Executive summary, roadmap, 

and recommendations

October 25, 2022

Federal Committee on Statistical Methodology 

Ron Jarmin, U.S. Census Bureau

1
A Once-in-a-Generation Opportunity

American Rescue Plan (ARP) and Infrastructure Investment and Jobs 

Act (IIJA) provide unprecedented resources to improve America’s 

infrastructure and support economic resilience and long-term growth

• We need to:

• Ensure we’re using taxpayer dollars wisely and effectively

• Quickly and accurately aggregate data on program performance

• Leverage data as a strategic asset

• Enable evidence-based decision making

• Advance data sharing and collaboration opportunities

• Expand model beyond DOC and to future programs (such as CHIPS and Science Act of 2022) 

2
Department of Commerce 

Data Governance Working Group (DGWG)

Purpose: 

• To identify ways to collect incoming program performance information

• Minimize burden to aid recipients

• Maximize ability to report achievement of program goals and objectives

• Demonstrate lessons learned

• Improve program outcomes

• Foster adoption of promising practices

3
Participants

Members: 

• Department of Commerce (DOC) 

• U.S. Census Bureau (chair)

• Economic Development Administration (EDA)

• National Oceanic and Atmospheric Administration (NOAA)

• National Telecommunications and Information Administration (NTIA)

• National Institute of Standards and Technology (NIST)

• Bureau of Economic Analysis (BEA)

Advisors:

• Office of Management and Budget (OMB)

• Department of Transportation (DOT)

• Staff from the DGWG member agencies

4
Scope and phased deliverables

• Phase 1 (completed)

• Develop shared data structure and data quality standards to facilitate data 

linkages and reduce reformatting complications

• Describe strategies to ensure availability of high-quality data to support policy 

and program outcomes

• Phase 2 (started)

• Identify common metadata standards to ensure the DOC’s data can be 

leveraged as strategic asset

• Phase 3 (coming soon)

• Discuss strategies to address barriers to data collection/use

• Implement systems standards to ensure maximum interoperability at an 

enterprise level

5
DGWG Report

• “Best Practices for Monitoring and Evaluating the ARP, IIJA and other 

programs: Report of the Department of Commerce Data Governance 

Working Group”

• Available at: https://www.census.gov/about/what/evidence-act.html

• Report is the culmination of “phase 1” sprint, and:

• Establishes goal for program monitoring and evaluation

• Compares evaluations strategies

• Identifies data resources and linkage strategies

• Considers factors such as geographies, socioeconomic factors, equitable 

delivery, and environmental risk factors

6
Recommendations

• Agencies should follow all applicable standards issued by the Office of 

Management and Budget (OMB) for grant awardees to report on geographic 

locations of primary and secondary awardees, as well as the point of service 

delivery. The DGWG supports using census tracts as a standard reporting 

element. 

• Agencies should continue to measure and monitor program operations (e.g., 

timeliness, compliance with regulations) following or exceeding guidance from 

OMB and their respective agencies.

• Agencies should leverage existing impact projection models from industry, 

academia, or government where possible.

7
Recommendations

• Agencies should implement a measurement and evaluation design that 

emphasizes credible results within resource, cost, and schedule 

constraints. 

• Agencies should consider implementing large-scale observational studies 

that link program administrative data to previously collected data from 

censuses, surveys, administrative records, commercial vendors, and 

aggregated indices. The Census Bureau’s Data Linkage Infrastructure may 

be particularly useful. 

• Agencies should collect high-quality unique identifiers from aid awardees, 

including both primary and secondary awardees to enable linkage to other 

data sources.

8
Recommendations

• Agencies should evaluate programs based on the phase of program 

implementation, direct versus indirect program impacts, and 

projected versus observed program impacts

• Phases

• Program Design/Stand Up

• Pre-Award Program Implementation

• Post-Award Program Implementation

• Closeout

9
Recommendations

• Agencies should use metrics and available indices of economic and 

geographic vulnerability to determine the equity or bias in program 

delivery.

• Agencies should consider incorporating program impacts on the 

environment and climate resilience into their evaluation plans.

• Agencies should establish or participate in a working group to identify 

existing standards and best practices for managing program 

operations and evaluation data and develop guidance for use by data 

practitioners. 

• Agencies should create a community of practice to share lessons 

learned from program implementation and foster collaboration.

10
Direct program impacts (D) Indirect program impacts (I)

Phase Projected Observed Projected Observed

Program 

design/stand up

Identify direct impacts (D) and determine 

how to capture in NOFOs

Identify indirect impacts (I) and determine 

administrative/survey data to measure

Pre-award program 

implementation

What is potential 

benefit of D?

What is current 

(baseline) rate of D? 

What is potential 

benefit of I?

Baseline: What is 

current rate of I?

Post-award 

program 

implementation

Compare to initial 

projection of D; 

update projection of 

D based on observed

Compare to baseline 

levels of D

Compare to initial 

projection of I; 

update projection 

of I based on 

observed

Compare to baseline 

levels of I

Closeout Compare to projected 

levels of D (from each 

phase)

Compare to baseline 

levels of D and 

implementation 

levels of D

Compare to 

projected levels of I

(from each phase)

Compare to baseline 

levels of I and 

implementation levels 

of I

Framework for program evaluation

11
U.S. Census Bureau’s response

• Create a Center of Excellence

• Develop budget initiative to support “Evidence Building, Evaluations, 

and Improving Underlying Race/Ethnicity Data” (FY23 DOC budget)

12
Census Data 

Warehouse & 

Products

Data Consultations 

& Analytical 

Support

Holistic Reporting

Center of Excellence model

Provision central data management, enhancement service, and data products for 

decision support and program evaluation.

Collaborate with implementing bureaus to understand how they “define success” and 

consult on data tools to support their efforts. 

Evaluate DOC-wide success metrics, ensuring that the “whole” of DOC’s efforts are 

measured, rather than relying on a “sum of the parts” approach. 

Census Bureau support must be integrated at front end to coordinate data inputs 

supporting policy, implementation, compliance, and oversight decisions. 
Data should be used across program lifecycle

• Use data from past programs to establish goals, set 

baselines, and develop effective grant criteria to direct funds 

to intended recipients in early design phases

• Harness data throughout implementation phase to measure 

progress towards goals and possibly make changes to stay on 

track

• Evaluate data post-deployment to understand programmatic 

success and inform design of future programs

Early 

Decision 

Support

Ongoing Trend 

Identification

Post 

Deployment 

Evaluation

Data provide insights across lifecycle of program implementation, not just in late-stage evaluation.