each non-compensatory flats product separately in the order of 

flats products with the lowest cost coverage to the highest. The analysis provides details on 

how the unit costs of each major functional category and their dependent components have 

changed for each non-compensatory flats product between FY 2008 and FY 2022.267 For 

simplicity, only dependent components that comprise more than 5 percent of the 

functional category are singled out, with the rest consolidated as “other” costs, except for 

the purchased transportation functional category, which only has three dependent 

components.268

b. In-County Periodicals

The unit attributable cost of In-County Periodicals comes mostly from the delivery 

functional category, though it is only since FY 2019 that delivery costs have significantly 

diverged from mail processing costs. See Figure IV-17. Mail processing unit costs have 

small year-to-year deviations but the general trend appears to be relatively constant at 

approximately 5 cents per unit.

267 For brevity, this section will mainly focus on the dependent components of each product’s highest costing functional category and only look 

at the other functional categories when there are unusual trends.

268 The mail processing functional category has more than 30 dependent components. Between FY 2008 and FY 2022, a number of dependent 

components have been added and removed but none which are of significance. See FY 2022 Piggybacks tab “MailProc.” Delivery has more than 

80 dependent components. Similar to mail processing, a number of dependent components have been added and removed between FY 2008 

and FY 2022, but none contribute significantly to the functional category. See FY 2022 Piggybacks, tab “CityCarriers” for City Carriers, tab 

“Rural” for Rural Carriers.
Docket No. SS2022-1 - 165 -

Figure IV-17

In-County Periodicals Functional Unit Costs269

Delivery. There are two dependent components responsible for the significant increase in 

costs since FY 2019: evaluated routes and In-Office Direct Labor. See Figure IV-18. 

Evaluated routes is the costliest dependent component. In-Office Direct Labor, after having 

been even with or below Delivery Activities and Other City Costs, has surpassed the two 

since FY 2020 to become the second most costly dependent component for In-County 

Periodicals. The Postal Service attributed increases in City Carrier In-Office unit costs in FY 

2020, in part, to a change in costing methodology regarding sampling of city carriers in the 

office which led to higher delivery costs. FY 2020 ACD at 47. While the overall unit 

attributable cost for In-County Periodicals has decreased from FY 2021 to FY 2022 as seen 

in Section II.A.1. and Section IV.A.1., it is concerning that In-Office Direct Labor and 

evaluated routes delivery unit costs continue to increase.

269 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 

CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Delivery Purchased Transportation Other
Docket No. SS2022-1 - 166 -

Figure IV-18

In-County Periodicals Delivery Functional Category Dependent Components,

FY 2008–FY 2022270

c. Outside County Periodicals

In FY 2022, mail processing and delivery make up almost an equal proportion of the unit 

cost of Outside County Periodicals (42.0 percent and 41.4 percent, respectively).271 Figure 

IV-19 illustrates that this was not always the case, and that delivery unit cost has increased 

steadily since FY 2015, with a dramatic jump in FY 2020. Delivery unit cost only recently 

caught up with mail processing unit cost.

270 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 

CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14; 

Response to CHIR No. 8, Excel file “SS2022.1Resp.ChIR8.Q2.xlsx.”

271 See Table IV-4.

 -

 0.02

 0.04

 0.06

 0.08

 0.10

 0.12

 0.14

 0.16

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

In-Office Direct Labor In-Office General Support Delivery Activities

Retiree Health Benefits (City) Evaluated Routes Other Routes

Retiree Health Benefits (Rural) City Other Rural Other
Docket No. SS2022-1 - 167 -

Figure IV-19

Outside County Periodicals Functional Unit Costs272

(1) Mail Processing

The unit cost of all dependent components of the mail processing functional category has 

decreased in FY 2022. See Figure IV-20. The dotted line in Figure IV-20 represents a 2-

percent growth rate in mail processing unit cost since FY 2008 and the figure illustrates 

that while the unit costs for mail processing dependent component trend slightly upwards, 

it remains below a 2 percent growth rate, even with inflation in recent years well above 

that.

272 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 

CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

0.00

0.05

0.10

0.15

0.20

0.25

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Delivery Purchased Transportation Other
Docket No. SS2022-1 - 168 -

Figure IV-20

Outside County Periodicals Mail Processing Functional Category Dependent Components,

FY 2008–FY 2022273

(2) Delivery

While the unit cost of the mail processing functional category is higher than the delivery 

functional category, the trends of the delivery unit costs is much more concerning. Figure 

IV-21 shows that the dramatic increase in delivery unit costs in FY 2020 was due to a jump 

in the unit cost of In-Office Direct Labor dependent component. This is primarily the result 

of a change in costing methodology for City Carriers In-Office. FY 2020 ACR at 28. Since 

then, there have not been any more significant increases in unit cost of In-Office Direct 

Labor. Unit cost of evaluated routes, however, has been increasing persistently and

significantly since FY 2018 and it does not appear to be slowing.

273 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 

CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Operating Equipment Maintenance

Retiree Health Benefits (Current Year) Other dependent components

2 percent growth
Docket No. SS2022-1 - 169 -

Figure IV-21

Outside County Periodicals Delivery Functional Category Dependent Components,

FY 2008–FY 2022274

(3) Purchased Transportation

Purchased transportation makes up 13.5 percent of the unit cost for Outside County 

Periodicals, the second highest share associated with purchased transportation among all 

flats products. Highway transportation contract unit cost is the main driver of the 

purchased transportation functional category for Outside County Periodicals. The unit cost 

of the highway transportation dependent component had almost doubled from FY 2017 to 

FY 2022.275 See Figure IV-22.

274 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report; FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 

Public CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 

Piggybacks; FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 

Piggybacks; FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; Response to CHIR No. 8, Excel file “SS2022.1Resp.ChIR8.Q2.xlsx.”

275 See Section IV.D.2. for further discussion.

 -

 0.02

 0.04

 0.06

 0.08

 0.10

 0.12

 0.14

 0.16

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unjit Cost (dollars)

Fiscal Year

In-Office Direct Labor In-Office General Support Delivery Activities

Retiree Health Benefits (City) Evaluated Routes Other Routes

Retiree Health Benefits (Rural) City Other Rural Other
Docket No. SS2022-1 - 170 -

Figure IV-22

Outside County Periodicals Purchased Transportation Functional Category Dependent

Components, FY 2008–FY 2022276

d. USPS Marketing Mail Flats

Mail processing, delivery, and purchased transportation unit costs have all increased for 

USPS Marketing Mail Flats since FY 2016. See Figure IV-23. Mail processing costs have 

increased more than delivery costs, which is especially noticeable from FY 2018 to FY 

2021. While from FY 2021 to FY 2022 the unit costs of the other major functional 

categories have either decreased (delivery) or stayed the same (mail processing, other), 

purchased transportation unit cost increased by 20.9 percent.277

276 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 CS14; FY 2016 CS14; 

FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

277 See Docket No. ACR2021, Library Reference USPS-FY21-45, folder “Rule 3050.50 Flats,” folder “Paragraph (b) – Financial Report,” Excel file 

“FY21.Rule.3050.50.Para.B.xlsx,” tab “Item b2;” Docket No. ACR2022, Library Reference USPS-FY22-45, folder “Rule 3050.50 Flats,” folder 

“Paragraph (b) – Financial Report,” Excel file “FY22.Rule.3050.50.Para.B.xlsx,” tab “Item b2.”

 -

 0.010

 0.020

 0.030

 0.040

 0.050

 0.060

 0.070

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Domestic Air Highway Railroad
Docket No. SS2022-1 - 171 -

Figure IV-23

USPS Marketing Mail Flats Functional Categories, FY 2008–FY 2022278

(1) Mail Processing

Figure IV-24 shows the trends of all the dependent components that comprise 5 percent or 

more of the mail processing functional category. While the other dependent components 

have increased slightly since FY 2016, the bulk of the increase comes from the mail 

processing dependent component.

The unit cost of the mail processing functional category appeared constant from FY 2021 to 

FY 2022 as Figure IV-23 shows. The dependent components in Figure IV-24 illustrate that 

this is due to the elimination of the Retiree Health Benefits dependent component rather 

than a decrease in mail processing dependent component costs. In fact, the mail processing 

dependent component has been on a steep, linear incline since FY 2016.279

278 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 

CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

279 See Appendix A, Section IV.B. Analysis for an analysis of the driving factors for this incline.

0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

0.400

0.450

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Delivery Purchased Transportation Other
Docket No. SS2022-1 - 172 -

Figure IV-24

USPS Marketing Mail Flats Mail Processing Functional Category Dependent Components,

FY 2008–FY 2022280

(2) Delivery

Figure IV-23 shows that while the unit costs of the delivery functional category appear 

relatively stable, a closer look at the dependent components reveals that there has been a 

large increase in costs associated with the evaluated routes dependent component. See 

Figure IV-25. The shift in cost from evaluated routes to delivery activities in FY 2016 is due 

to the migration of Carrier Route Flats to the USPS Marketing Mail Flats products as a result 

of the implementation of FSS-specific prices, which was eliminated the next year. FY 2016 

ACD at 48 n.59.

280 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report; FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 

Public CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 

Piggybacks; FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 

Piggybacks; FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Mail Processing Operating Equipment Maintenance

Retiree Health Benefits (Current Year) Other dependent components
Docket No. SS2022-1 - 173 -

Figure IV-25

USPS Marketing Mail Flats Delivery Functional Category Dependent Components,

FY 2008–FY 2022281

(3) Purchased Transportation

Purchased transportation costs associated with highway transportation contracts is the 

driving component for the increase in purchased transportation costs.282 See Figure IV-26.

281 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report; FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 

Public CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 

Piggybacks; FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 

Piggybacks; FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; Response to CHIR No. 8, Excel file “SS2022.1Resp.ChIR8.Q2.xlsx.”

282 See Section IV.D.2. for further discussion.

 -

 0.02

 0.04

 0.06

 0.08

 0.10

 0.12

 0.14

 0.16

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

In-Office Direct Labor In-Office General Support Delivery Activities

Retiree Health Benefits (City) Evaluated Routes Other Routes

Retiree Health Benefits (Rural) City Other Rural Other
Docket No. SS2022-1 - 174 -

Figure IV-26

USPS Marketing Mail Purchased Transportation Dependent Components,

FY 2008–FY 2022283

e. USPS Marketing Mail Carrier Route

Increases in Carrier Route Flats unit attributable cost is driven by higher delivery unit 

costs. See Figure IV-27.

283 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 CS14; FY 2016 CS14; 

FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Domestic Air Highway Railroad
Docket No. SS2022-1 - 175 -

Figure IV-27

USPS Marketing Mail Carrier Route Functional Unit Costs284

(1) Mail Processing

The mail processing unit cost of carrier route flats, while low compared to delivery costs, 

has almost doubled since FY 2016. While the increase appears to level out between FY 

2019 and FY 2022 in Figure IV-27, separating the dependent components in Figure IV-28 

shows that the mail processing dependent component has continued to increase 

dramatically in FY 2021 and FY 2022 and that the stability of the mail processing functional 

category from FY 2021 to FY 2022 was only because of the elimination of Retiree Health 

Benefits.

284 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 

CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

0.00

0.05

0.10

0.15

0.20

0.25

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Delivery Purchased Transportation Other
Docket No. SS2022-1 - 176 -

Figure IV-28

USPS Marketing Mail Carrier Route Mail Processing Functional Category Dependent

Components, FY 2008–FY 2022285

(2) Delivery

Similar to other flats products, there is a jump in the unit cost of the In-Office Direct Labor 

dependent component in FY 2020 which is due to a methodology change. The unit costs of 

all the major dependent components of the delivery functional category are trending

upwards. See Figure IV-29. Rural Carrier evaluated routes has the highest unit costs for 

Carrier Route Flats and, similar to other flats products, is increasing at a faster rate than the 

other dependent components.

285 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks.

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Operating Equipment Maintenance

Retiree Health Benefits (Current Year) Other dependent components
Docket No. SS2022-1 - 177 -

Figure IV-29

USPS Marketing Mail Carrier Route Delivery Functional Category Dependent Components, 

FY 2008–FY 2022286

f. First-Class Mail Flats287

In FY 2022, First-Class Mail Flats had the largest gap between its mail processing unit cost 

and the unit cost of other functional categories. Only 20.9 percent of First-Class Mail Flats 

attributable cost is associated with delivery activities. This is the lowest share of delivery 

costs among all flats products. See Section IV.B.2.a., Table IV-4. It is also the flats product 

that has the highest share of cost associated with purchased transportation, 18.1 

percent.288 Unit costs in all functional categories are trending upwards. See Figure IV-30.

286 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; Response to CHIR No. 8, Excel file “SS2022.1Resp.ChIR8.Q2.xlsx.”

287 The product was non-compensatory in FY 2021 only.

288 See Section IV.2.B.a.

 -

 0.02

 0.04

 0.06

 0.08

 0.10

 0.12

 0.14

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

In-Office Direct Labor In-Office General Support Delivery Activities

Retiree Health Benefits (City) Evaluated Routes Other Routes

Retiree Health Benefits (Rural) City Other Rural Other
Docket No. SS2022-1 - 178 -

Figure IV-30

First-Class Mail Flats Functional Unit Costs289

(1) Mail Processing

Similar to USPS Marketing Mail Flats, while the unit cost of the mail processing functional 

category decreased in FY 2022, as Figure IV-30 illustrates, this is only due to the 

elimination of costs in the Retiree Health Benefits dependent component. The unit cost 

associated with the mail processing dependent component is still increasing. See Figure IV31.

289 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 

CS14; FY 2016 CS14; FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Delivery Purchased Transportation Other
Docket No. SS2022-1 - 179 -

Figure IV-31

First-Class Mail Flats Mail Processing Functional Category Dependent Components,

FY 2008–FY 2022290

(2) Delivery

Unlike most other flats products,291 which only had a substantial increase in unit costs for 

In-Office Direct Labor in FY 2020 due to the methodology change,292 the unit cost for InOffice Direct Labor of First-Class Mail Flats has had a number of increases since FY 2017, 

and they do not appear to be associated with any methodology changes.293 The unit cost of 

evaluated routes has been increasing at a steady rate every year since FY 2008 except for 

FY 2018. See Figure IV-32.

290 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks.

291 The unit costs for In-Office Direct Labor of In-County Periodicals continued to increase after FY 2020, but for other non-compensatory flats 

products, In-Office Direct Labor costs leveled off after FY 2020. See Figures IV-18, IV-21, IV-25, and IV-29.

292 FY 2020 ACR at 28 (citing Docket No. RM2020-10).

293 See Table IV-8 in Section IV.E. for a list of methodology changes.

 -

 0.10

 0.20

 0.30

 0.40

 0.50

 0.60

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Mail Processing Operating Equipment Maintenance

Retiree Health Benefits (Current Year) Other Dependent Components
Docket No. SS2022-1 - 180 -

Figure IV-32

First-Class Mail Flats Delivery Functional Category Dependent Components, 

FY 2008–FY 2022294

(3) Purchased Transportation

First-Class Mail Flats has the highest purchased transportation unit costs of all the flats 

products. It’s also the only flats product with a significant proportion of costs associated 

with the domestic air contracts. While the unit cost relating to highway contracts of other 

flats products was relatively flat until FY 2017, it has been increasing for First-Class Mail 

Flats since FY 2008, with a large jump in FY 2021. See Figure IV-33. Unit costs of domestic 

air contracts have been increasing steadily since FY 2014.

294 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 Piggybacks; FY 2021 Piggybacks; FY 2020 Piggybacks; FY 2019 Piggybacks; FY 2018 Piggybacks; 

FY 2017 Piggybacks; FY 2016 Piggybacks; FY 2015 Piggybacks; FY 2014 Piggybacks; FY 2013 Piggybacks; FY 2012 Piggybacks; FY 2011 Piggybacks; 

FY 2010 Piggybacks; FY 2009 Piggybacks; FY 2008 Piggybacks; Response to CHIR No. 8, Excel file “SS2022.1Resp.ChIR8.Q2.xlsx.”

 -

 0.02

 0.04

 0.06

 0.08

 0.10

 0.12

 0.14

 0.16

 0.18

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

In-Office Direct Labor In-Office General Support Delivery Activities

Retiree Health Benefits (City) Evaluated Routes Other Routes

Retiree Health Benefits (Rural) City Other Rural Other
Docket No. SS2022-1 - 181 -

Figure IV-33

First-Class Mail Flats Purchased Transportation Functional Category Dependent Components, 

FY 2008–FY 2022295

g. Conclusion

First-Class Mail Flats, USPS Marketing Mail Flats, and Carrier Route Flats are all 

experiencing increases in mail processing unit costs, though delivery costs outweigh mail 

processing costs for Carrier Route Flats. The driving factors for these higher mail

processing unit costs are increases in clerk and mailhandler costs associated with ASFM

100 operations296 and increases in unit costs for mail processing activities at post offices 

and other small facilities.297

Delivery unit costs are increasing for all flats products. This is primarily due to increases in 

unit costs to deliver and collect mail by rural carriers (evaluated routes). Increases in 

delivery unit costs are also magnified by increases in unit costs associated with mail 

preparation and sequencing by city carriers (In-Office Direct Labor), including an increase 

295 Source: Commission calculations using data from FY 2022 Public CRA Report; FY 2021 Public CRA Report; FY 2020 Public CRA Report; FY 2019 

Public CRA Report; FY 2018 Public CRA Report; FY 2017 Public CRA Report; FY 2016 Public CRA Report; FY 2015 Public CRA Report; FY 2014 

Public CRA Report FY 2013 Public CRA Report; FY 2012 Public CRA Report; FY 2011 Public CRA Report; FY 2010 Public CRA Report; FY 2009 Public 

CRA Report; FY 2008 Public CRA Report; FY 2022 CS14; FY 2021 CS14; FY 2020 CS14; FY 2019 CS14; FY 2018 CS14; FY 2017 CS14; FY 2016 CS14; 

FY 2015 CS14; FY 2014 CS14; FY 2013 CS14; FY 2012 CS14; FY 2011 CS14; FY 2010 CS14; FY 2009 CS14; FY 2008 CS14.

296 See Appendix A, Section IV.B. Analysis for driving factors in increases in mail processing dependent component unit costs.

297 Some increases in mail processing unit costs in FY 2018 at post offices and other small facilities is due to a methodology change (Docket No. 

RM2018-10, Order on Analytical Principles Used in Periodic Reporting (Proposal Seven), October 12, 2018 (Order No. 4855), but this does not 

explain the continued increases. See Cost Segment 3 Summary Description FY 2021.

 -

 0.02

 0.04

 0.06

 0.08

 0.10

 0.12

 0.14

 0.16

 0.18

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Domestic Air Highway Railroad
Docket No. SS2022-1 - 182 -

in FY 2020 in the unit costs of In-County Periodicals, Outside County Periodicals, Carrier 

Route Flats, and BPM Flats due to a costing methodology change.298

Purchased transportation unit costs are also increasing for Outside County Periodicals, 

USPS Marketing Mail Flats, and First-Class Mail Flats. These increases are driven by 

increases in unit costs associated with highway contracts. Of all flats products, First-Class 

Mail Flats is the product with the highest share of purchased transportation cost (that 

share was more than 18 percent in FY 2022). It is also the only flats product that has a large 

and increasing unit cost associated with domestic air contracts.

C. Impact of Excess Capacity and Idle Time on 

Flats Sorting Operations

1. “Excess Capacity” in Postal Service Operations

As required by section 206(a)(1)(B) of the PSRA, within the Flats Study, the Commission 

must quantify the effect of excess capacity on flats operations and costs. In this section, the 

Commission analyzes excess capacity in mail processing and discusses excess capacity in 

transportation and delivery. In the mail processing operations, at the facility level, the 

Commission econometrically evaluates how excess capacity affects workhours used to 

process flats on automated equipment (AFSM and FSS).

For this purpose, the Commission first econometrically evaluates how flats volume and 

machine downtime affect excess capacity. Then, the Commission analyses the impact of 

flats volume and the number of machines at each facility on excess capacity. Finally, the 

Commission examines how flats volume and excess capacity affect workhours (and costs) 

at the mail processing facilities. The methodology and results of the econometric analysis 

are discussed in Sections IV.C.1. and IV.C.2., and some additional details are provided in 

Appendix A, Section IV.C. Analysis.

The Federal Reserve Board refers to capacity as “sustainable maximum output—the 

greatest level of output a plant can maintain within the framework of a realistic work 

schedule after factoring in normal downtime and assuming sufficient availability of inputs 

to operate the capital in place.”299 The Postal Service defines “downtime [as a measure of 

the amount] of time that machines [are] not operational during a run, as distinct from the 

298 FY 2020 ACR at 28 (citing Docket No. RM2020-10).

299 Board of Governors of the Federal Reserve System, Capacity Utilization Explanatory Notes, available at 

https://www.federalreserve.gov/releases/g17/capnotes.htm#:~:text=The%20Federal%20Reserve%20Board%20constructs,divided%20by%20a%

20capacity%20index.
Docket No. SS2022-1 - 183 -

amount of time machines are not used outside of processing runs,”300 which is idle time.301

In Response to CHIR No. 3, the Postal Service discussed the factors that determine excess 

capacity in flats mail processing, transportation, and delivery operations. Response to CHIR 

No. 3, question 5.

a. Mail Processing

The Postal Service stated that the main reason for excess capacity in flats mail processing is 

the steady decline in flats mail volume. Over the past few years, as volume declined, “the 

Postal Service has made minimal reductions to the flat processing fleet,” i.e., FSS and AFSM. 

Therefore, “the decline in volume without a commensurate decline in number of machines 

has led to an increase in excess capacity.” Id. question 5.a.

During facility visits, Commission staff learned that on low-volume days facility staff made 

determinations not to use FSS equipment, and sort flats on the AFSM equipment instead. 

This led to FSS equipment being unused. At one facility the Commission staff visited, FSS 

was usually run on weekends and sometimes on Fridays. Only running the FSS machines 

two-three times a week significantly increased idle time. At another facility that only 

operated AFSMs, management discussed their efforts to decrease the idle time. They ran 

AFSM machines each day and used the Run Plan Generator to optimize machine usage. 

Besides a certain 4-hour maintenance window, management had flexibility to choose times 

for different sort plans based on mail volumes. As a result, the AFSMs at that facility had 

very low idle time.

The Postal Service defines daily machine capacity as the number of pieces that theoretically 

“could be processed in 16 hours of run time per day with a target throughput of 7,500 

pieces per hour for AFSM” machines and “19,000 pieces per hour for FSS” machines. Id. The 

Postal Service also defines percent utilization as the “actual number of pieces processed 

divided by capacity.” Accordingly, AFSM daily capacity is 120,000 (= 7500 x 16) pieces and 

its annual capacity is 43,800,000 (=120,000*365). Similarly, the FSS daily capacity is 

304,000 (=19,000*16) pieces, and its annual capacity is 110,960,000 (=304,000*365). 

Thus, the percent excess capacity is calculated as 1 minus utilization. Id. Subsequently, the 

Postal Service concluded that in FY 2022, excess capacity for AFSM was 42 percent, and for 

FSS was 51 percent. Id.

The Commission analyzed the relationship between volumes and excess capacity at the 

facility level. Using MODS data for FY 2017 through FY 2022 by mail processing facility for 

two machine types (AFSM and FSS), the Commission developed a panel dataset with the 

data on volume, workhours, number of machines, machine downtime, and capacity by the 

finance number for each machine type at the corresponding facility. See Appendix A, 

300 Response to CHIR No. 3, question 5.a.; Library Reference USPS-SS2022-1/NP3, December 21, 2022, folder “SS22.1_NP3_ResponseFiles,” 

folder “Q.5,” Excel file “Flats MP Excess Capacity FY 2022.xlsx,” tab “Main.”

301 During machine idle time, they “are not run but are available to do so.” See, e.g., Docket No. N2012-1, Responses of United States Postal 

Service Witness Emily Rozenberg to Public Representative Interrogatories PR/USPS-T3-17, February 16, 2012. Generally speaking, idle time is a 

period of time when employees or equipment are in a waiting period. See https://www.getflowpath.com/blog/how-to-calculate-idle-time-andwhy-its-important.
Docket No. SS2022-1 - 184 -

Section IV.C. Analysis for details. Excess capacity for each machine at the facility was 

estimated using the formula provided by the Postal Service. Response to CHIR No. 3, 

question 5.

The Commission’s econometric analysis confirms that there is a significant reverse 

relationship between the excess capacity and flats volume processed by each machine type 

(FSS or AFSM). See Table IV-5. In this econometric model, excess capacity is a dependent 

variable, and volume and machine downtime are the explanatory variables. This model 

explains how a unit change in volume or downtime may impact excess capacity.302 The sign 

of a coefficient indicates if a relationship is positive or negative. In addition, the P-Value of 

coefficient indicates whether this relationship is statistically significant.303 The magnitude 

of impact is related to the size of the coefficient. Id. at 133-35. The data used in this analysis 

were provided by the Postal Service and cover the period from FY 2017 to FY 2022. See 

Appendix A, Section IV.C. Analysis for details.

As presented in Table IV-5, negative volume coefficients for ASFM and FSS machines mean 

that a decrease in flats volumes processed on these machines corresponds with an increase 

in the excess capacity at the Postal Service’s facilities (when machine downtime does not 

change). Furthermore, the P-Values for these two coefficients indicate that the reverse 

relationship between excess capacity and volume is significant. A decline in volume results 

in an increase in excess capacity.

The downtime coefficient is more predictable. As Table IV-5 displays, a significant positive 

relationship exists between machines’ downtime and excess capacity at the facility level. 

An increase in machine downtime corresponds with a slight increase in excess capacity, 

assuming the processed volume does not change.

302 A logarithm (ln) transform in variables volume and downtime ensures the relationships are linearized. It also allows an easier interpretation 

of the result in percentage. See Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach 41 (5th ed. 2013). Since excess capacity 

is already a percentage ratio, it does not need to be transformed into logarithm form.

303 When the P-Value is less than 0.05 and close to zero, it means that with 95 percent confidence, we can accept the coefficient. In other 

words, the coefficient is statistically significant. See Wooldridge, supra, at 41.
Docket No. SS2022-1 - 185 -

Table IV-5

Regression Results

Relationship Between Excess Capacity, Volume, and Downtime FY 2017-FY 2022

AFSM

Excess Capacity Coefficient Std. err. T P>t [95% conf. interval]

lnVolume -0.206765 0.00937 -22.07 0.000 -0.225146 -0.188383

lnDowntime 0.058068 0.00814 7.13 0.000 0.042091 0.074046

_cons 3.724427 0.12611 29.53 0.000 3.476996 3.971858

R-squared: Obs per group:

Within = 0.4807 min = 195

Between = 0.6788 avg = 197.8

Overall = 0.4817 max = 199

F(2,1179) = 545.77

corr(u_i, Xb) = 0.0581 Prob > F = 0.000

FSS

Excess Capacity Coefficient Std. err. T P>t [95% conf. interval]

lnVolume -0.115823 0.0122991 -9.42 0.000 -0.140052 -0.091594

lnDowntime 0.091436 0.0127809 7.15 0.001 0.066257 0.116614

_cons 2.143740 0.1505374 14.24 0.000 1.847184 2.440296

R-squared: Obs per group:

Within = 0.6733 min = 33

Between = 0.8725 avg = 41

Overall = 0.6733 max = 43

F(2,238) = 46.18

corr(u_i, Xb) = 0.3961 Prob > F = 0.000

Moreover, as shown in Table IV-6, in both AFSM and FSS flats processing operations, 

additional machines at mail processing facilities increase excess capacity if volumes are 

stable. In a declining volume environment, excess capacity increases if the number of 

machines is unchanged. In other words, excess capacity may increase when volume 

declines at a facility without the number of machines being adjusted appropriately. 

Response to CHIR No. 3, question 5.a.
Docket No. SS2022-1 - 186 -

Table IV-6

Regression Results

Relationship Between Excess Capacity, Volume, and Number of Machines FY 2017-FY 2022

AFSM

Excess Capacity Coefficient Std. err. T P>t [95% conf. interval]

lnVolume -0.297196 0.006524 -45.55 0.000 -0.3099963 -0.2843953

lnMachinesNo 0.287799 0.010448 27.55 0.000 0.2673009 0.3082967

_cons 5.469688 0.109418 49.99 0.000 5.255012 5.684365

R-squared: Obs per group:

Within = 0.6705 min = 195

Between = 0.9571 avg = 197.8

Overall = 0.6709 max = 199

F(2,1179) = 1199.32

corr(u_i, Xb) = 0.0862 Prob > F = 0.000

FSS

Excess Capacity Coefficient Std. err. T P>t [95% conf. interval]

lnVolume -0.1850294 0.0069807 -26.51 0.000 -0.1987812 -0.1712777

lnMachines 0.1856448 0.0076024 24.42 0.000 0.1706682 0.2006214

_cons 3.902918 0.1210274 32.25 0.000 3.664497 4.14134

R-squared: Obs per group:

Within = 0.7503 min = 33

Between = 0.9810 avg = 41

Overall = 0.7984 max = 43

F(2,238) = 357.54

corr(u_i, Xb) = 0.4333 Prob > F = 0.000
Docket No. SS2022-1 - 187 -

b. Transportation

The Postal Service specified that there is “potential excess capacity in flat transportation 

due to FSS processing.” Id. The Commission acknowledges that the Postal Service will 

discontinue FSS processing from all facilities in FY 2023. Id. However, it is unclear how 

much transportation utilization will improve after decommissioning all FSS at the mail 

processing facilities. The Postal Service stated that it “will reevaluate plant-to-delivery unit 

transportation at former FSS sites as FSS processing is discontinued in FY 2023.” Id.

When discussing excess capacity in current transportation operations related to flats, the 

Postal Service states that it determines surface transportation by reviewing trip utilization 

and calculates it as the average floor utilization of the truck or trailer by leg for each trip. Id.

However, this calculation is not for flats transportation only because the truck or trailer 

floor is not used only for flats transportation. Id.

An example of transportation operations that the Commission staff observed and likely led 

to excess transportation capacity, was the fact that only mail of the same shape, same mail 

class, and for the same destination could be combined in containers as they were being 

consolidated for long-haul transportation in the surface transportation network. As a 

representative at a STC explained, filling containers in this manner with declining FirstClass Mail letters and flats volumes prevented better maximum use of container space. In 

the case of stackable containers, such as Gaylord four-foot containers, it also prevented 

stacking them on trucks (see Section III.D.1.).

Commission staff also observed that to meet service standards, facility management often 

makes decisions, to dispatch delayed mail or misrouted containers on direct underutilized 

trips, which contributes to excess capacity in transportation.

Although the usual standard in industries is to consider excess capacity when the 

utilization is less than 80 or 85,304 the Postal Service considers excess capacity in 

transportation when the utilization is less than 65 percent. Response to CHIR No. 3, 

question 5.a. Besides “processing operating plans” and “service standards” constraints and 

“arrive by the Critical Entry Times (CETs),” which sometimes make the transportation run 

under-utilized, there are other factors that impact transportation utilization. Id.

These factors are “container fill rates, the number of trips operating in lanes, and the 

amount of time between the available dispatch time and required arrival at destination as 

it compares to the service standards of the product on the trips.” Id. Consequently, the 

Postal Service concluded that in FY 2022, the utilization rate for HCR was 42.46 percent, 

and for PVS was 32.54 percent. In total (as an annual average), the transportation 

utilization for FY 2022 was 39 percent. Id.

304 The Effect of Imports of Steel on the National Security, U.S. Department of Commerce, Bureau of Industry and Security, Office of Technology 

Evaluation, January 11, 2018, at 4; CRI: How Manufacturers Should Account for Excess Capacity, available at 

https://cricpa.com/insight/manufacturers-excess-capacity/.
Docket No. SS2022-1 - 188 -

This utilization rate is for more than flats and includes all other types of mail. As discussed 

in Section III.D.1., the Postal Service generally combines mail products with similar service 

standards, and with the same origin and destination points, on shared transportation. 

Therefore, the data are not available that would allow isolating the excess capacity in 

transportation of flats mail from transportation of all mail shapes.

c. Delivery

The Postal Service stated that it is unaware of any meaningful excess capacity related to 

delivery because “carriers generally handle all shapes simultaneously on the street, 

variations in flats volume would not automatically create situations” that allied with excess 

capacity. Id. Moreover, through a route adjustment process, variations in the volumes of all 

shapes would be handled over time to eliminate any mismatch between workload and 

hours. Subsequently, the Postal Service states that the concept of excess capacity relating to 

flats is irrelevant in the current delivery operating environment. Id. The operational expert 

the Commission consulted noted this might not be easily done during a short time (e.g., 2-3 

years), especially if volume continues to decline and the FSS is taken out of the mail 

processing operations.

While the Postal Service stated that it would be adjusting routes to eliminate any mismatch 

between workload and hours over time, the Commission’s operational expert noticed that 

removing FSS from all facilities may increase carrier office hours and the number of 

required routes. He also suggested that the Postal Service should continue the ongoing 

City-Route Inspections to ensure halting any workhours, vehicle, and equipment 

mismatches due to volume reduction.

2. Analysis of the Relationship Between Excess 

Capacity and Workhours in Flats Sorting 

Operations

The Postal Service specified that sharp and constant volume declines and invariant setup 

and breakdown activities to processed volume are reasons for the continued increase in 

flats mail processing cost. FY 2021 ACR at 20; FY 2021 ACD at 53.

When quantifying the effects of the volume trends and excess capacity on the Postal 

Service’s costs at the facility level, the Commission looked at the impact of these two factors 

on workhours spent during AFSM and FSS operations. These workhours represent time 

spent by labor while operating the machines, and it is reported in MODS as direct labor 

workhours on the specific machine. See Appendix A, Section IV.C. Analysis for details. In the 

Postal Service costing system, workhours recorded at the mail processing facilities and 

directly associated with FSS and AFSM operations are used to estimate the costs of these 

operations.305

305 See, e.g., Summary Description of USPS Development of Costs by Segments and Components, Fiscal Year 2021; Narrative Explanation of 

Econometric Demand Equations for Market Dominant Products Filed with Postal Regulatory Commission on January 20, 2022; Narrative, July 1, 

2022, folder “Summary Descriptions FY 2021,” folder “Summary Descriptions of FY 2021,” Word file “CS-03-21.docx,” at 3-3-3-4.
Docket No. SS2022-1 - 189 -

The results of the econometric analysis presented in Table IV-7, suggest that there is a 

strong positive relationship between workhours, on one side, and volume and excess 

capacity, on another side. For both AFSM and FSS, regression results indicate that 1 percent 

(1 unit) increase in volume corresponds with almost a proportional impact on workhours 

(i.e., they increase by approximately 1 percent as well). This is consistent with previous 

Commission findings.306 Similarly, a positive relationship exists between excess capacity 

and workhours, and this relationship is statistically significant. See Table IV-7. An increase 

in excess capacity results in increased workhours for AFSM and FSS flats operations. For 

instance, in the case of FSS, a 1 percent increase in excess capacity results in approximately 

1.2 percent increase in workhours. For AFSM, the impact of excess capacity on workhours 

is smaller: a 1 percent increase in excess capacity corresponds with a 0.36 percent increase 

in workhours.

307

The Commission concludes that a combined effect of declined volume and increased excess 

capacity corresponds with the increased costs of flats operations.

306 Docket No. RM2022-13, Order on Analytical Principles Used in Periodic Reporting (Proposal Six), November 3, 2022, at 11-12 (Order No. 

6322).

307 For interpretation of coefficients in regression models in different functional forms see e.g., Woodbridge Jeffrey M., Introductory 

Econometrics. A Modern Approach (5th Edition), 2013 at 44, available at https://jaimedv.com/eco/4c1-ecomet/jeffrey-m-wooldridge--

econometrics--book.pdf.
Docket No. SS2022-1 - 190 -

Table IV-7

Regression Results

Relationship Between Workhours, Volume, and Excess Capacity FY 2017-FY 2022

AFSM

lnWorkhours Coefficient Std. err. t P>t [95% conf. interval]

lnVolume 0.9927277 0.0258873 38.35 0.000 0.9419372 1.043518

Excess Capacity 0.3627038 0.1146985 3.16 0.001 0.1376677 0.5877399

example_cons -7.759188 0.4897082 -15.84 0.000 -8.719986 -6.798391

R-squared: Obs per group:

Within = 0.678 min = 194

Between = 0.5008 avg = 197.7

Overall = 0.6758 max = 199

F(2,1178) = 1240.07

corr(u_i, Xb) = -0.0741 Prob > F = 0.000

FSS

lnWorkhours Coefficient Std. err. t P>t [95% conf. interval]

lnVolume 1.07153 0.0371403 28.85 0.000 0.998364 1.144695

ExcessCap 1.208881 0.3284074 3.68 0.000 0.5619247 1.855838

_cons -9.80325 0.7786812 -12.59 0.000 -11.33724 -8.269263

R-squared: Obs per group:

Within = 0.7873 min = 33

Between = 0.8362 avg = 41

Overall = 0.7835 max = 43

F(2,238) = 440.35

corr(u_i, Xb) = -0.2028 Prob > F = 0.000
Docket No. SS2022-1 - 191 -

D. Effects of Different Operational Factors 

and Certain Investment Decisions on Flats 

Cost

1. Cost Impacts of Bundle Breakage

Figure IV-34 displays the total cost impact of broken bundles for each fiscal year. Total 

bundle breakage costs have increased during the last three consecutive fiscal years even 

though the total number of bundles has declined throughout this period. In FY 2022, 

bundle breakage costs accounted for 34 percent of all bundle processing costs. From FY 

2019 through FY 2022, bundle breakage cost the Postal Service $260 million cumulatively, 

which emphasizes the urgent need to reduce bundle breakage rates and, consequently, 

costs.

Figure IV-34

Annual Cost of Broken Bundles308

As discussed in Section III.C., bundle breakage is a significant cost to the Postal Service, 

which has been increasing every year since FY 2020. The Postal Service collects data on 

bundle breakage, but the dataset has several shortfalls. First, bundles without a FullService IMb are missing from the count of bundles processed. Second, bundles that are 

purposefully broken because they were viewed as on the verge of breaking as they are 

entering the bundle sorting system and bundles that broke before they were processed are 

308 Docket No. ACR2021, Library Reference USPS-FY21-45, folder “FY21.45.Files,” folder “e.9 Trend Narrative.PRC.LR.9 Update,” Excel file “CH 6 

Data and Tables FY 21. PRC.LR.9 Update.xlsx,” tab “Table VI-10 – Bundle Cost Impact.”

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2019 2020 2021 2022

Cost Impact (millions)

Fiscal Year
Docket No. SS2022-1 - 192 -

missing from the count of broken bundles. Third, the dataset does not identify where 

bundle breakage occurs. The Postal Service lacks ways to fully document breakage. In turn 

it lacks the ability to associate this data with specific mailers and provide this information 

to the mailers. Ultimately, it also lacks the ability to hold mailers financially accountable for 

ongoing poor bundle creation in order to offset the additional processing costs that result. 

With adequate data collection, the Postal Service could identify patterns of bundle 

breakage and work to mitigate it. Expanded use of MIA would notify mailers of mail 

preparation issues.

2. Impacts on Flats Transportation Costs

Between FY 2015 and FY 2022, the flats unit transportation costs increased by 57.1 percent 

and the associated volume transported to a DDU for delivery or to another mail processing 

unit for further sortation decreased by 34.4 percent.309 As shown in Figure IV-35, the 

upward trajectory of unit costs began in FY 2017.310 The Postal Service has attributed the 

increases in unit transportation costs to include more USPS Marketing Mail Flats being 

entered farther from their destinations.311 The Postal Services also credited the increases 

to overall surface transportation inflationary pressures together with sampling 

variation,312 and an increase in purchased surface transportation for First-Class Mail Flats 

due in part to a decrease in the capacity utilization of flats tubs.313 Additionally, the Postal 

Service ascribed the increases to transit failures exacerbated by the COVID-19 pandemic 

taking a toll on employee availability,314 and transportation capacity for all mails being 

greatly affected by the increases in e-commerce. Id. Among other policy measures the 

Postal Service undertook to respond to transportation unit cost increases were hiring new 

employees and converting non-career employees into career employees to address 

employee shortages. Id.

309 See Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45,” folder “FY22.45.Files,” folder “Rule 3050.50 Flats,” folder 

“Paragraph (e) – Pinch Point Reports,” folder “e.9 Trend Narrative.PRC.LR.9 Update,” Excel file “CH 6 Data and Tables 2022.PRC.LR.9 

Update.xlsx,” tab “Figure VI-10 Transportation.” First-Class Mail Flats, USPS Marketing Mail Carrier Route, USPS Marketing Mail Flats, USPS 

Marketing Mail High Density/Saturation Flats, Periodicals, and BPM Flats for each fiscal year are summed to calculate the costs and volumes.

310 Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY22-45,” folder “FY22.45.Files,” folder “Rule 3050.50 Flats,” folder 

“Paragraph (e) – Pinch Point Reports,” folder “e.9 Trend Narrative.PRC.LR.9 Update,” Excel file “CH 6 Data and Tables 2022.PRC.LR.9 

Update.xlsx,” tab “Figure VI-10 Transportation.

311 See Docket No. ACR2018, Responses of the United States Postal Service to Questions 1-5 of Chairman’s Information Request No. 22, 

question 5, March 13, 2019 (Docket No. ACR2018, Response to CHIR No. 22). See also Docket No. ACR2019, Library Reference PRC-LR-ACR2019-

9, March 25, 2020. The percent of USPS Marketing Mail Flats and Carrier Route entered at a DSCF decreased from 77.0 percent to 75.5 percent 

in FY 2019, and the percent of mail entered at origin increased from 12.0 percent to 12.7 percent from FY 2015 to FY 2019. Response to CHIR 

No. 22, question 5; Docket No. Library Reference PRC-LR-ACR2019-9.

312 Docket No. ACR2019, Library Reference USPS-FY19-45, December 27, 2019, folder “FY19.45.3050.50 Public Content,” folder “Paragraph (e) --

Pinch Point Reports,” folder “e.9 Trend Narrative.Chpt 6 Update,” PDF file “FY19.ACD.CHAPTER 6 UPDATE.pdf,” at 3.

313 Docket No. ACR2020, Responses of the United States Postal Service to Questions 1-30 of Chairman’s Information Request No. 5, question 

1.a., February 2, 2021.

314 FY 2022 Narrative at 6.
Docket No. SS2022-1 - 193 -

Figure IV-35

Flats Transportation Unit Costs FY 2015–FY 2022

3. Impact on Last Mile/Delivery Costs 

In-office and street time are the two components of the city career delivery operations.315

The unit costs for city carrier in-office processing (casing) increased by 47.1 percent from 

FY 2008 to FY 2022. Comparatively, the same unit costs increased by 35.1 percent from FY 

2015 to FY 2022 as shown in Figure IV-36.316 The Postal Service spent a total of $3.7 billion 

on delivery costs for flats in FY 2022, equivalent to 16.9 cents per piece.317 The Postal 

Service spent a total of $1.1 billion on city carrier in-office costs in FY 2022, including the 

casing costs for flats. See FY22 Delivery. When the additional mail processing costs 

315 Docket No. RM2015-7, Order Approving Analytical Principles Used in Periodic Reporting (Proposal Thirteen), October 29, 2015 (Order No. 

2792). See also FY 2015 ACD at 177. The in-office time reflects the costs the city carriers incur while casing, and the street time reflects the costs 

the city carriers incur while delivering the mail. Id. at 6 n.9. City carriers delivered 67.7 percent of all flats and accounted for about 66.4 percent 

of delivery costs in FY 2022, and rural carriers delivered 32.3 percent and accounted for about 33.6 percent of the delivery costs in the fiscal 

year. The total flats delivered in the fiscal year were 20,892,071, and the rural carriers delivered about 6,737,731 of the totals. The total costs of 

flats delivery in the fiscal year amounted to $3,002,622, and the costs for rural flats delivery amounted to $1,009,115. See Docket No. ACR2022, 

Library Reference USPS-FY22-19, FY 2022 Delivery Costs by Shape, December 29, 2022, folder “USPS-FY22-19,” folder “Delivery Model Files,” 

Excel file “UDCInputs.xlsx,” tabs “RuralVols” and “RPWShape,” column “Flats.” See also Docket No. ACR2022, Library Reference USPS-FY22-2, 

Excel file “FY22Public Cost Segs and Comps.xlsx,” tabs “CS06,” “CS07,” and “CS10.”

316 See Docket No. ACR2022, Library Reference USPS-FY22-45, December 29, 2022, zip folder “USPS-FY21-45.zip,” zip folder “FY21.45.Files.zip,” 

folder “Rule 3050.50 Flats,” folder “Paragraph (e) – Pinch Point Reports,” folder “e.9 Trend Narrative.PRC.LR.9 Update,” Excel file “CH 6 Data 

and Tables 2022.PRC.LR.9 Update.xlsx,” tab “Figure VI-11 Delivery” (FY22 Delivery).

317 See Docket No. ACR2022, Library Reference USPS-FY22-45, December 29, 2022, zip folder “USPS-FY21-45.zip,” zip folder “FY21.45.Files.zip,” 

folder “Rule 3050.50 Flats,” folder “Paragraph (b) – Financial Report,” Excel file “FY22.Rule.3050.50.Para.B.xlsx,” tab “Item b2” (FY22 Financial 

Report B2). See also Docket No. ACR2022, Library Reference USPS-FY22-24, December 29, 2022, folder “USPS-FY22-24,” Excel file 

“FY22Public.PB,” tabs “CityCarriers” and “Rural;” Docket No. ACR2022, Library Reference USPS-FY22-1, FY 2022 Public Cost and Revenue 

Analysis (PCRA) Report, December 29, 2022, file “Public_FY22CRAReport.xlsx,” tab “Volume1.”

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FY 2015 FY 2016 FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Unit Transportation Cost

Fiscal Year

2015 2016 2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 194 -

associated with the FSS are added to the city carrier in-office costs,318 the Postal Service 

spent over $1.24 billion processing flats to DPS in FY 2022. This is a 4.3 percent decrease in 

costs from FY 2021 when the Postal Service spent $1.30 billion on processing flats to 

DPS.319 Nevertheless, this is only slightly less than the amount spent casing flats in FY 2008 

when volume was more than double the FY 2022 volume.320 The Postal Service had to case 

all flats manually in FY 2008 because there were no FSS machines. Despite the addition of 

several FSS machines and volume declining by 54.1 percent between FY 2008 and FY 

2023,321 the Postal Service has only been able to reduce the cost of final sortation operation 

for flats by 24.4 percent.322

Figure IV-36

City Delivery Carriers – Office Activity

Unit Costs, FY 2015–FY 2022

318 Id. The cost segment 6 In-Office cost for flats in FY 2022 was $1.109 billion. Id. The mail processing cost for the FSS was $130 million. See

Docket No. ACR2022, Library Reference USPS-FY22-45, folder “USPS-FY2245,” folder “FY22.45.Files,” folder “Rule 3050.50 Flats,” folder 

“Paragraph (b) – Financial Report,” Excel file “FY22.Rule.3050.50.Para.B.xlsx,” tab “Item b6.”

319 Id. The unit cost of processing flats to DPS in FY 2022 was 6.7 cents per piece, and 6.4 cents per piece in FY 2021. See Docket No. ACR2022, 

Library Reference USPS-FY22-45, folder “USPS-FY21-45,” folder “FY21.45.Files,” folder “Rule 3050.50 Flats,” folder “Paragraph (e) – Pinch Point 

Reports,” folder “e.9 Trend Narrative.PRC.LR.9 Update,” Excel file “CH 6 Data and Tables 2022.PRC.LR.9 Update.xlsx,” tab “Figure VI-12 FSS.”

320 See FY22 Delivery. The cost segment 6 In-Office cost for flats in FY 2008 was $1.641 billion, $401 million more than the combined FSS mail 

processing and in-office cost of $1.240 billion in FY 2022. The flats volume was 47.94 billion pieces in FY 2008 and declined to 21.99 billion 

pieces in FY 2022, representing a 54.1 percent decline. Id.

321 Id.

322 The cost segment 6 In-Office cost for flats in FY 2008 was $1.641 and the cost of processing flats to DPS in FY 2022 was $1.240. Id.

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 $0.060

FY 2015 FY 2016 FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022

Unit Delivery Cost

Fiscal Year

2015 2016 2017 2018 2019 2020 2021 2022
Docket No. SS2022-1 - 195 -

4. History of FSS Operations and Potential Impact 

of FSS Decommissioning on Flats Costs

In October 2006, the Postal Service invested $1.49 billion to develop, purchase, and deploy 

100 flats sequence sorting machines at 33 sites. OIG Report No. SM-WP-15-001 at 8. The 

FSS was a strategic initiative implemented to increase the percentage of flat-shaped mail in 

delivery point sequence.323 This initiative focused on reducing carrier sortation and 

associated costs through automated processing of flats into delivery point sequence. The 

goal of the FSS was to replicate for flats the benefits achieved by letter sequencing, which 

would have improved service and financial performance of flats. Id. at 51. 

Due to the reduction in flats volume and the FSS failing to meet key performance 

requirements, the deployment of the FSS was more limited than originally envisioned. OIG 

Report No. SM-WP-15-001 at 8. Furthermore, FSS operations did not have the intended 

effect on improving cost or service.

In the FY 2021 ACD, the Commission noted continuous and persistent increases in flats 

costs. FY 2021 ACD at 228. The Commission also highlighted the trend of declining 

performance for the FSS. Id. at 250-51. In FY 2015, only 82 percent of flats which 

destinated in FSS zones were sorted to DPS. FY 2015 ACD at 170. By FY 2021, only 66 

percent of flats were sorted to DPS. FY 2021 ACD at 250.

The Postal Service implemented several initiatives aimed at improving FSS performance, 

including monitoring it through the FSS Scorecard, creating self-audit checklists for 

facilities, and deploying certain software enhancements to address sort logic and improve 

handling of barcoded items. FY 2019 ACD at 167. In FY 2021, the initiatives designed to 

improve FSS processing included removing excess FSS machines. FY 2021 ACD at 251.

Finding it no longer cost-effective to continue FSS processing due to declines in flats 

volume and changes in “mailer make-up,” the Postal Service stated that FSS processing 

would be discontinued in FY 2023.324

Since FSS decommissioning will impact mail processing at both mail processing facilities 

and DDUs, as well transportation schedules, and delivery operations, it will impact costs 

the Postal Service incurs on these operations. Given the plan to complete the

decommissioning of FSS in FY 2023, it is likely that costs for certain operations will 

increase immediately following the decommissioning. The Postal Service will need to 

restructure operations at the destination mail processing centers by shifting volumes from 

the eliminated FSS to AFSMs. The flats that cannot be sorted to carrier route on the AFSM 

and go through the manual sortation, will likely shift to DDUs. DDUs might need to expand 

323 Docket No. ACR2010, Library Reference USPS-FY10-17, 2010 Comprehensive Statement on Postal Operations, December 29, 2010, at 53.

324 Docket No. ACR2022, Library Reference USPS-FY22-45, folder “FY22.45.Files,” folder “Rule 3050.50 Flats,” “Paragraph (f) -- Operational 

Changes Report,” PDF file “FY22 Paragraph (f) Flats Operational Initiatives Report.pdf,” at 4-5.
Docket No. SS2022-1 - 196 -

their operations to include additional sortation and bundle distribution operations. The 

additional office time that carriers will spend manually casing flats previously sorted to 

DPS will force a reduction in street time to keep routes within an 8-hour timeframe. This 

will result in a change to route structure.

Mail processing costs. The removal of FSS equipment will eliminate costs associated with 

the scheduled and unscheduled maintenance of this equipment. Management at the Postal 

Service facilities visited by Commission staff explained that FSS equipment received 4 

hours of preventive maintenance daily. The Postal Service stated it saved $2.8 million in 

FSS maintenance in just two months (October through November 2022), and it planned to 

save $23.4 million in maintenance “by the end of FY 2022.” Response to CHIR No. 7, 

question 4.b. The Postal Service added it had removed 93 of the 100 FSS machines 

originally installed, as of January 26, 2023, the date of the filing of its Response to CHIR No. 

7. Id.

The discussions with staff at mail processing facilities suggested the Postal Service made 

facility-specific projections for increases in flats volumes that would be processed on the 

AFSM equipment and which were previously sorted on the FSS equipment. Staff also 

commented that these projections were based on an assumed shift in mailers’ presorting of 

flats to carrier route bundles, which would not need sorting at mail processing facilities and 

would be cross docked to DDUs. The Postal Service confirmed this expectation and clarified 

that to require no handling at mail processing facilities, carrier route bundles would need 

to be entered on carrier route or 5-Digit pallets.325 The Commission is not able to project 

changes in flats presort levels by mailers, and the associated impact on mail processing 

workload and costs at impacted facilities.

The discussion that follows reflects the operational expert’s high-level views of the impact 

that the decommissioning of the FSS will have on flats operations and costs following FSS 

shutdown.

According to the operational expert the Commission consulted, there will be a direct 

impact on DDUs associated with the distribution of both Carrier Route and Enhanced 

Sequence bundles to their specific routes. Flats from these bundles were previously 

processed on FSS and then sent in containers to DDUs, where they were directly handled 

by carriers. As such, the Postal Service incurred minimal in-office delivery costs for these 

flats when they were sorted on FSS, and the costs associated with these pieces will likely 

increase when the FSS is decommissioned.

Transportation costs. The Commission anticipates reduction in costs associated with 

transportation of FSS flats. This would include elimination of certain transportation 

dedicated to moving flats sorted on FSS equipment, such as transportation from mail 

processing facilities to DDUs and transportation of flats between facilities operating FSS 

equipment to facilities operating AFSM equipment. See Section III.B.4.d.

325 Response to CHIR No. 2, question 3.d.; Response to CHIR No. 3, question 5.e.; Response to CHIR No. 7, question 1.b.
Docket No. SS2022-1 - 197 -

However, while the Postal Service expressed hope FSS decommissioning would reduce 

trips from plants to delivery units,326 it also suggested it would “reevaluate transportation 

from plants to delivery units at former FSS sites in FY 2023.” Response to CHIR No. 3, 

question 5.e. Therefore, there is an uncertainty regarding the cost impact of FSS 

decommissioning on transportation operations.

Delivery costs. When FSS processing is discontinued, delivery costs associated with manual 

casing of flats that were previously sorted to DPS and required no casing, will increase. The 

operational expert the Commission consulted explained that due to the increased casing 

workload, the routes will need to be inspected and restructured. The expert clarified the 

process for accomplishing this is somewhat different for city and rural carrier routes, due 

to different methods in the bargaining agreements with the two unions that represent city 

and rural carrier employees. The operational expert concluded that while there are some 

differences in route evaluation processes between city and rural carrier routes, the impacts 

of FSS decommissioning on delivery costs associated with city and rural carrier routes will 

be similar.

The first challenge for the Postal Service might be on management/supervisor staffing 

required to conduct these inspections/evaluations. The operational expert provided 

additional details on what the route evaluation process would entail. Specifically, the 

expert commented that, as was the case when FSS was first implemented, dedicated teams 

of managers and supervisors would need to be created. The process would require welltrained staff and be time consuming. This process could not be absorbed by the existing 

staff of managers and supervisors, nor could these activities be absorbed during the 

current workday. The teams formed would have to come from top quality managers and 

supervisors from DDUs. In turn, it would be necessary to backfill these positions with 

temporary management and supervisory staff. To the maximum extent possible, the Postal 

Service will need to draw this staff from non-FSS DDUs. However, non-FSS DDUs’ staff may 

not have the appropriate level of experience. The result might be an added strain on 

staffing at the Postal Service facilities and an increase in associated costs.

Another challenge the elimination of FSS will impose on the Postal Service operations will 

be a shift of workload from mail processing operations performed at mail processing 

facilities to DDUs. This shift in workload will increase the time carriers will spend on inoffice activities and reduce the time available for street delivery. Because carriers must 

keep routes within an 8-hour schedule, this change will require a creation of new, shorter 

routes with reduced street time, to offset the increase in office time. The basic issue is to 

keep routes within an 8-hour schedule.

The restructuring of routes will clearly impact the Postal Service’s delivery and mail 

processing operations. It will also impact mailers, who will need to adjust the bundle 

preparation to reflect the restructured carrier routes. Mailers are generally provided an 

allowance period to make the transition to the new route structures. During that period of 

326 Response to CHIR No. 7, question 1.b.
Docket No. SS2022-1 - 198 -

time, and for each delivery zone undergoing a change, the Postal Service will receive presorted bundles from mailers that will require manual sortation by clerks. However, mailers 

will still receive the discounts that would apply if their pre-sorted bundles were sorted on 

automated equipment, and the Postal Service will not receive the full savings benefit of 

proper presort.

5. Potential Changes in Flats Operations and Costs 

Due to Sorting and Delivery Centers

a. Background

The Postal Service is in the early stages of rolling out a plan to move and aggregate certain 

delivery units, which currently mostly operate out of post offices, into larger facilities called 

Sorting and Delivery Centers (S&DCs).327 S&DCs will mostly be using existing space in 

P&DCs and other existing facilities, including Processing and Distribution Facilities and 

main offices.328 The Postal Service also plans to build new facilities in metro areas to house 

the S&DCs, some of which will also house Regional Distribution Centers (RDCs). Id.

The purpose of the S&DCs is to “reduce transportation and mail handling costs”329 by 

aggregating delivery units into "larger Sort and Delivery Centers with adequate space, 

docks and material handling equipment to operate more efficiently.”330 According to an 

issue of The Eagle, a Postal Service magazine targeted to its employees, the daily operating 

function of the S&DC will be essentially the same as a Destination Delivery Unit (DDU), 

“except on a larger scale and with much greater efficiency, operational reliability and 

staffing flexibility.”331 Where a metropolitan area might today be served by 80 small 

delivery units, these carrier operations will be served by four or five larger facilities. Id. at 

10. See Figure IV-37 for an illustrative example. Moving delivery units from post offices to 

S&DCs means that instead of delivery routes starting and ending at post offices after being 

transported there from P&DCs, delivery routes will start directly from large S&DCs.

327 The Athens location was opened mid-November 2022 after some delay. The updated schedule in a USPS letter to the National Association of 

Postal Supervisors sets out to convert another 17 “spoke offices” (post offices and other facilities that currently house delivery units) to five 

additional S&DCs by in February 2023. See Letter to Ivan D. Butts, President, National Association of Postal Supervisors from James Lloyd, 

Director, Labor Relations Policies and Programs, December 5, 2022, available at 

https://naps.org/files/galleries/Updated_Schedule_for_Implementation_of_S_DC_Sites_and_Spoke_Offices_Lloyd_12_2_2022.pdf. In total, the 

Postal Service plans to consolidate delivery operations at more than 200 post offices and other facilities. See United States Postal Service, Office 

of Inspector General, Upcoming Audit Work, available at https://www.uspsoig.gov/reports/upcoming-audit-work?page=1.

328 Sorting & Delivery Center presentation by USPS, July 29, 2022, https://www.unitedpma.org/docs/default-source/default-documentlibrary/resources/sdc---dpmg-management-association-update_07.29.2022.pdf.

329 See Letter to Edmund A. Carley, National President, United Postmasters and Managers of America from James Lloyd, Director, Labor 

Relations Policies and Programs, July 29, 2022, available at https://www.unitedpma.org/docs/default-source/default-documentlibrary/resources/notification-0729202246b67af2-353b-48a5-9ca8-87cf43e95d81.pdf?sfvrsn=6055688d_3.

330 See The Eagle Magazine, Volume 1, Issue 4, July 2022, at 11, available at https://about.usps.com/resources/eaglemag/em20220802.pdf.

331 See The Eagle Magazine, Volume 2, Issue 2, February 2023, at 11, available at https://about.usps.com/resources/eaglemag/em20230131.pdf.
Docket No. SS2022-1 - 199 -

Figure IV-37332

Illustrative Example of Planned Network Change

b. Potential Changes to Flats Operations and Costs

While there is not much detailed information yet on how these new S&DCs will reduce 

transportation and mail handling costs, the Commission anticipates it will affect the major 

functional cost categories of flats products in the following ways.

Mail processing. The effect on the Flats operations will heavily depend on which delivery 

units are being aggregated. For example, if the carriers at the selected delivery units are 

currently preparing large volumes of flats products, these costs would then be shifted and 

aggregated to an S&DC, which could potentially be more efficient because of economies of 

scale.333 However, given the elimination of FSS, it is unlikely many additional processing 

windows will be available. As a result, cost savings due to economies of scale may not be

significant.334

Delivery. One presentation from the Postal Service estimated a 5 to 10 percent increase in 

the number of routes required.335 This appears to be due to longer distances traveled 

between the S&DC and the start and end points of a delivery route, which will increase the 

time needed to complete a route. These routes will need to be shortened to accommodate 

any delivery time restrictions, so more routes will need to be added. Based on current 

information, the Commission anticipates costs related to delivery activities to increase. InOffice costs, which currently includes mail preparation at delivery units, may see 

improvements if mail processing becomes more efficient at the S&DCs. However, as 

discussed above, much of the improvements in mail processing will already be realized due 

to the elimination of FSS.

332 Louis DeJoy, Postmaster General, United States Postal Service, Keynote Address at 2022 National Postal Forum, May 16, 2022, at 24:30, 

25:05, available at https://about.usps.com/video/NPF2022Keynote.mp4.

333 Currently, mail preparation by city carriers is considered “In-Office Direct Labor.” See Section IV.B.2. for more details about this cost 

component.

334 With the elimination of FSS, the only operation of benefit that can be performed will be Carrier Route on an AFSM. Given the elimination of 

FSS, a significant amount of Carrier Route volumes will already have to be shifted to AFSM.

335 United States Postal Service, Sorting & Delivery Center (S&DC), July 29, 2022, available at http://www.savethepostoffice.com/wpcontent/uploads/2022/08/SDC-DPMG-Management-Association-Update_07.29.2022.pdf.
Docket No. SS2022-1 - 200 -

Purchased transportation. Since delivery routes will start and end at S&DCs, this eliminates 

the need for transportation from P&DCs to individual delivery units at post offices and 

other facilities. In addition, many of these S&DCs will be co-located with P&DCs or RDCs, so 

transportation costs to S&DCs may be significantly less than to DDUs.

E. Impact of Methodological Changes on Unit 

Attributable Cost

1. Introduction

The Postal Service calculates unit attributable costs for its products in each year. However, 

comparing unit attributable costs over time presents additional challenges. This is 

especially true in cases where the Postal Service has modified the methodology it employs 

to estimate costs, as it risks conflating changes due to cost measurement changes with 

those due to other factors, such as improvements in operations. This makes the 

construction of a useful time series problematic.

This section identifies changes to cost measurement methodologies that render 

comparisons of the unit attributable costs of certain products over time difficult and 

suggests methods that will partly overcome the difficulties and produce a useful time 

series. In particular, this section identifies the impact methodological changes exercise on 

the unit attributable costs of flats products.

To analyze flats unit attributable costs as a time series, it would be ideal to remove the 

impact of cost methodology changes on each product’s cost in each fiscal year. Fortunately, 

there is information available on the impacts of costing methodology changes, so that it is 

possible to produce such a time series, one that does not vary dramatically from the unit 

attributable costs filed in the relevant CRA. The resulting time series can be used to cast 

some light on the recent history of flats costs, but great care should be taken in using the 

series, as it embodies significant assumptions, as described in the Appendix A, Section IV.E. 

Analysis.

These time series of costs will differ from the CRA unit attributable costs not only because 

they account for changes in cost methodology, but also because they address the impact of 

the overall price level over the period. For that reason, the time series of costs for flats 

products include an adjustment for inflation, with annual costs expressed in terms of FY 

2022 prices. Section IV.E.2. presents the flats-shaped unit attributable cost time series from 

2008 to FY 2022, adjusted for both methodological changes and inflation.336 Issues and 

concerns over the use of such a time series of flats unit attributable costs are included in 

the Appendix A, Section IV.E. Analysis.

336 This inflation adjustment uses fiscal-year CPI-U. See United States Bureau of Labor Statistics, www.bls.gov.
Docket No. SS2022-1 - 201 -

2. Costing Methodology Impacts on Flats Unit 

Attributable Cost

The Postal Service has proposed numerous changes to analytical principles (methodology 

changes) over the past decade and a half, most of which have been affirmed by the 

Commission because these changes have improved the quality and accuracy of the data or 

analysis. The Postal Service petitions the Commission to open a rulemaking docket for 

specific changes. Interested parties may comment and reply to each other’s comments; but 

ultimately the Commission rules on the proposal. The subset of rulemaking dockets with an 

impact on unit flats costs is shown in Table IV-8, along with a brief description of each 

methodology change.
Docket No. SS2022-1 - 202 -

Table IV-8

Methodology Changes with Impacts on Flats Products Costs

Rulemaking Docket No. Description Date Affirmed

RM2022-13 Peak Season Transportation Costs 11/3/2022

RM2021-1 Change in Estimation of Highway Costs 10/6/2021

RM2021-7 Replace Manual data collection for SPR with 

PTR and TACS

9/30/2021

RM2020-10 IOCS Cluster Sampling Using TACS 9/25/2020

RM2020-1 Update method for estimating facility-related 

costs

8/17/2020

RM2020-7 New Methodology for City Carrier Delivery 

Time

6/9/2020

RM2019-6 Update and Improve Methodology for 

Calculating SPR Cost Estimation

1/14/2020

RM2018-5 IOCS Street and Office Time Definitions 1/8/2019

RM2018-10 Reorganize C/S 3 and Change some Mail 

Processing Cost Pools

10/12/2018

RM2018-4 Methodology changes in RCCS data collection 

procedures - digital images

7/13/2018

RM2016-12 New Method for Highway Variabilities 

Estimation

6/22/2017

RM2016-3 Attribution of the Cost of Vehicles used on 

City Carrier Routes.

12/22/2015

RM2015-19 Merge C/S 3 and 4 - CAG K and L Post Offices 

w/CAG A-J Post offices

11/24/2015

RM2015-5 Methodology for Customer Care Center costs 11/19/2015

RM2015-7 Update City Carrier Street Time Model- for 

C/S 7

10/29/2015

RM2012-5 New method for VSD cost measurement 

based on TRACS-VSD C/S 8

9/10/2012

RM2010-1 Updated Density Factors for C/S 14 and C/S 8 1/14/2010

RM2009-10 New Items for Inclusion Rural Evaluation 

Factors

11/13/2009

RM2009-10 Distribution of MVS costs - correction 

erroneous distribution key

11/13/2009

RM2009-10 Distribution of SPR Costs C/S 7 11/13/2009

RM2009-10 Accrued Costs of Loading/Unloading Vehicle 11/13/2009
Docket No. SS2022-1 - 203 -

Table IV-9 shows the predicted cost impact of each methodology change on the unit 

attributable cost of flats products in the fiscal year the methodology changes was 

implemented.337 The unit attributable cost changes are those that result from the change in 

costing methodology in a given fiscal year.338

337 This report refers to the impact of the methodology change in the year it was implemented as “local” to distinguish them from the “global” 

impact of methodology changes on unit costs (i.e., when local impacts are applied to all relevant years).

338 The analysis makes use of the unit attributable cost changes shown in the petition. Otherwise, the cost change is divided by Revenue, Pieces, 

and Weight to obtain unit attributable cost changes.
Docket No. SS2022-1 - 204 -

Table IV-9

Local Impacts (in Dollars) on Flats Products Costs from Methodology Changes

First-Class 

Mail Flats

High 

Density 

and 

Saturation 

Flats and 

Parcels

Carrier 

Route Flats

USPS 

Marketing 

Mail Flats

Every Door 

Direct 

Mail--

Retail

Periodicals

Bound 

Printed 

Matter 

Flats

RM2022-13 -0.0365 -0.0003 -0.0028 -0.0162 0.0000 -0.0072 -0.0132

RM2021-1 0.0132 0.0001 0.0008 0.0025 0.0000 0.0023 0.0030

RM2021-7 -0.0003 0.0000 0.0000 -0.0001 0.0000 -0.0002 -0.0016

RM2020-10 -0.0037 0.0050 0.0174 -0.0207 0.0054 0.0284 0.0577

RM2020-1 0.0011 0.0004 -0.0004 0.0010 0.0003 0.0003 -0.0030

RM2020-7 -0.0110 -0.0120 -0.0070 -0.0050 -0.0090 -0.0050 -0.0030

RM2019-6 0.0050 -0.0002 -0.0010 -0.0021 -0.0002 -0.0009 -0.0004

RM2018-5 0.0023 0.0063 0.0115 -0.0217 0.0064 0.0183 0.0684

RM2018-10 0.0091 0.0000 0.0005 -0.0001 -0.0002 0.0050 0.0022

RM2018-4 0.0000 0.0000 -0.0001 0.0000 0.0000 0.0000 0.0000

RM2016-12 -0.0156 -0.0004 -0.0012 -0.0058 0.0000 -0.0065 -0.0172

RM2016-3 0.0015 0.0021 0.0018 0.0019 0.0018 0.0016 0.0015

RM2015-19 -0.0001 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001

RM2015-5 0.0006 0.0000 0.0000 0.0000 0.0000 0.0000 0.0011

RM2015-7 -0.0113 0.0212 0.0088 0.0077 0.0182 0.0060 -0.0016

RM2012-5 0.0050 0.0000 0.0010 0.0010 0.0000 0.0010 -0.0060

RM2010-1 -0.0020 0.0000 0.0000 0.0000 0.0000 0.0000 -0.0190

RM2009-10 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 -0.0015

RM2009-10 0.0023 0.0004 0.0010 0.0018 0.0000 0.0013 0.0012

RM2009-10 -0.0001 -0.0001 -0.0001 -0.0001 0.0000 -0.0004 -0.0492

RM2009-10 -0.0013 -0.0017 -0.0022 -0.0020 0.0000 -0.0021 -0.0024
Docket No. SS2022-1 - 205 -

An example of a methodology change that had an impact on the unit attributable cost of 

flat-shaped products is the changes the Postal Service made to the In-Office Cost System 

(IOCS) sampling method in FY 2020. In September 2020, the Commission affirmed the 

Postal Service’s Proposal Three (Docket No. RM2020-10) to modify the sampling method 

for IOCS.339 The new sampling method would utilize census data from the Time and 

Attendance Collection System to take on-site readings while the carriers are still in the 

office. This enables the collection of more on-site readings, considered more accurate than 

telephone readings taken after the carrier leaves for the street.340

The impact of this proposal on flats unit attributable costs is significant. The Postal Service 

estimated the FY 2020 unit cost of First-Class Mail Flats would fall by 0.37 cents and the 

unit cost of USPS Marketing Mail Flats would fall by 2.07 cents, while other flats products 

unit cost would rise: for High Density and Saturation Flats and Parcels by 0.5 cents, for 

EDDM-R by 0.54 cents, for Carrier Route by 1.74 cents, for Periodicals by 2.84 cents, and for 

BPM by 5.77 cents (see Table IV-9, row 4).

As a second example of a cost methodology change with impacts on flats products, Proposal 

Two in Docket No. RM2020-7 updated city carrier delivery variabilities.341 The Commission 

affirmed the Postal Service’s proposed methodology changes in this docket on July 9, 

2020.342 In its proposal, the Postal Service introduced a new method for estimating delivery 

unit costs, which would be updated each year. Prior to this methodological change, the 

variability was calculated from the study data set. However, by utilizing the total average 

letter and flat delivered volume for this task, it became possible to update the delivery 

variabilities each year. This change had the effect of lowering the unit attributable costs of 

the flats products, as illustrated by the impact of the change on the Marketing Mail High 

Density and Saturation Flats and Parcels product (see Table IV-9, row 6).

Adjusting unit attributable costs by accounting for methodology changes is heavily reliant 

on the Postal Service’s prediction of the impact of the methodology change on a single 

year.343 See Appendix A, Section IV.E. Analysis for more discussion on assumptions used in 

the Commission’s analysis.

Another important consideration with regard to a time series of unit attributable costs 

stems from the fact that each methodology change in the unit attributable costs for the 

current fiscal year implies a change in all of the unit attributable cost estimates preceding 

339 Docket No. RM2020-10, Order on Analytical Principles Used in Periodic Reporting (Proposal Three), September 25, 2020 (Order No. 5697).

340 Since it may be that telephone readings tend to raise the cost of First-Class Single-Piece Letters, the impact of the change to the IOCS 

sampling method would be expected to lower the cost of Single-Piece Letters and raise costs for presorted products. Indeed, the Postal 

Service’s estimate of the impact reflects this effect.

341 Docket No. RM2020-7, Petition of the United States Postal Service for the Initiation of a Proceeding to Consider Proposed Changes in 

Analytical Principles (Proposal Two), April 7, 2020 (Docket No. RM2020-7, Petition).

342 Docket No. RM2020-7, Order on Analytical Principles Used in Periodic Reporting (Proposal Two), July 9, 2020 (Order No. 5583).

343 In addition to changes to cost methodology, the Postal Service makes changes to the products it delivers. Two such changes are discussed in 

the Appendix A, Section IV.E. Analysis and assumed to have no impact on the costs of flats products.
Docket No. SS2022-1 - 206 -

the current year, stretching back to the beginning of the period over which the desired time 

series extends. This is because costing methodology changes are generally proposed to 

improve the accuracy of the cost measurement. As seen in Appendix A, Section IV.E. 

Analysis, the accuracy of the analysis depends on the validity of the assumptions, and 

therefore there is no verifiably accurate method of making the overall adjustments.344

To produce a time series that has comparable unit attributable costs across years, the 

impacts of the methodology changes in Table IV-9 are applied to the unit attributable costs 

of flats products in all fiscal years prior to the fiscal year of its affirmation.345 An additional 

adjustment is then made for inflation. Figure IV-38 and Figure IV-39 present the 

unadjusted and adjusted time series from FY 2008 to FY 2022 for flats products that were 

non-compensatory and compensatory in FY 2021.

344 As new or improved data become available, a new methodology may become a possibility. However, and for reasons discussed above, a cost 

impact predicted for the current year, possibly because of the availability of new data, will require adjustments in all previous years. Hence a 

time series of unit attributable costs in this year will be different from the time series conducted in future years, after more changes to costing 

methodologies have taken place. A possible exception would be those changes in cost that are reflective of operational changes in the current 

year. In that case, the unit attributable cost of the previous years may arguably not need any adjustment based on cost changes in the current 

year. In that case, a part of the work of constructing a time series would be to disentangle impacts tied to operational changes and those 

proposed as corrections to erroneous past costing methodologies. That will be a difficult task, as proposed changes brought forward in the 

Commission rulemaking dockets are typically discussed by the USPS as stemming from both sources: a desire to improve a costing methodology 

and a desire to keep the cost measurement in line with changes in operations. See Appendix A, Section IV.E. Analysis for further discussion.

345 More discussion is provided in the Appendix A, Section IV.E. regarding the procedure and assumptions required to do this.
Docket No. SS2022-1 - 207 -

Figure IV-38

Unadjusted and Adjusted Unit Attributable Costs of Non-Compensatory Flats Products

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars) 

Fiscal Year

Unadjusted First-Class Mail Flats Real Adjusted First-Class Mail Flats

Unadjusted Carrier Route Real Adjusted Carrier Route

Unadjusted Marketing Mail Flats Real Adjusted Marketing Mail Flats

Unadjusted Periodicals Real Adjusted Periodicals
Docket No. SS2022-1 - 208 -

Figure IV-39

Unadjusted and Adjusted Unit Attributable Costs for Compensatory Flats Products

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

Unadjusted HDS Flats and Parcels Real Adjusted HDS Flats and Parcels

Unadjusted EDDM-R Real Adjusted EDDM-R

Unadjusted BPM Flats Real Adjusted BPM Flats
Docket No. SS2022-1 - 209 -

CHAPTER V. SUMMARY OF 

CONCLUSIONS

This study identifies the causes of inefficiencies in the collection, sorting, transportation, 

and delivery of flats. In addition, the study quantifies the effects of the volume trends, 

investment decisions, excess capacity, and operational inefficiencies of the Postal Service 

on costs that are attributable to flats.

The principal findings of this study are as follows:

• In FY 2022, the cost coverage (revenue divided by attributable cost) for all flats 

products increased. However, unit attributable costs also increased for the majority 

of flats products.

• Since FY 2010, the total volume of all flats products has decreased by 43.4 percent 

or an average of 4.6 percent annually.

• Six pinch points continue to contribute to cost and service issues for flats: 

(1) bundle processing; (2) automated processing; (3) manual sorting; (4) allied 

operations; (5) transportation; and (6) last mile/delivery.

• Reported bundle breakage rates likely underestimate true bundle breakage because 

only bundles that break on bundle sorters are reported. However, bundles break, or 

are treated as if they will break, during other processing stages.

• Bundle breakage often results in inefficient manual processing of individual flats.

• How bundles are prepared and presented to the Postal Service significantly impacts 

bundle breakage rates. Better coordination between the Postal Service and mailers 

is necessary to improve bundle integrity.

• Due to the lack of machine counts and clocking errors, measurement of both 

workhours and volumes in manual flats sorting are unreliable. The lack of reliable 

volume or workhour data represents a tremendous loss of opportunity to track or 

use this data in any meaningful way.

• Lack of relevant data prevents effective communication between mailers, facility 

staff, and Postal Service Headquarters, inhibiting corrective action.

• Insufficient data, coupled with data quality issues, makes it difficult to assess the 

Postal Service’s ability to improve flats processing efficiency.

• The Postal Service does not always understand the sources of flats processing 

inefficiencies or track volumes that cause inefficient operations.

• Recent operational plans, such as decommissioning FSS machines and the creation 

of S&DCs, will likely impact flats costs.
Docket No. SS2022-1 - 210 -

The PSRA requires the Postal Service, within 6 months, either to develop and implement a 

plan to remedy each inefficiency identified in the study or else to provide an explanation as 

to why remedying such inefficiency is impracticable. Based on the findings of the study, the 

Commission provides the following suggestions to the Postal Service for consideration as it 

develops its plan. Specifically, the Postal Service should consider:

• Continuing the combination of increasing revenue and reducing costs until unit 

revenue exceeds unit attributable cost for each non-compensatory flats product.

• Continuing to study the causes, impacts, and ways to reduce bundle breakage; 

enhancing the reporting and tracking of bundle irregularities; and working with 

mailers to ensure corrective actions are implemented when irregularities are 

shared.

• Further assessing the quality of its data, particularly as it relates to volume, 

workhours, and productivity, and exploring cost effective ways to improve that 

quality.

• Implementing initiatives to reduce mail processing costs.

• Identifying mail processing facilities with extreme (unusually high or low) 

productivity values and those with quarterly productivity values based on a large 

number of missing workhours or volume; targeting those sites to improve their 

reporting or explaining why the provided productivity is accurate for a given 

facility.

• Developing an accurate method to track flat-shaped mail that is manually processed. 

Once there is an accurate measurement of such flat-shaped mail, the Postal Service 

should consider developing a specific plan to: (1) continue to decrease the quantity 

of flat-shaped mailpieces processed manually, and (2) achieve a proportional 

reduction in unit mail processing costs for manual operations.

• Including in its plan specific, achievable goals to reduce costs associated with allied 

operations, transportation, and delivery of flats.

• Quantifying the impact of any initiatives on costs to ensure its efforts are effective.

The Commission will continue to work with the Postal Service and the postal community to 

address these challenges.
Docket No. SS2022-1 Appendix A

 Page 1 of 36

Appendix A: Flats Study Report Analysis

Sections III.B.1. and III.B.2. Analysis

Methodology Applied in Commission Analysis

1. Methodology for Developing Datasets Used for Commission Analysis on Bundle 

Breakage and Productivity Issues

Productivity data related to both manual and automated processing are available via the 

Mail Processing Variance (MPV) dataset, which is developed by aggregating Management 

Operating Data System (MODS) data.1 The MPV dataset includes the volume of mailpieces 

processed on each flats mail processing machine and the number of associated workhours. 

The MPV dataset contains one observation per facility in every fiscal quarter and defines 

productivity as volume divided by workhours. See id.

Bundle processing data are available via a bundle breakage dataset that provides data on 

the number of bundles processed and the number of bundles broken at each facility.2

Transportation data are available in the Surface Visibility (SV) dataset and includes metrics 

such as the number of late trips per facility and container utilization, which is the 

percentage of space that containers utilize in a truck.3

When developing the datasets for analysis in Sections III.B.1. through III.B.2., Sections 

III.C.1. through III.C.2., and Section III.C.4., the Commission cleaned the Postal Service data 

using Python programming language. The cleaning process involved removing rows with 

zero volumes or abnormal observations (outliers). Specifically, some facilities were 

recorded as having zero mail volumes for a particular mail processing machine if that 

machine did not actually exist in that particular facility. These zero observations were 

removed as they did not provide any relevant information on mail processing. Also, each 

dataset was adjusted to account for synonyms that indicated the same value. For example, 

if multiple names were used for the same facility, they had to be standardized. The 

Commission then merged the datasets to gain more information about all the facilities and 

identify those that were substantially above or below average based on certain criterion 

(e.g., level of productivity of flats mailpieces on automated machines or bundle breakage 

1 Responses of the United States Postal Service to Questions 1-8 of Chairman’s Information Request No. 1, August 16, 2022, question 5 

(Response to CHIR No. 1); Docket No. ACR2021, Library Reference USPS-FY21-NP31, December 29, 2021, Excel file “NONPUBLIC MP Variance 

FY17_21.xlsb.”

2 Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “FY17_FY21.Bundle.Brkge.E1_NonPublic.xlsx.”

3 Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “NonPublic SV Data_FY17_FY21.xlsx.”
Docket No. SS2022-1 Appendix A

 Page 2 of 36

rate). See Section III.B.2. The Commission also performed data analysis indicating 

geographic regions where mail processing facilities are located and facility types, such as 

network distribution centers (NDCs) and processing and distribution centers (P&DCs). 

Ultimately, the final dataset the Commission developed included bundle breakage and 

automation processing data at the facility level and with information for each machine at 

each facility. Data were of a quarterly frequency spanning FY 2016 through FY 2021.

2. Commission Data Analysis Underlying the Selection of Mail Processing Sites for 

Visits Based on Automated Flats Sorting Machine (AFSM) and Flats Sequencing 

System (FSS) Volumes and Productivities

As explained in Section III.B.2.a., when selecting mail processing sites, the Commission 

sought to visit:

• both P&DCs and NDCs

• sites in different regions of the United States

• sites with high and medium flats volumes

• sites with relatively high and relatively low

o productivity of AFSMs

o productivity of FSS machines

o rates of broken bundles

• sites that have good network ties with each other

When considering volume processed at facilities as provided in the Postal Service’s 

datasets, the Commission observed that some facilities processed too little flats volume to 

merit consideration for a visit in the time we had available. See Figure A-1.
Docket No. SS2022-1 Appendix A

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Figure A-1

Volume and Productivity of AFSMs at the Mail Processing Facilities:

Facilities with Low Volume vs. Other Facilities4

Figure A-1 provides volume and productivity for all types of facilities with AFSMs. Each dot 

represents a single type of AFSM at a facility in FY 2021.5 For example, a facility may have 

five machines of two types: three AFSM-AI and two AFSM-ATHS. This facility will have two 

dots on the chart (one dot for each AFSM type). Orange dots represent the AFSM 

equipment with volume in the lowest decile of all AFSM machines. They cover a wide range 

of productivities but process such a low volume of flats mailpieces that the Commission 

excluded them from consideration for this study.

As Figure A-2 shows, the Commission visited both types of mail processing facilities—

P&DCs and NDCs—that process flats on AFSMs. Figure A-2 provides the FY 2021 volume 

and productivity for some of the AFSMs at the facilities selected by the Commission for 

visits (visualized by dots of different color) and some other facilities with average volume, 

productivity, or both (visualized by dark grey dots).

4 See Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “NONPUBLIC MP Variance FY17_21.xlsb.”

5 Not all AFSMs are homogenous. For a more detailed description of each AFSM type, please refer to Section III.C.
Docket No. SS2022-1 Appendix A

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Figure A-2

Volume and Productivity of AFSMs at Mail Processing Facilities in FY 20216

For facilities that the Commission did not visit (they are represented by grey dots), both the 

flats volumes and AFSM productivities fall within 50 percent of the mean (average) volume 

and the mean productivity. Thus, for AFSMs, the grey dots represent machines that process 

between approximately 20 million and 60 million flats mailpieces. Other facilities that are 

further from the average volume or average productivity have been filtered. NDC 1 

processes above-average volume on its AFSM equipment, yet its productivity was among 

the lowest of all facilities with AFSMs. P&DC 4 has one of the highest AFSM productivities 

but processes volume close to average. The volume processed by the AFSM located at P&DC 

3 is far above the average level, yet its productivity is close to the average.

Similarly, Figure A-3 displays the FY 2021 volume and productivity of a sample of the FSS 

facilities visited by the Commission (visualized by colored dots) and some other facilities 

(visualized by dark grey dots).

6 See Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “NONPUBLIC MP Variance FY17_21.xlsb.”
Docket No. SS2022-1 Appendix A

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Figure A-3

Volume and Productivity of FSS at Mail Processing Facilities in FY 20217

For the visualized facilities that the Commission did not visit, both the flats volumes and 

FSS productivities are within 30 percent of the average volume and the average 

productivity. Other facilities that are further from the mean volume or mean productivity 

have been filtered. P&DC 3 shows high FSS volume and productivity—far above average. 

NDC 1 processes volume well above average but its FSS productivity is much lower than of

FSS machines at other facilities processing a similar amount of volume. P&DC 5 processes 

flats on its FSS machine at a similar level of productivity as NDC 1, yet it processes roughly 

half of the volume.

When selecting facilities to visit based on the rate of broken bundles, the Commission used 

the bundle breakage dataset provided by the Postal Service as part of flats cost and service 

performance analysis in the Annual Compliance Report (ACR).8 This dataset, however, 

presents unique problems because there are six different machines that can process 

bundles. See Table A-1.

7 See Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “NONPUBLIC MP Variance FY17_21.xlsb.”

8 See Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “FY17_FY21.Bundle.Brkge.E1_NonPublic.xlsx.”
Docket No. SS2022-1 Appendix A

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Table A-1

All Bundle Processing Machines

Acronym Full Name

ADUS Automated Delivery Unit Sorter

APPS Automated Package Processing System

EPPS Enhanced Package Processing System

HTPS High Throughput Package Sorter

SPBSTS Small Parcel and Bundle Sorter Tracking System

SPSS Small Package Sorting System

After analyzing bundle breakage data, the Commission chose to focus primarily on the 

APPS and SPBSTS bundle processing machines because they typically process a large 

volume of bundles.

Figure A-4 was created by filtering the bundle breakage dataset to include only the APPS 

and SPBSTS machines and USPS Marketing Mail Flats. The dataset was further filtered to 

include machines that were within 50 percent of the average volume of bundles processed 

and 50 percent of the average percentage of broken bundles. The facilities selected for 

visits from this filtered dataset had a different rate of broken bundles than a typical mail 

processing facility. Figure A-4 displays a sample of the facilities that the Commission visited 

and where it observed bundle processing, as well all other facilities that process bundles.
Docket No. SS2022-1 Appendix A

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Figure A-4

Bundle Breakage Rate and Bundles Processed – All Facilities9

Figure A-4 demonstrates that both NDC 1 and NDC 2 have very high volume and high rates 

of bundle breakage. P&DC 5 processes a similar number of bundles to NDC 2, yet its bundle 

breakage rate is less than half of the NDC 2 rate.

9 See Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “FY17_FY21.Bundle.Brkge.E1_NonPublic.xlsx.”
Docket No. SS2022-1 Appendix A

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3. Commission Data Analysis Underlying the Selection of Surface Transfer Centers 

(STCs)

When selecting facilities to visit based on transportation metrics, the Commission used the 

SV dataset provided by the Postal Service as part of the ACR.10 The Commission selected 

STCs with low on-time arrivals and on-time departures.

Figure A-5

On-Time Arrival and On-Time Departures by STC

Figure A-5 shows that STC 1 and STC 2 are clear outliers in terms of both low on-time 

arrival and on-time departure when compared to most other facilities.11

10 See Docket No. ACR2021, Library Reference USPS-FY21-NP31, Excel file “NonPublic SV Data_FY17_FY21.xlsx.”

11 On-time arrival and on-time departure percentage are highly correlated. On-time Departure

On-time Arrival
Docket No. SS2022-1 Appendix A

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Section III.B.4.d. Analysis

Impact of Mail Processing Network Design on Allied Operations

In Section III.B.4.d., the Commission discusses the impact of network design on the time 

flats spend in allied operations as they move between facilities for different mail processing 

jobs. Frequent movement of mail between facilities also increases trip frequency and 

mileages driven in the surface transportation network and, in turn, increases 

transportation costs for flats products.

In Section III.B.4.d., the Commission includes an illustrative example of the collaboration 

and the associated flows of USPS Marketing Mail flats volumes between three mail 

processing sites (see Figure III-10.). The flows depicted in Figure III-10 are described in 

more detail below.

The NDC receives USPS Marketing Mail flats pre-sorted in bundles.
Docket No. SS2022-1 Appendix A

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All bundles that break before they can be sorted at the NDC, bundles that are loose and 

bypass bundle/small package processing, and bundles that are rejected during bundle 

processing at the NDC are sent to P&DC 7 for processing. These include bundles that 

destinate in P&DC 2 and in P&DC 7 service areas.

All intact bundles are sorted on the NDC’s bundle/small package sorting equipment, for 

subsequent distribution to mail processing facilities that the NDC serves, including P&DC 2 

and P&DC 7. Bundles that are processed successfully are dispatched to respective P&DCs 

based on whether they destinate in FSS zones. This is explained below.

P&DC 7 service area includes FSS and non-FSS zones; P&DC 2 service area includes only 

FSS zones. However, of the two P&DCs, only P&DC 2 has FSS equipment. As such, USPS 

Marketing Mail bundles that are successfully processed at the NDC and destinate in P&DC 7 

service area are dispatched from the NDC in two separate flows—bundles that destinate in 

P&DC 7 non-FSS zones are sent to P&DC 7 for next processing while bundles that destinate 

in FSS zones served by P&DC 7 are sent to P&DC 2, for sorting of individual flats pieces to 

DPS (on its FSS equipment). Since P&DC 2 service area includes FSS zones only, and since 

this P&DC operates FSS equipment, all successfully processed flats bundles that destinate 

in P&DC 2 service area are dispatched from the NDC to P&DC 2 for subsequent processing, 

in one flow.

P&DC 2 sorts flats that destinate in FSS zones included in its own service area and flats that 

destinate in FSS zones served by P&DC 7, on its FSS equipment.

All successfully sorted flats that destinate in P&DC 7 FSS zones are dispatched to P&DC 7 

where they are cross docked and subsequently dispatched to respective DDUs, served by 

P&DC 7. All successfully sorted flats that destinate in P&DC 2 service area are dispatched to 

respective DDUs that this P&DC serves.

FSS rejects, whether they destinate in the P&DC 2 or P&DC 7 service areas, are sent to 

P&DC 7 to be re-run on the AFSMs and sorted to carrier route. Flats that are sorted on the 

AFSM equipment at P&DC 7, and which destinate in its own service area, are dispatched to 

respective DDUs for final delivery. Carrier routed flats sorted on the AFSM equipment at 

P&DC 7 that destinate in P&DC 2 service area are dispatched to P&DC 2, for eventual 

transportation to respective DDUs, served by P&DC 2.

As for broken/loose/reject flats bundles that P&DC 7 receives from the NDC for processing, 

some destinate in FSS zones (within P&DC 2 and P&DC 7 service areas), while others 

destinate in non-FSS zones (within P&DC 7 service area). After being manually prepared 

and then sorted on the AFSM equipment to 5-digit ZIP Code level, flats that destinate in FSS 

zones (whether within the P&DC 2 or P&DC 7 service areas) are dispatched to P&DC 2, for 

sorting to DPS on the facility’s FSS equipment. Flats from broken/loose/reject bundles that 

destinate in non-FSS zones (within the P&DC 7 own service area) remain at P&DC 7 and are 

sorted on the AFSM equipment to carrier route, for final delivery.
Docket No. SS2022-1 Appendix A

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Section IV.A.2. Analysis

This section covers two parts pertaining to the analysis performed in Section IV.A.2. The 

first part (A1) presents a more detailed discussion of the degree of scale economies. The 

second part (A2) describes the model and the corresponding estimation techniques, as well 

as the tables and figures pertaining to the estimation results.

A1. The Degree of Scale Economies

Definition and Properties

To formalize the idea behind scale economies, it is insightful to begin with the case of a 

single-product firm and then generalize the definition to the multiproduct case, which is 

more relevant to the Postal Service. First, a few notations are introduced.

Let C(v) denote the cost function of a single-product firm, with the argument v denoting 

the output level.

Definition A1.12

The degree of scale economies at v is

S(v) =

C(v)

vC

′(v)

(A1)

Returns to scale are increasing, constant, or decreasing as S(v) is greater than, equal to, or 

less than unity.

In the expression on the right-hand side of (A1), C

′

(v) denotes the derivative of C(v) with 

respect to the output v, i.e., the marginal cost at the level of output v.

The metric S(v) is, as one can observe, the inverse of the elasticity of the cost function with 

respect to the output. Hence, it is interpretable as “the elasticity of the output with respect 

to the cost needed to produce it.” Baumol et al., supra, at 51. The generalization of 

Definition A1 to the multiproduct case is obtained by first viewing the output as a vector 

v = (v1, ... , vJ), where it is assumed that there are J outputs in total. In the case of the 

Postal Service, v includes Competitive products grouped as a single mail product, among its 

components.

12 William J. Baumol et al., Contestable Markets and the Theory of Industry Structure 21 (Definition 2A6) (1988).
Docket No. SS2022-1 Appendix A

 Page 12 of 36

Let C(v) denote the cost function of a multiproduct firm, with the argument v denoting the 

relevant composite output, v = (v1, ... , vJ).

Definition A2.13

The degree of scale economies defined over the entire product set N = {1, ... ,J}, at v, is given 

by

SN(v) =

C(v)

∑ vjCj

′

j (v)

, (A2)

where Cj

′

(v) denotes the partial derivative of the cost function with respect to the jth output, 

i.e., the marginal cost of product j, Cj

′

(v) =

∂C(v)

∂vj

. (A3)

SN(v) can be interpreted as the elasticity of the output bundle v with respect to the cost 

needed to produce it, and returns to scale are increasing (constant, or decreasing) as 

SN(v) is greater than unity (equal to, or less than unity, respectively). Baumol et al., supra, 

at 50, 51.

Worthy of note is the fact that the metric SN(v) is dimension-free. In particular, it is not 

affected by inflation since the latter’s effects on the numerator and the denominator cancel 

out.

Remark A1.

The elasticity of a single-argument function can, in general, be defined for a given value of 

the argument as the ratio of the marginal value of the function to its average value. Hence, 

for a cost function of a single-product firm, the elasticity is the ratio of the marginal cost to 

the average cost. The right-hand side of relation (A1) can, therefore, equivalently be 

expressed as the ratio of the average cost (cost per output unit) to the marginal cost (cost 

of the last unit).

S(v) =

C(v)

vC′(v)

=

(

C(v)

v

)

C′(v)

 (A4)

In the multi-product case, the metric SN(v) can be given a similar representation, i.e., the 

ratio of average to marginal cost. However, because the average cost, as stressed by 

Bradley (2017)14, is an ill-defined concept, a conventional metric can be defined by 

13 Baumol et al., supra, at 50 (Definition 3B1).

14 United States Postal Service, Office of Inspector General, Report No. RARC-WP-17-005, Examining Changes in Postal Product Costs, March 13, 

2017, at 11, available at https://www.uspsoig.gov/sites/default/files/reports/2023-01/RARC-WP-17-005_0.pdf.
Docket No. SS2022-1 Appendix A

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referring to the concept of ray average cost (RAC). Baumol et al., supra, at 48-50. The RAC is 

defined by first fixing a bundle, say v

0

, and then calculating the average cost of t units of 

this reference bundle, i.e., of tv

0

,t > 0, where t becomes the (one-dimensional) count unit.

RAC(t; v

0

) =

C(tv

0

)

t

 (A5)

However, because the choice of the reference bundle v

0

is completely arbitrary, it can be 

(conventionally) taken to be the product mix in which the quantity of each product is 

expressed as a fraction of the total number of mailpieces.

v

0 = (

v1

∑j vj

, ... ,

vJ

∑j vj

) (A6)

The quantity t is chosen in this case to be the total number of mailpieces: t = ∑j vj. With 

these choices, the RAC takes the form

RAC(∑j vj; v

0

) =

C((∑j vj

)v

0)

∑j vj

=

C(v)

∑j vj

 (A7)

Noteworthy is the fact that the right-hand side of the second equality in (A7) is a popular 

alternative way in which the cost per mailpiece is defined in the postal literature, i.e., as 

total operating cost divided by total mailpieces. Taking this as a conventional measure for 

the average cost, one has (by dividing both the numerator and the denominator by total 

mail pieces)

SN(v) =

C(v)

∑ vjCj

′

(v) j

=

(

C(v)

∑ vj j

)

(

∑ vj

Cj

′

(v) j

∑ vj j

)

=

RAC

AMC

. (A8)

The denominator of the right-most ratio in (A8) is the volume-weighted average of the 

product-level marginal cost or, equivalently, the ratio of the total volume-variable cost to 

total number of mailpieces, which will be referred to as the aggregate marginal cost (AMC). 

Hence AMC is an overall measure of marginal cost and relation (A8) expresses the degrees 

of scale economies as the ratio of the average cost, measured by the RAC, to the aggregate 

marginal cost, measured by AMC.
Docket No. SS2022-1 Appendix A

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Application

In the context of this analysis, the cost C(v) is taken to be the Postal Service’s total 

operating cost in a given fiscal year. The argument v is the volume bundle corresponding to 

the set N, the set of all products in the relevant fiscal year. In the parlance of the postal 

costing, the product between the marginal cost of the mail product j and its volume, i.e., 

vjCj

′

(v), represents product jth’s volume-variable cost. Hence, the sum ∑ vjCj

′

j (v)

represents the total volume-variable cost. The degree of scale economies is measured, 

therefore, by the ratio of total operating cost to total volume-variable cost, i.e.,

SN(v) =

Total Operating Cost

Total Volume Variable cost

 (3.2)

Because total operating cost is larger than volume-variable cost, SN(v) is larger than 1, i.e., 

returns to scale are increasing in the context of the Postal Service. This means that overall 

decline in volume will likely result in a comparatively slower decline in overall operating 

cost. In the case of a single-product firm, this would mean an increase in unit costs, all other 

things held constant.

Remark. Although it is tempting to conclude that given a level of overall operating cost, 

larger total volume-variable cost induces a lower degree of scale economies, which, in the 

context of decreasing mail volumes, may suggest that more cost should be attributed 

regardless of statutory costing principles, one must resist that temptation. Indeed, the 

reason for calculating total variable cost is the existence of common costs that cannot be 

causally linked to specific products or sub-groups of products. Hence, the size of the total 

volume-variable cost is not a deliberate choice left to the discretion of the Postal Service.

Product-specific returns to scale can be calculated as the ratio of the average incremental 

cost of the mail product to its marginal cost. Baumol et al., supra, at 68. In the Postal 

Service’s costing methodology, product incremental cost is defined as the sum of its 

volume-variable costs, its product-specific costs, and those inframarginal costs calculated 

as part of a product's incremental cost. See 39 C.F.R. § 3035.107(b). Although it may seem 

more convenient to have an independent product-level cost function, as already mentioned, 

there is no meaningful way to disaggregate the Postal Service cost function into a set of 

product-level cost functions.

Regarding the magnitudes of the loss of scale economies, in FY 2021 calculated using total 

operating cost, for example, the degree of scale economies was equal to 1.83 (see Section 

IV.A.2., Figure IV-8). Hence, each percent decrease in volumes has induced only 1

1.83

or 0.55

percent decrease in costs.
Docket No. SS2022-1 Appendix A

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Table A-2 displays marginal costs of the four flat-shaped mails (columns 2-5), along with 

the aggregate firm-level marginal costs (the volume-weighted average of the products’ 

marginal costs, which is also equal to the total volume-variable cost over all mailpieces, 

which are provided in column 6.

Table A-2

Marginal Costs

FY FC 

Flats

Marketing Mail 

Flats

In County 

Periodicals

Outside County 

Periodicals 

Firm-Level Aggregate 

Marginal Cost

2008 0.76 0.39 0.11 0.34 0.21

2009 0.75 0.45 0.12 0.36 0.23

2010 0.86 0.45 0.14 0.36 0.23

2011 0.87 0.46 0.13 0.36 0.23

2012 0.87 0.46 0.15 0.38 0.24

2013 0.89 0.45 0.14 0.36 0.24

2014 0.88 0.49 0.15 0.38 0.24

2015 0.93 0.50 0.16 0.38 0.25

2016 0.97 0.47 0.16 0.39 0.26

2017 1.06 0.52 0.16 0.40 0.26

2018 1.12 0.59 0.16 0.40 0.28

2019 1.17 0.60 0.19 0.43 0.29

2020 1.28 0.66 0.21 0.48 0.33

2021 1.32 0.72 0.24 0.51 0.35

It is useful to match the marginal costs amounts in Table A-2 with the corresponding rates 

of decline in volumes that were provided in Table IV-1 in Section IV.A.2. of this Report. The 

flats products with the top two highest marginal costs series (First-Class Mail Flats and 

USPS Marketing Mail Flats) also have the respective rates of -7.80 percent and -9.16 

percent, which are higher in absolute value than the average rate of mail decline for Market 

Dominant mail (-3.81 percent). Outside County Periodicals also has higher marginal cost 

than the firm-level aggregate marginal cost and its rate of mail volume decline is larger 

than the average rate for Market Dominant mail. The lowest of the marginal costs pertains 

to In County Periodicals, which nevertheless has a larger volume decline rate than the 

average rate for Market Dominant mail.

The return to scale for product i can be calculated as the ratio of its unit attributable cost to 

its marginal cost. This ratio will be denoted by Si.
Docket No. SS2022-1 Appendix A

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Table A-3 shows the returns to scale for four flat-shaped mail along with the firm-level 

number where the latter, for the sake of comparison, is calculated as the ratio of 

attributable cost to volume-variable cost, for the period from FY 2017 to FY 2021.

Table A-3

Attributable-Cost-Based Firm-Level and Mail-Product-Specific Returns to Scale

FY Firm-Level FC Flats Marketing 

Flats

In County 

Periodicals

Outside 

County 

Periodicals

2017 1.051 1.004 1.004 1.001 1.003

2018 1.077 1.003 1.003 1.001 1.003

2019 1.075 1.003 1.003 1.000 1.003

2010 1.074 1.004 1.004 1.000 1.002

2021 1.075 1.003 1.003 1.000 1.002

In all cases, the degree-of-scale-economies is larger than 1, indicating the existence of scale 

economies over all the considered period, albeit the magnitudes are much smaller than the 

firm-level counterparts. Although Table A-3 has the advantage of offering a way to compare 

the product-level to the firm-level returns to scale, this advantage is tempered by the fact 

that the mail-product-level metric is based on a less comprehensive cost concept. For this 

reason, the product-level degree of scale economies is not given further consideration in 

this section of this Appendix.

A2. Model and Estimation Method

(a) The Model

The econometric model is written as

cit = φ(vit, dt, sit, cit, νi

) + uit (A2.1)

In (A2.1), the indexes i and t denote the mail product and the fiscal year, respectively. The 

dependent variable is the marginal cost, i.e., the unit volume-variable cost, denoted by cit. 

The set of explanatory variables includes the product volume, vit, the share of a product’s 

volume in the mail-class volume, sit , the share of mail class volume in the total (firm-level) 

volume, cit, the number of delivery points, dt, and a product-specific dummy, νi. The data 

underlying the estimation are the result of a piling up the time series of all mail products. 

The term uit denotes the idiosyncratic error term. To control for the effect of inflation, the 

marginal costs are inflation-adjusted prior to the estimation, using the consumer price 

index for all urban consumers, and choosing FY 2021 as the base year.15

15 See U.S. Bureau of Labor Statistics, available at www.bls.gov.
Docket No. SS2022-1 Appendix A

 Page 17 of 36

This estimation, which includes product dummies, does not assume linearity of the 

function. In fact, the estimation is agnostic about φ, which is simply assumed to belong to a 

(large) defined set of base functions of various degrees of complexity. The main 

justification for including product dummies in the model is in the fact that the number of 

mail products can roughly be considered as fixed, i.e., it does not increase with the sample 

size and, therefore, the estimation is not subject to the well-known incidental-parameter 

problem.16 As part of the estimation process, the choice of the regression function is made 

through an index that, in a Ridge-like estimation,17 penalizes function complexity. The 

penalization of complexity is referred to in the relevant literature (the machine-learning 

literature) as a regularization. The specific version of the regularization-based estimation 

technique used in this analysis is known as the kernel regularized least squares, which is 

described below.18

(b) Data and Estimation Results

The estimation of (A2.1) uses the data on volumes and delivery points over the FY 2000 

through FY 2021 time period. The summary statistics of the observed variables entering 

the model are provided in Table A-4 where the product share of the mail class volume is 

the ratio of the product’s volume to the volume of the corresponding mail class. Likewise, 

the share of mail class volume in the total volume is the ratio of the mail class volume to the 

firm-level total mail volume. Prior to the estimation, numerical identification numbers are 

assigned to the mail products. Table A-5 indicates the correspondences, where flats are 

bolded.

Table A-4

Summary Statistics

Variable Obs Mean Std. Dev. Min Max

Marginal Cost (2021 Dollars) 330 1.0 1.4 0.0 6.2

Volume (Millions) 330 11549.9 16299.7 20.0 57086.0

Delivery Points (Millions) 330 150.1 7.9 134.5 163.1

Product's Share of Mail Class Volume 330 0.4 0.4 0.0 1.0

Mail Class's Share of Total Volume 350 0.3 0.2 0.0 0.5

16 See generally Tony Lancaster, The Incidental Parameter Problem Since 1948, 95 J. Econometrics 391 (2000); Manuel Arellano & Jinyong Hahn, 

Understanding Bias in Nonlinear Panel Models: Some Recent Developments (Centro de Estudios Monetarios y Financieros (CEMFI) [Center of 

Monetary and Financial Studies], Working Paper No. 0507, 2005), available at https://ideas.repec.org/p/cmf/wpaper/wp2005_0507.html.

17 See Arthur E. Hoerl & Robert W. Kennard, Ridge Regression: Biased Estimation for Nonorthogonal Problems, 12 Technometrics 55 (1970).

18 Detailed technical information can be found in Jens Hainmueller & Chad Hazlett, Kernel Regularized Least Squares: Reducing Misspecification 

Bias with a Flexible and Interpretable Machine Learning Approach. 22 Pol. Analysis 143 (2014) and Peter Bühlmann & Sara van de Geer, 

Statistics for High-Dimensional Data. Methods, Theory and Applications (2011).
Docket No. SS2022-1 Appendix A

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The estimation results are shown in Table A-6, along with Figure A-6, which provides the 

histograms of the pointwise derivatives of the deflated marginal cost with respect to each 

of the explanatory variables, except for the dummies.

19

Table A-5

Mail Product Identification Numbers

Mail Product/Category Product/Category 

identification Number 

Enhanced Carrier Route 1

Free Mail - blind, handicapped & servicemen 2

Bound Printed Matter Flats and Parcels 3

FC Mail Flats 4

In County Periodicals 5

USPS Marketing Mail Flats 6

USPS Marketing Mail Letters 7

USPS Marketing Mail Parcels 8

Media Mail and Library Mail 9

Outside County Periodicals 10

Presort Cards 11

Presort Letters 12

Single-Piece Letters 13

Single-Piece Postcards 14

Competitive Mail 15

19 The marginal effects of the dummies also vary along the predicted curve. Their histograms have not been included.
Docket No. SS2022-1 Appendix A

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Table A-6

Estimation Results

Number of Obs 330

Reference mail product for dummies: Enhanced Carrier Route

Lambda 0.11

Tolerance 0.33

Sigma 18

Eff. df 39.54

R2 0.97

Looloss 17.78

Marginal Cost in 2021 Dollars Avg. SE t P>t P25 P50 P75

Volume -1.2E-05 1.50E-06 -8.251 0.000 -1.2E-05 -1E-05 -8.00E-06

Delivery Points -0.004 0.002 -2.461 0.014 -0.004 0.000 0.012

Product_Share_of_Class_Volume -0.196 0.051 -3.844 0.000 -0.257 -0.136 -0.037

Class_Share_of_Total_Volume -0.611 0.107 -5.730 0.000 -0.710 -0.517 -0.308

Free Mail -0.071 0.035 -2.036 0.043 -0.233 0.291 0.420

Bound Printed Matter Flats -0.022 0.050 -0.432 0.666 -0.147 0.346 0.474

FC Mail Flats 0.029 0.045 0.644 0.520 -0.017 0.342 0.478

In County Periodicals -0.427 0.043 -10.032 0.000 -0.526 -0.134 0.096

USPS Marketing Mail Flats -0.144 0.048 -3.026 0.003 -0.163 0.153 0.341

USPS Marketing Mail Letters -0.134 0.082 -1.620 0.106 -0.163 0.157 0.286

USPS Marketing Mail Parcels 0.260 0.046 5.585 0.000 0.222 0.546 0.674

Media and Library Mail 1.061 0.044 24.208 0.000 0.719 1.051 1.448

Outside County -0.260 0.039 -6.753 0.000 -0.410 0.085 0.267

Presort Cards -0.344 0.044 -7.842 0.000 -0.455 -0.131 0.140

Presort Letters -0.143 0.065 -2.196 0.029 -0.174 0.148 0.276

Single-Piece Letters -0.150 0.048 -3.161 0.002 -0.203 0.143 0.319

Single-Piece Postcards -0.256 0.044 -5.831 0.000 -0.352 -0.024 0.241

Competitive Mail 0.757 0.039 19.427 0.000 0.280 0.750 1.203
Docket No. SS2022-1 Appendix A

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Figure A-6

Histograms of the Pointwise Derivatives

In Table A-6, “Avg.” denotes the (sample) average pointwise marginal effects. Unlike in 

linear regression, the marginal effect varies along the predicted curve. These average 

marginal effects are given along with their standard deviation and the corresponding pvalues. The last three columns, P25, P50, and P75, respectively, display the 1st quartile, the 

median, and 3rd quartile of the pointwise marginal effects. The estimation is performed 

with the STATA package and, more precisely, with the command “krls” and its associated 

postestimation commands.

(c) In-Sample and Out-of-Sample Forecasts

Figure A-7 shows the in-sample predictions. Only the predictions for 3 fiscal years (FY 

2008, FY 2015, and FY 2021) are presented, for illustrative purposes. The centers of the 

triangles are the actual values of the deflated marginal cost. The (brown-color) discs at the 

top end of the vertical segments represent the predicted values. The locations of mail 

products on the x-axis are determined by the numerical identification numbers assigned to 

them (see Table A-5).
Docket No. SS2022-1 Appendix A

 Page 21 of 36

Figure A-7

In-Sample Prediction
Docket No. SS2022-1 Appendix A

 Page 22 of 36

(d) The Kernel Regulated Least Squares Estimation

The estimation procedure for φ will consist of: (i) defining, on the basis of the available data 

sample, the set of candidate functions that will fit the data and (ii) choosing the best 

function from the set of candidate functions, based on a loss function (which is defined so 

as to penalize those functions that have too many parameters, and hence are too complex).

A clarification concerning the word “kernel” is needed to avoid any confusion between the 

regularized least squares method used here and the traditional weighted local estimation 

called the kernel regression. While both approaches (KRLS and kernel regression) use 

mathematical kernels, the KRLS method uses a kernel to define (from the sample 

observations on the explanatory variables) the set of candidate functions that can be used 

to fit the data.20 This amounts to defining the candidate right-hand side variables in a linear 

ridge regression equation. In that sense, regularized least squares methods are generalized 

ridge-regression methods in which the estimate function is chosen from some suitable 

space of functions defined on the basis of the available sample. The objective is to minimize 

some given loss function over the defined space of functions. A penalization term (the 

“regularizer”) is added to the loss function to control the complexity of the optimally 

chosen function. A trade-off between the model fit and function complexity is realized 

through a positive multiplicative coefficient, say λ, to the regularizer.21 A larger value of the 

coefficient λ is synonymous to a heavier penalty imposed to more complex functions. Id. In 

the specific method considered, the suitable class of candidate functions are all kernelexpansion functions φ of the form

φ(. ) = ∑l clk(. , xl) (A2.2)

where l denotes the observation index, xlis the vector of the values of the explanatory 

variables appearing in observation l, and c1, ... , cN are coefficients to be estimated along 

with λ. The function k(. , . ) is some suitable kernel function chosen by the modeler, e.g., the 

Gaussian kernel function

(xi, xj; δ) = e

(

||xi−xj||

2

δ

)

,

where δ is the dimension of xi and ||.|| is the Euclidean norm.

20 Mathematically, a given kernel gives rise to a class of kernel-expansion types of functions that can be organized into a reproducing kernel

Hilbert space (RKHS). The “representer theorem” is a set of results according to which a large class of optimization problems with RKHS 

regularizers have solutions that can be expressed as kernel expansions in terms of the sample. See, e.g., Bernhard Scholkopf et al., A 

Generalized Representer Theorem 416 (David Helmbold & Bob Williamson eds., 2001), available at 

https://alex.smola.org/papers/2001/SchHerSmo01.pdf.

21 See generally Hainmueller & Hazlett, supra; Bϋhlmann & van de Geer, supra.
Docket No. SS2022-1 Appendix A

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Formally, the problem to be resolved is a version of the so-called Tikhonov Regularization 

Problem:

Argminφ∈Φ ∑ (yl − φ(xl

))

2

+ λ ∥ φ ∥

2

l

 (A2.3)

where ∥. ∥ is the norm corresponding to the Reproducing Kernel Hilbert Spaces defined by 

the chosen kernel,22 and ylis the value of the dependent variable in the l-th observation.

The estimation consists in optimally choosing the coefficients c1, ... , cN, λ, and the variance 

σ

2 of the error term u in the regression equation y = ∑l clk(. , xl) + u, where y is the

dependent variable. Homoskedasticity is implicitly assumed (but is not necessary) in the 

presentation.

Hainmueller and Hazlett (2014) summarize some of the properties of the KRLS estimator 

as follows.

First, it is worth noting that for a given λ > 0, problem (16) has the unique solution

c

∗ = (K + λI)−1y,

23

where K = [

k(Q1 ,Q1

) ⋯ k(Q1 ,QN)

⋮ ⋱ ⋮

k(QN ,Q1) ⋯ k(QN,QN)

]. (A2.4)

Under the assumptions that the unknown function is of the form (A.2.1), but y is observed 

with an error u of zero conditional expectation, E(u|Q) = 0, the estimator, ĉ, of the vector 

c = (c1, ... , cN) (which is simply of the same form as (A2.4), with the particularity that the 

observed y is noisy), is unbiased in the sense: E(ĉ|Q, λ) = c, where λ is included in the 

condition to emphasize the dependence of the optimal solution on it. Likewise, the 

predicted marginal cost function, φ̂(x), is pointwise unbiased, conditional on volume, i.e.,

E(φ̂(x)| Q, λ) = φ(x) ∀x (A2.5)24

Regarding the small-sample properties of the KRLS, Hainmueller and Hazlett (2014) 

provide evidence, from simulations, of the not-so-bad small-sample performance of the 

kernel regularized least squares method.25

22 See Hainmueller & Hazlett, supra, at 149.

23 See id.

24 Recall that ridge estimator is biased but has lower variance than the OLS estimator. So, the untestable assumption that the unknown function 

is in the choice set is crucial for the unbiasedness.

25 See W. Holmes Finch & Maria E. Hernández Finch, Multivariate Regression with Small Samples: A Comparison of Estimation Methods. 43 Gen. 

Linear Model J. 16 (2017).
Docket No. SS2022-1 Appendix A

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Section IV.B. Analysis

Expanded Discussion of Dependent Components

Note on delivery dependent component unit cost calculations

When calculating a product’s unit costs for delivery dependent components, the volume of 

the product is split into city volume and rural volume.26 City Carrier dependent component 

costs are divided by city volume, Rural Carrier dependent component costs are divided by 

rural volume.

Mail processing dependent component driving factors

The mail processing dependent component encompasses three major categories of 

activities: (1) automated and manual distribution of mail; (2) “allied labor” operations27; 

and (3) miscellaneous work including other mail processing support activities.28 This 

component is partitioned into three types of facilities in which the costs accrue: MODS 

facilities, NDCs,

29 and “non-MODS” offices. MODS facilities include P&DCs, processing and 

distribution facilities (P&DFs), and International Service Centers (ISCs).Id. The non-MODS 

group consist primarily of Post Offices, stations, and branches not included in the previous 

two groups. Id. at 37. They are generally Post Offices and other small facilities that engage 

primarily in manual mail processing activities. Id.

The following analyzes the partitioned mail processing dependent component costs of the 

two products with the highest mail processing costs, USPS Marketing Mail Flats and FirstClass Mail Flats.

USPS Marketing Mail Flats Mail Processing Dependent Component Driving Factors

To understand the driving factors for increase in the mail processing costs of USPS 

Marketing Mail Flats, the next three figures illustrate the cost changes in the three types of 

facilities that partition the mail processing dependent component.

26 The city/rural volume split for each product is calculated each year using percentages derived from the city and rural volumes provided in 

Chairman’s Information Request No. 8 and Notice of Filing Under Seal, January 25, 2023, question 2.

27 This includes platform operations, collection and cancellation operations, main preparation, manual bundle/tray/sack/sorting, and 

dispatching.

28 See Summary Description of USPS Development of Costs by Segments and Components, Fiscal Year 2021, July 1, 2022, folder “Summary 

Description FY2021.zip,” file “CS03-21.docx” (FY 2021 Cost Segment 3 Summary Description).

29 NDCs use MODS for operational data reporting but are treated as a separate facility group. Id. at 3-3.
Docket No. SS2022-1 Appendix A

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MODS facilities

MODS costs are separated into cost pools forming three primary groups: distribution 

operations, allied operations, and miscellaneous and support operations.30 Figure A-8 

separates the MODS cost in this way, with specific distribution operations separated out 

(AFSM 100, FSS, APBS Bundle) because these are of particular interest for flats products. 

Clerk and mailhandler costs associated with AFSM 100 operations, which has been 

increasing since FY 2016, appears to be a driving factor in the increase in mail processing 

unit costs since FY 2016. The other operations remain relatively stable.

Figure A-8

USPS Marketing Mail Flats MODS Facilities Unit Costs by Operation, FY 2013–FY 202231

NDCs

Clerk and mailhandler labor costs at NDCs are relatively low compared to other facilities 

and remain relatively stable compared to the other facilities. See Figure A-9.

30 See id. at 3-4-3-6.

31 As seen in Figure A-8, the mail processing dependent component unit cost had been quite stable prior to FY 2013. For simplicity, the figures 

showing the partitioned mail processing dependent component unit costs will only focus on 10 fiscal years.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

AFSM100 FSS APBS BUNDLE

MANUAL ALLIED MISC

OTHER DISTRIBUTION

AFSM 100
Docket No. SS2022-1 Appendix A

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Figure A-9

USPS Marketing Mail Flats NDCs Unit Costs by Operation, FY 2013–FY 2022

Non-MODS Facilities

Non-MODS offices are generally Post Offices and other small facilities that engage primarily 

in manual mail processing activities.32 As seen in Figure A-10, non-MODS clerk and 

mailhandler costs were very stable until FY 2017. In FY 2018, there was a sudden jump in 

the costs of all activities (allied, manual, and other), and increases have continued for 

manual activities since while allied operations were stable a couple years before large 

increases in FY 2021 and FY 2022. These increases contribute to the increase in mail 

processing unit costs seen in Figure IV-24 in Section IV.B.2.d. The sudden jumps in costs in 

FY 2018 are due to methodology changes implemented that year.33

32 See id. at 3-7.

33 Beginning in FY 2018, costs recorded at MODS facilities in LDCs 41-44, 48-49, and 79 are included in the costs for non-MODS offices. Id. at 3-3 

n.2; see Docket No. RM2018-10, Order on Analytical Principles Used in Periodic Reporting (Proposal Seven), October 12, 2018 (Order No. 4855).

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

FSS MANP APBS ALLIED OTHER DISTRIBUTION
Docket No. SS2022-1 Appendix A

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Figure A-10

USPS Marketing Mail Flats Non-MODS Facilities Unit Costs by Operation, FY 2013–FY 2022

First-Class Mail Flats Mail Processing Dependent Components Driving Factors

MODS Facilities

Similar to USPS Marketing Mail Flats, clerk and mailhandler costs associated with AFSM 

100 appear to be the driving factor for the increase in mail processing unit costs for FirstClass Mail Flats since FY 2014. The other operations remain relatively stable. See Figure A11.

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

ALLIED MANUAL OTHER
Docket No. SS2022-1 Appendix A

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Figure A-11

First-Class Mail Flats MODS Facilities Unit Costs by Operation, FY 2013–FY 202234

Non-MODS Facilities35

Although there is a sharp increase in the unit costs of all non-MODS operations36, nonMODS unit costs are low compared to costs associated with AFSM 100 operations. See 

Figure A-12. Therefore, these sudden jumps are not noticeable in the unit cost of the mail 

processing dependent component seen in Figure IV-31 in Section IV.B.2.f.

34 As seen in Figure IV-12 in Section IV.B.1., the mail processing dependent component unit cost had been quite stable prior to FY 2013. For 

simplicity, the figures showing the partitioned mail processing dependent component unit costs will only focus on 10 fiscal years.

35 Mail processing unit cost at NDCs for First-Class Flats is excluded from the analysis because it is very low and contribute a negligible amount 

to the mail processing dependent component.

36 Similar to USPS Marketing Mail Flats, this jump corresponds with a methodology change in how costs are recorded. See generally Order No. 

4855; FY 2021 Cost Segment 3 Summary Description.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

AFSM100 FSS APBS BUNDLE

MANUAL ALLIED MISC

OTHER DISTRIBUTION

AFSM 100
Docket No. SS2022-1 Appendix A

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Figure A-12

First-Class Mail Flats Non-MODS Facilities Unit Costs by Operation, FY 2013–FY 2022

0

0.01

0.02

0.03

0.04

0.05

0.06

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Unit Cost (dollars)

Fiscal Year

ALLIED MANUAL OTHER
Docket No. SS2022-1 Appendix A

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Section IV.C. Analysis

1. Methodology for Developing Datasets for Econometric Analysis

The Postal Service provides annually to the Commission the daily Management Operating 

Data System (MODS) data37 by facility, tour,38 and operation and the monthly MODS data39

by facility and operation. To support the MODS data, the Postal Service also annually 

provides the map of MODS operations to operation groups.40 To calculate excess capacity at 

the mail processing facilities for FY 2017 to FY 2022, the Postal Service provided the key41

to the finance number and name of each facility, as well as the machine counts42 at each 

facility for FY 2017 to FY 2022. The Postal Service also made available the list of relevant 

MODS operations codes,43 including the operations codes used to calculate the excess 

37 Docket No. ACR2017, Library Reference USPS-FY17-NP18, December 29, 2017, folder “documents,” folder “USPS-FY17-NP18,” folder “USPSFY17-NP18 MODS Data,” folder “mods2017tour-np,” file “mods2017tour-np.csv;” Docket No. ACR2018, Library Reference USPS-FY18-NP18, 

December 28, 2018, folder “USPS-FY18-NP18.files,” folder “USPS-FY18-NP18 MODS Data,” folder “mods2018tour-np,” file “mods2018tournp.csv;” Docket No. ACR2019, Library Reference USPS-FY19-NP18, December 27, 2019, folder “USPS-FY19-NP18,” folder “USPS-FY19-NP18 

MODS Data,” folder “modstour2019-np,” file “modstour2019-np.csv;” Docket No. ACR2020, Library Reference USPS-FY20-NP18, December 29, 

2020, folder “USPS-FY20-NP18,” folder “USPS-FY20-NP18 MODS Data,” folder “modstour2020-np,” file “modstour2020-np.csv;” Docket No. 

ACR2021, Library Reference USPS-FY21-NP42, February 22, 2022, folder “OneDrive_2022_02-22,” folder “Docket No. ACR.2021,” folder “USPSFY21-NP42,” folder “USPS-FY21-NP42.files,” file “modstour2021r-np.csv;” Docket No. ACR2022, Library Reference USPS-FY22-NP18, December 

29, 2022, folder “USPS-FY22-NP18,” folder “USPS-FY22-NP18 MODS Data,” folder “mods2022tour-np,” file “mods20222022-np.csv.”

38 MODS is a Postal Service national program that is a systematic approach to gathering, storing, and reporting workload, workhours, and 

machine utilization. The MODS day consists of three tours of 8 hours each; Tour II begins at the start of the MODS day, followed by Tour III, and 

ends with Tour I. For example, if the MODS day begins at 07:00, tour times would be Tour II from 07:00 to 14:59, Tour III from 15:00 to 22:59, 

and Tour I from 23:00 to 06:59. See Docket No. ACR2022, Library Reference USPS-FY22-NP18, folder “USPS-FY22-NP18,” folder “USPS-FY22-

NP18 MODS Data,” file “M-32 MODS Handbook.pdf,” at 1 n. 9 (MODS Handbook).

39 Docket No. ACR2017, Library Reference USPS-FY17-NP18, folder “documents,” folder “USPS-FY17-NP18,” folder “USPS-FY17-NP18 MODS 

Data,” file “mods_month_fy17.csv;” Docket No. ACR2018, Library Reference USPS-FY18-NP18, folder “USPS-FY17-NP18.files,” folder “USPSFY18-NP18 MODS Data,” file “mods_month_fy18.csv;” Docket No. ACR2019, Library Reference USPS-FY19-NP18, folder “USPS-FY19-NP18,” 

folder “USPS-FY19-NP18 MODS Data,” file “mods_month_fy19.csv;” Docket No. ACR2020, Library Reference USPS-FY20-NP18, folder “USPSFY20-NP18,” folder “USPS-FY20-NP18 MODS Data,” file “mods_month_fy20.csv;” Docket No. ACR2021, Library Reference USPS-FY21-NP18, 

December 29, 2021, folder “USPS-FY21-NP18,” folder “USPS-FY21-NP18 MODS Data,” file “mods_month_fy21.csv;” Docket No. ACR2022, 

Library Reference USPS-FY22-NP18, folder “USPS-FY22-NP18,” folder “USPS-FY22-NP18 MODS Data,” file “mods_month_fy22.csv.”

40 Docket No. ACR2017, Library Reference USPS-FY17-23, December 29, 2017, folder “USPS-FY17-23,” folder “Programs,” file “opmap17.xlsx;” 

Docket No. ACR2018, Library Reference USPS-FY18-23, December 28, 2018, folder “USPS-FY18-23,” folder “Programs,” file “opmap18.xlsx;” 

Docket No. ACR2019, Library Reference USPS-FY19-23, December 27, 2019, folder “USPS-FY19-23,” folder “Programs,” file “opmap19.xlsx;” 

Docket No. ACR2020, Library Reference USPS-FY20-23, December 29, 2020, folder “USPS-FY20-23,” folder “Programs,” file “opmap20.xlsx;” 

Docket No. ACR2021, Library Reference USPS-FY21-23, December 29, 2021, folder “USPS-FY21-23,” folder “Programs,” file “opmap21.xlsx;” 

Docket No. ACR2022, Library Reference USPS-FY22-23, December 29, 2022, folder “USPS-FY22-23,” folder “Programs,” file “opmap22.xlsx.”

41 Docket No. ACR2021, Library Reference USPS-FY21-NP42, folder “OneDrive_2022_02-22,” folder “Docket No. ACR.2021,” folder “USPS-FY21-

NP42,” folder “USPS-FY21-NP42.files,” file “ChIR17.Q4b.finlist_FY21_MODS.nonpublic.xlsx.”

42 Library Reference USPS-SS2022-1 - NP6, February 1, 2023, folder “USPS-SS2022-1_NP6,” folder “SS.NP6.ChIR.8.NP.Files,” folder “Q.5,” file 

“ChIR8.Q5.Rev.AttB.Nonpublic.xlsx,” tab “Machine Counts;” Responses of the United States Postal Service to Questions 1-6 of Chairman’s 

Information Request No. 8, February 1, 2023, Excel file “ChiR 8 Q3 2016_2022.xlsx.”

43 See Responses of the United States Postal Service to Questions 1-8 of Chairman’s Information Request No. 1, August 16, 2022, question 5.c.
Docket No. SS2022-1 Appendix A

 Page 31 of 36

capacity at the mail processing facilities. The operations codes employed in determining 

the excess capacity are part of the labor distribution code (LDC) 12.44

The Commission created a subset of the daily MODS data aggregated to the monthly level 

by LDC 12 and a subset of the monthly MODS data by LDC 12 and merged the two subsets, 

comprising the relevant operations relating to AFSM and FSS mail processing machines. 

The merger enabled the Commission to get the total volume (the number of pieces-fed)45

and the labor workhours on machines from daily MODS data and the machine downtime46

hours from the monthly MODS data. The merged MODS data were combined with the 

operations map data, the facility identifier data, and the machine count data to create 

comprehensive data to calculate excess capacity. This merger allowed the Commission to 

ascertain each facility's machine type, machine count, capacity, reported volume, 

workhours, and downtime.

2. Testing Explanatory Variables for Multicollinearity

To ensure that there is no multicollinearity in the econometric models developed and 

presented within the instant study, the Commission ran some tests. A high (although not 

perfect) correlation between two or more independent (explanatory) variables is called 

multicollinearity.47 High multicollinearity threatens the stability and precision of the 

estimated coefficients in the regression models over time.48 To measure the degree to 

which each explanatory (predictor) variable is affected by multicollinearity, statisticians 

apply the variance inflation factor (VIF) test. The higher the VIF, the more serious the effect 

of multicollinearity is on the explanatory variables.49 An accepted cutoff value for the VIF is 

10.50 Multicollinearity exists when VIF > 10. Table A-7 presents VIFs for all three 

econometric models discussed in Sections IV.C.1. and IV.C.3. It is easy to see that there is no 

multicollinearity in any of these models.

44 The LDC is a matrix of the Postal Service’s National Workhour Reporting System (NWRS), the labor expense functional reporting system 

consisting of the National Workhour Report and the Labor Utilization Report. LDC 12 records all nonsupervisory hours of employees involved in 

the mechanized distribution of letters and flats relating to mail processing operations. See Docket No. R2006-1, Library Reference USPS-LR-L-55, 

May 3, 2006, folder “LR-55,” folder “LR-L-55 electronic version (.doc &. excel),” folder “lr-l-55 part1,” PDF file “_Labor Distribution Codes.pdf.” 

See also United States Postal Service, Publication 32 – Glossary of Postal Terms, July 2013, available at 

https://about.usps.com/publications/pub32/pub32_terms.htm#ep1011832.

45 Total pieces fed (TPF) is the number of pieces inducted at the front of mechanization or automation equipment. This count includes rejects, 

reworks, re-feed, etc. While preparing the data, the TPF was set equal to the total piece handling (TPH), wherever TPF is less than TPH in the 

data. TPH is the number of handlings necessary to distribute each piece of mail from the time of receipt to dispatch. See MODS Handbook at 

17-18. See also Docket No. ACR2022, Library Reference USPS-FY22-23, December 29, 2022, folder “USPS-FY22-23,” folder “Programs,” TXT file 

“MODSprod22_log.txt.”

46 The Postal Service did not include records of downtime hours in the daily MODS data for FY 2017 to FY 2021.

47 See Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach 95 (5th ed. 2013).

48 For the discussion of the potential impact of multicollinearity on the estimated variabilities in the Postal Service costing models, see, e.g., 

Docket No. RM2019-6, Order on Analytical Principles Used in Periodic Reporting (Proposal One), January 14, 2020, at 18, Appendix (Order No. 

5405).

49 For more details, see, e.g., John Fox, Applied Regression Analysis and Generalized Linear Models 320-21 (2nd ed. 2008).

50 See, e.g., Wooldridge, supra, at 98; Dawn Iacobucci et al., Mean Centering Helps Alleviate “Micro” But Not “Macro” Multicollinearity, 48 

Behav. Rsch. Methods 1308, 1315 (2016).
Docket No. SS2022-1 Appendix A

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Table A-7

The Variance Inflation Factor (VIF) – Multicollinearity Test

VIF Test

Dependent Variable Explanatory Variables VIF

AFSM

Excess Capacity lnDowntime, lnVolume 4.03

Excess Capacity lnMachineNo, lnVolume 3.17

lnWorkhours ExcessCapacity, lnVolume 1.90

FSS

Excess Capacity lnDowntime, lnVolume 3.57

Excess Capacity lnMachineNo, lnVolume 3.14

lnWorkhours ExcessCapacity, lnVolume 1.27

3. Summary Statistics

Table A-8 provides some basic information about all variables in econometric models for 

AFSM and FSS machines. See Sections IV.C.1., IV.C.3. There were 1,187 observations for 

AFSM and 246 observations for FSS models.

Table A-8

Summary Statistics

Variable Units Obs Mean Std. dev. Min Max

AFSM

ExcessCapacity Percent 1,187 0.426475 0.2032069 -0.4849408 0.947901

lnVolume Million 1,187 17.55494 0.9175507 9.964818 19.70422

lnDowntime Hours 1,187 5.713749 1.062127 -2.995732 8.11068

lnWorkhours Hours 1,186 9.829 1.011889 5.022103 12.44823

lnMachinesNo Numbers 1,187 0.604731 0.5718543 0 2.079442

FSS

ExcessCapacity Percent 246 0.705253 0.076907 0.3522206 0.8712559

lnVolume Million 246 17.92949 0.5915817 16.20959 19.34828

lnDowntime Hours 246 6.979262 0.5420426 5.499706 8.339649

lnWorkhours Hours 246 10.2613 0.6587158 8.645352 12.07607

lnMachinesNo Numbers 246 0.6454212 0.5141506 0 1.791759
Docket No. SS2022-1 Appendix A

 Page 33 of 36

Section IV.E. Analysis

Expanded Discussion of Costing Methodology Changes

This analysis bears upon the issue of producing reliable SPLY comparisons and more 

generally on the possibility of constructing a series of unit flats costs going back in time. 

Clearly, a comparison of costs in one fiscal year to another would need to rely on the 

adjusted unit costs, but the question is how to make that comparison, and the answer to 

that question will influence the comparison. If a simple comparison from year to year may 

be misleading, one possible remedy would be to compare adjusted attributable unit costs, 

where the adjustment would be derived from the projected impacts.

Consider a comparison of the FY 2021 Carrier Route Flats costs to the FY 2020 costs. A 

simple comparison of unit attributable costs would show an increase in Carrier Route Flats 

costs of 3.5 percent.51 However, if the costs are first transformed by making the relevant 

adjustments, the comparison shows a 3.0 percent decline in unit costs.52

Such an exercise would rely upon an assumption that the impacts estimated for one year 

are appropriate to use to adjust attributable unit costs in prior years, an assumption 

Section IV.E. of this Report makes in proposing a time series.53 This assumption requires 

that events and changes each year are independent, which is a strong assumption to make. 

Suppose, for example, that some event had occurred in FY 2019, which made the FY 2020 

changes in In-Office Cost System (IOCS) impossible to apply to FY 2019. Then the 

application of these cost adjustments to all prior years would produce inaccurate 

attributable unit costs. By explicitly assuming the independence of the adjustments, this 

analysis calls for attention to the care that should be taken in use of the time series data.

51 Commission calculations using data from FY 2021 and FY 2020 Public CRA. See Docket No. ACR2021, Library Reference USPS-FY21-1, 

December 29, 2021, PDF file “USPS-FY21-1 Preface.CRA.Report.pdf”(FY 2021 Public CRA Report); Docket No. ACR2020, Library Reference USPSFY20-1, December 29, 2020, PDF file “USPS-FY20-1 Preface.CRA.Report.pdf” (FY 2020 Public CRA Report).

52 Commission calculations using data from FY 2021 Public CRA Report and FY 2020 Public CRA Report. These relevant adjustments include 

inflation and methodology changes as described below.

53 There is a materiality issue here, of course. Consider Docket No. RM2015-19, which merges C/S 3 and C/S 4. A small impact is felt on FCM 

flats (-0.01 cents) and by increases of similar magnitude in some other flats products.
Docket No. SS2022-1 Appendix A

 Page 34 of 36

The issue becomes more problematic when comparing unit costs over a greater span of 

time because of the frequency of methodological changes. Consider again, as an example, 

the impact of methodology changes on the Carrier Route Flats product. The appropriate 

local impact due to methodology changes in FY 2020 alone would include:

• IOCS Cluster Sampling using Time and Attendance Collection System (Docket No. 

RM2020-10)

o 1.74 cents

• New Methodology for City Carrier Delivery Time (Docket No. RM2020-7)

o -0.70 cents

• Update and Improve Methodology for Calculating SPR Cost Estimates (Docket No. 

RM2019-6)

o -0.10 cents

• Update Method for Estimating Facility-Related Costs (Docket No. RM2020-1)

o -0.04 cents

The local impact for Carrier Route Flats due to methodology changes in FY 2020 would be 

0.90 cents (1.74 -0.70 -0.10 -0.04). Application of the provided local impact to prior years’ 

unit costs would require the assumption that this adjustment derived for Carrier Route 

Flats in FY 2020 is applicable to prior years. A decision also needs to be made as to whether 

the adjustments are best represented by level quantities or proportions, or in some other 

way.

The adjustments applied in Section IV.E. of this Report are due to methodological changes. 

Cost impacts due to methodological changes are more likely to be applicable to previous 

years, unlike changes in products’ volume mix or operational changes. The presumption 

made here is that the Postal Service will adopt the most accurate estimate of the cost 

impact, subject to cost considerations, that evolving technology will support. Part of the 

motive for introducing changes to a costing methodology may at times be keeping up with 

operational practices, but for the purposes of this Report it is assumed to be secondary to 

choosing the most accurate technique for cost measurement.

Using the Carrier Route Flats example, this assumption suggests that the 0.90 cents local 

adjustment in FY 2020 should apply to all prior years in order to make a valid comparison 

of attributable unit cost across years. Therefore, in constructing the time series seen in 

Section IV.E., the unit attributable costs of FY 2008 through FY 2019 are all adjusted by 

0.90 cents due to the methodology changes in FY 2020.
Docket No. SS2022-1 Appendix A

 Page 35 of 36

Caveats and Cautions for the Applied Adjustments

The report discusses the possible construction of a time series of the unit cost of flats 

products going back to FY 2008. Since the Postal Service provides an estimate of the 

impact of each of its proposed methodology changes, it is possible to produce a time 

series, by applying the calculated impact to the unit costs of flats products, going back in 

time. Whether such a series would be meaningful depends on the use to which it put and 

whether it would be subject to significant restrictive assumptions.

One such assumption is that the adjustments applied to the previous years’ unit costs are 

the appropriate ones, bearing in mind there is no unique procedure for choosing the 

adjustments. The restriction is that the adjustments derived from analysis of the current 

year are equally applicable to the prior years. This is problematic because the Postal 

Service produces the impact estimate in order to compare costs with and without the 

proposed methodological change in the current year, and not necessarily as long-term 

impacts.

The procedure for deriving an adjusted time series is straightforward: apply the 

adjustments to the unit costs and include impacts of all subsequent years’ local impacts, 

then adjust for inflation. There are three steps in constructing the time series:

• Construct a matrix of local impacts. In some cases, there are multiple impacts in a 

given year. In that case impacts are summed to present a unique effect for the fiscal 

year.

• Construct a matrix of global impacts, based on the local impacts described above. 

Each year’s total unit cost global impact would include the local impacts of all 

subsequent years.

• Such numbers, when also adjusted for inflation, constitute the desired time series of 

adjusted unit attributable costs that account for inflation and methodology changes. 

These time series of unit attributable costs are for each flats product, and they are 

referred to as real adjusted attributable unit costs.

The difference between the reported Cost and Revenue Analysis (CRA) unit cost and the 

real adjusted attributable unit cost is relatively small, usually is not higher than a few 

cents (assuming that the inflation level is low).
Docket No. SS2022-1 Appendix A

 Page 36 of 36

Changes to Products

Among the assumptions to which the time series would be subject are whatever 

modifications are made to produce some consistency in the list of products. Among such 

modifications are the date when a new product is offered, the fraction of the new 

product’s volume in the total mail volume, and the fraction of the product’s volume that is 

a result of a reduction in volume from pre-existing products.

The FY 2008 CRA introduces a line item under Standard Mail (currently USPS Marketing 

Mail) referred to as Not Flat-Machinables and Parcels.54 This category, which consists of 

parcel-shaped pieces that do not meet the eligibility standards for letters or flats, was 

present in the CRA through FY 2012.55 The construction of a time series would require an 

assumption on the source of such volumes, i.e., which of the other Standard Mail items 

would see a reduction because of the added category, and how this would impact the effect 

of the change on specific product costs. This Report assumes that the inclusion of Not FlatMachinables and Parcels had no impact on the volumes or costs of other categories of 

Standard Mail, and in particular that the local impact of cost methodologies on the flatshaped products would not change as a result of the additional category.

Similarly, USPS Marketing Mail Every Door Direct Mail—Retail (EDDM-R) is introduced as a 

product in FY 2013. Although targeted to new volume, it is not certain whether the source 

of EDDM-R volumes and costs comes from a reduction in other Standard Mail categories. 

The unit costs in a time series would be sensitive to the assumptions made regarding such 

inclusions or exclusions of cost categories featured in the CRA. Again, for simplicity, this 

Report assumes that the inclusion of EDDM-R does not change the impact of costing 

methodology changes on unit costs of other products.

54 Docket No. ACR2008, Library Reference USPS-FY08-1, December 29, 2008, file “USPS-FY08-1.doc”(FY 2008 Public CRA Report).

55 Docket No. ACR2008, United States Postal Service Annual Compliance Report, December 29, 2008.
Docket No. SS2022-1 Appendix B

 Page 1 of 2

Appendix B: Acronyms and Abbreviations

Acronym/Abbreviation Meaning

ACD Annual Compliance Determination

ACR Annual Compliance Report

ADC area distribution center

ADUS Automated Delivery Unit Sorter

AFSM Automated Flats Sorting Machine

AFSM - AI Automated Flats Sorting Machine with Automatic Induction 

Modification

AFSM - ATHS Automated Flats Sorting Machine with Automatic Tray Handler and 

Sorting Modification

AFSM - AI ATHS Automated Flats Sorting Machine with both AI and ATHS

APBS Automated Parcel and Bundle Sorter

APC All Purpose Container

APPS Automated Package Processing System

CETs Critical Entry Times

DDU destination delivery unit

DMM Domestic Mail Manual

DSE Degree of Scale Economies

DU delivery unit

eMIR Electronic Mail Improvement Reporting

EPPS Enhanced Package Processing System

FCM First-Class Mail

FSS Flats Sequencing System

FY Fiscal Year

HCR Highway Contract Route

IMb Intelligent Mail barcode

IOCS In-Office Cost System

LDC labor distribution code

LMI Last Mile Impact

MIA Mailer Irregularity Application

MMP Managed Mail Program

MODS Management Operating Data System

MPV Mail Processing Variance

NDC network distribution center
Docket No. SS2022-1 Appendix B

 Page 2 of 2

Acronym/Abbreviation Meaning

NDLL National Distribution Labeling List

NPA National Performance Assessment

OTR over-the-road container

P&DC processing and distribution center

PAEA Postal Accountability and Enhancement Act

PVS Postal Vehicle Service

RDC Regional Distribution Center

S&DC Sorting and Delivery Center

SPBSTS Small Package and Bundle Sorter Tracking System

SPPS Small Package Sorting System

STC Surface Transfer Center

SV Surface Visibility

TACS Time and Attendance Collection System

TRACS Transportation Cost System

USPS OIG United States Postal Service Office of Inspector General

WIP Work in Process
Docket No. SS2022-1 Appendix C

 Page 1 of 3

Appendix C: Glossary

A

Allied operations are mail processing activities that involve preparing the mail for pallet, bundle, or piece 

processing and include platform operations, such as unloading trucks and moving pallets to mail processing 

equipment.

Attributable costs include the sum of the volume-variable costs, product-specific costs, and those 

inframarginal costs calculated as part of the product’s incremental costs.

B

Bundle is a plastic-wrapped or banded group of presorted mailpieces.

Bundle breakage occurs when the material holding the flats bundle breaks.

C

Capacity is the sustainable maximum output—the greatest level of output a plant can maintain within the 

framework of a realistic work schedule after factoring in normal downtime and assuming sufficient 

availability of inputs to operate the capital in place.

Carrier route is a delivery route along which mail carrier delivers mail to individual addresses.

Casing involves placing mailpieces into separations that follow the sequence in which carriers deliver mail 

along carrier routes.

City route is a route of geographic locations within the boundaries of a delivery unit.

Compensatory product is a product whose revenues are greater than its attributable cost.

Contribution of a product or group of products is the product or group of products’ revenue minus its 

attributable cost.

Cost coverage of a product or group of products is the product or group of products revenue divided by the 

product or group of products attributable cost.

D

Degree of Scale Economies measures the degree to which the proportionate increase in the output 

induces less than the proportionate increase in the cost, with the effect that the cost per unit decreases.

Delivery point sequence is an order of delivery units that mail carrier follows as he/she delivers mail 

along a carrier route.

Distribution operations are mail processing activities that involve sorting mail into separate groups based 

on a common destination.

Downtime is the time machines are not operational during a run.
Docket No. SS2022-1 Appendix C

 Page 2 of 3

E

Excess capacity is calculated as one minus utilization and expressed as a percentage.

Extra transportation is short-term highway transportation, scheduled on an as-needed basis, to transport 

mail volumes that failed to be loaded on scheduled transportation.

I

Idle time is the time machines are not used outside of processing runs.

Incoming mail is mail received by a mail processing facility for distribution within its service area.

Incremental cost of a product is the total cost caused by adding that product to the Postal Service’s 

output mix.

Inframarginal costs of a product represent the difference between the incremental cost of the product 

and the sum of the volume-variable and product-specific costs of the product.

L

Labor productivity in a specific mail processing operation is the volume (number of mailpieces) processed 

during a workhour.

Last Mile includes all activities related to last mile operations that involve office time (when carriers are in 

a delivery unit preparing and manually sorting mail prior to delivery) and street time (when carriers are on 

the street actually delivering mail).

M

Managed mail program is a distribution system, which includes First-Class Mail, destinating in specific ZIP 

Codes.

Manual sorting is the sorting of mailpieces performed by hand.

Marginal cost of a mail product is the cost of the last unit produced (of that product) when the volumes 

of all other products are assumed constant. In the context of the Postal Service, the marginal cost of a 

mail product is calculated as the per-mailpiece volume-variable cost of that product.

N

Non-compensatory product is a product whose revenue is less than its attributable cost.

O

On-Time Arrival is a percentage of mailpieces arriving at the facility on time.

On-Time Departure is a percentage of mailpieces departing a facility on time.

Outgoing mail is mail received by a mail processing facility for sorting and dispatch to mail processing 

facility(ies) where mail destinates. Outgoing mail is also referred to as originating mail.
Docket No. SS2022-1 Appendix C

 Page 3 of 3

P

Pinch point(s) are functions where the Postal Service is not operating at maximum efficiency from a 

cost or service perspective. The Commission previously identified six pinch points related to flats 

processing and delivery: bundle processing, automated processing, manual sorting, allied operations, 

transportation, and last mile/delivery.

Product-specific costs represent costs that are not volume variable but, for certain products, are 

directly or indirectly caused by that product.

Productivity is the volume of mailpieces processed divided by hours in a specific mail processing 

operation. See also Labor productivity.

R

Rural route is a route serving delivery points outside the boundaries of a delivery unit.

S

Sort plan is a systematic plan for the distribution of mail to its destination according to ZIP Codes and 

delivery point codes. Schemes are classified by the types of separations made and/or the source of 

the mail worked.

Surface Visibility is a concept using barcode technology that allows the tracing of barcoded mail as it 

passes through automated and manual processes that scan the barcodes and capture the handling in 

real time by the piece, container, and trailer.

U

Unit attributable cost is attributable cost divided by volume.

Utilization is the actual number of pieces processed divided by the capacity in percentage.

V

Volume is the count of mailpieces.

Volume-variable costs are calculated by multiplying the total volume of the class or product by the 

unit costs (the change in total costs resulting from a one-unit change in its volume alone when the 

volumes of other products remain constant).

W

Workhour is one hour of work performed by a postal employee.