FY 2013

ANNUAL PERFORMANCE 

REPORT 
TABLE OF CONTENTS

ITEM PAGE

STRATEGIC GOALS AND OBJECTIVES............................................................................1

PERFORMANCE RESULTS...................................................................................................2

PERFORMANCE GOAL INFORMATION............................................................................3

 STRATEGIC GOAL 1 .........................................................................................................6

 STRATEGIC GOAL 2 .........................................................................................................22

 STRATEGIC GOAL 3 .........................................................................................................40

 STRATEGIC GOAL 4 .........................................................................................................41

PRIORITY GOALS..................................................................................................................56

This Annual Performance Report provides information on performance achievements of the 

Department of Agriculture in Fiscal Year (FY) 2013. Excerpts from this document are posted on 

www.performance.gov.
STRATEGIC GOALS AND OBJECTIVES

1

Exhibit 1: USDA’s Strategic Planning Framework for FY 2013
PRIORITY GOALS 

2

The U.S. Department of Agriculture (USDA) had 43 performance goals in FY 2013. The funding 

and performance targets for FY 2013 were estimated in the FY 2014 Budget Summary and 

Annual Performance Plan which was released prior to final enactment of appropriations for the 

Department. The funding and performance target estimates were based on an annualization of 

amounts provided by the Continuing Appropriations Act, 2013 (P.L. 112-175). Therefore, the 

FY 2013 estimated numbers did not reflect the enacted funding levels for FY 2013 that included 

reductions for most programs affected by the March 1, 2013, sequestration as well as two 

separate across-the-board rescissions. FY 2013 targets were adjusted after enactment of 

FY 2013 appropriations to reflect funding provided by Congress. 

Exhibits 2 and 3 provide a summary of the Department’s year-end actual performance results. Of 

the 43 performance measures contained in USDA’s FY 2013 Annual Performance Plan, 36 (84 

percent) were met or exceeded and 7 (16 percent) were unmet. 

Exhibit 2: Fiscal Year 2013 Performance Results 

36 - Met or Exceeded

7 - Unmet

Met

Unmet
PRIORITY GOALS

3

Exhibit 3: Performance Goals Information

Strategic Goal 1: Assist Rural Communities to Create Prosperity So 

They are Self Sustaining, Repopulating, and Economically Thriving

Strategic Objectives Annual Performance Goals Result

1.1 Enhance Rural 

Prosperity

Number of jobs created or saved through USDA’s financing of 

businesses Exceeded

Number of borrowers/subscribers receiving new or improved 

telecommunication services (millions) Exceeded

1.2 Create Thriving 

Communities

Population receiving new or improved service from agency-funded 

water and wastewater facilities or projects (millions) Exceeded

Homeownership opportunities provided Met

Percentage of customers who are provided access to new and/or 

improved essential community facilities

Health Facilities Exceeded

Safety Facilities Exceeded

Educational Facilities Exceeded

Number of borrowers/subscribers receiving new and/or improved 

electric facilities (millions) Exceeded

1.3

Support a Sustainable 

and Competitive 

Agricultural System

Percentage direct and guaranteed lending to socially disadvantaged 

farmers (SDA) Met

Percentage direct and guaranteed lending to beginning Farmers Exceeded

Maintain or increase percentage of Farm Service Agency program 

delivery applications at USDA Service Centers that are Web 

enabled

Met

Value of trade preserved through resolution of foreign market 

access issues such as U.S. export detainment, restrictive 

sanitary/phytosanitary and technical barriers to trade issues, and 

trade regulations ($billions) 

Met

Value of agricultural exports resulting from participation in foreign 

food and agricultural trade shows ($billions) Exceeded

Value of Federal Crop Insurance Corporation (FCIC) risk protection 

coverage provided through FCIC-sponsored insurance ($billions) Exceeded

Normalized value of FCIC risk protection coverage provided 

through FCIC-sponsored insurance ($billions) Exceeded

Percent of industry compliance with the Packers and Stockyards Act Exceeded
PRIORITY GOALS

4

Exhibit 3: Performance Goals Information (continued)

Strategic Goal 2: Ensure Our National Forests and Private Working Lands Are 

Conserved, Restored, and Made More Resilient to Climate Change, While Enhancing Our 

Water Resources

Strategic Objectives Annual Performance Goals Result

2.1

Restore and Conserve the 

Nation’s Forests, Farms, 

Ranches, and Grasslands

Conservation Reserve Program: Restored wetland acreage (millions of 

acres) Unmet

Conservation Technical Assistance: Cropland with conservation 

applied to improve soil quality (millions of acres) Met

Environmental Quality Incentives Program: Cropland with 

conservation applied to improve soil quality (millions of acres) Met

Conservation Technical Assistance: Grazing land and forest land with 

conservation applied to protect and improve the resource base (millions 

of acres) 

Met

Environmental Quality Incentives Program: Grazing land and forest 

land with conservation applied to protect and improve the resource 

base (millions of acres) 

Exceeded

Farm and Ranch Lands Protection Program: Prime, unique, or 

important farmland protected from conversion to non-agricultural uses 

by conservation easements (thousands of acres) 

Unmet

Wildlife Habitat Incentive Program: Non-Federal land with 

conservation applied to improve fish and wildlife habitat quality 

(millions of acres) 

Unmet

Environmental Quality Incentives Program: Non-Federal land with 

conservation applied to improve fish and wildlife habitat quality 

(millions of acres) 

Unmet

Number of communities with urban and community forestry programs 

resulting from Forest Service assistance (number of communities) Met

Annual acres of public and private forest lands restored or enhanced 

(millions of acres) Met

Volume of timber sold Met

2.3 Protect and Enhance 

America’s Water 

Resources

Conservation Technical Assistance: Land with conservation applied to 

improve water quality (millions of acres) Met

Environmental Quality Incentives Program: Land with conservation 

applied to improve water quality (millions of acres) Met

Wetlands Reserve Program: Wetlands created, restored, or enhanced 

(thousands of acres) Unmet

2.4 Reduce Risk from 

Catastrophic Wildfire and 

Restore Fire to its 

Appropriate Place on the 

Landscape

Acres of Wildland-Urban Interface fuels treated to reduce the risk of 

catastrophic fire (millions of acres) Exceeded

Percentage of acres treated in the Wildland-Urban Interface that have 

been identified in Community Wildfire Protection Plans Exceeded
PRIORITY GOALS

5

Exhibit 3: Performance Goals Information (continued)

Strategic Goal 3: Help America Promote Agricultural Production and 

Biotechnology Exports as America Works to Increase Food Security

Strategic Objectives Annual Performance Goals Result

3.2 Enhance America's 

Ability to Develop and 

Trade Agricultural 

Products Derived from 

New Technologies

Cumulative number of genetically engineered plant lines reviewed 

by the U.S. Department of Agriculture and found safe for use in the 

environment

Exceeded

Strategic Goal 4: Ensure That All of America’s Children 

Have Access to Safe, Nutritious, and Balanced Meals

Strategic Objectives Annual Performance Goals Result

4.1 Increase Access to 

Nutritious Foods

Participation rates for the major Federal nutrition assistance 

programs (millions per month): Supplemental Nutrition Assistance 

Program (SNAP)

Met

SNAP payment accuracy rate (percent) Met

Participation levels for the major Federal nutrition assistance 

programs (millions per day):

National School Lunch Program Met

School Breakfast Program Met

Participation levels for the major Federal nutrition assistance 

programs (millions per month): The Special Supplemental 

Nutrition Program for Women, Infants, and Children (average)

Met

4.2 Promote Healthy Diet and 

Physical Activity Behavior

Application and usage level of nutrition guidance tools (billions of 

pieces of nutrition guidance distributed) Exceeded

4.3 Protect Public Health by 

Ensuring Food is Safe

Percent of broiler plants passing the carcass Salmonella

Verification Testing Standard Unmet

Total illnesses from all Food Safety and Inspection Service 

products Unmet

Percent of establishments with a functional food defense plan Exceeded

4.4

Protect Agricultural Health 

by Minimizing Major 

Diseases and Pests, 

Ensuring Access to Safe, 

Plentiful, and Nutritious 

Food

Value of damage prevented and mitigated annually as a result of 

selected plant and animal health monitoring and surveillance efforts 

($billions)

Exceeded
PRIORITY GOALS

6

Strategic Goal 1: Assist Rural Communities to Create Prosperity So They 

Are Self-Sustaining, Repopulating, and Economically Thriving

Objective 1.1: Enhance Rural Prosperity

Number of jobs created or saved through USDA financing of businesses

Analysis of Results

USDA exceeded the target for this performance measure by more than 12 percent. The 

Department’s efforts to create and save jobs included the following:

Funding projects of highest priority, which is reflected when jobs are created and saved, 

while emphasizing quality production in loan and grant making;

Emphasizing the importance of correlating the data used in priority scoring applications with 

those used in reporting performance measures;

Providing additional guidance and training to agency field offices to reinforce Guaranteed 

Loan System (GLS) data integrity, combined with weekly monitoring by the national 

office; and

Extending the processing time for grants of $20,000 or less from 15 to 60 days, thereby 

ensuring a more comprehensive agency review.

Exhibit 4: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.1.1 Number of jobs created 

or saved through USDA 

financing of businesses

N/A N/A N/A 64,935 52,468 39,612 44,419 Exceeded

Allowable Data Range for Met: The tolerance range for the measure to be “met” is 5 

percent. 

Completeness of Data — Business program data are considered final and complete.

Reliability of Data — Data for jobs created or saved are obtained by State office staff from 

borrowers and lenders. They are entered into the GLS when obligations are recorded. Overall, 

the data on jobs created and saved are reliable. 

Quality of Data — The quality of the data on jobs created and saved is satisfactory.

Challenges for the Future

While rural communities are diverse and their economic challenges vary based on the condition 

of the industries that drive their economies, generally speaking, for more than a decade, those 

that rely heavily on the manufacturing and agricultural industries have struggled to remain 

competitive in the global economy. Furthermore, rural areas typically have underdeveloped 

public services that make it difficult to attract or retain businesses. The persistent lack of wellpaying job opportunities and the related local tax base ramifications place many rural county and 

municipal governments under great stress.
PRIORITY GOALS

7

Number of borrowers/subscribers receiving new or improved telecommunication services

Analysis of Results

USDA exceeded the target for this performance measure. It should be noted the performance 

measure targets for these programs were lower than previous years because in FY 2012 and 

FY 2013, loan demand continued to be affected by changes made by the Federal 

Communications Commission (FCC) to rules governing Universal Service Fund (USF) and 

inter-carrier compensation (ICC) distributions to rural carriers in 2012.

The level of uncertainty caused by the USF and ICC revisions directly impacted the level of 

demand for the infrastructure loan program. Consequently, the program did not obligate all 

available funding in FY 2013. However, infrastructure loans that were approved proposed 

serving more subscribers than forecasted, resulting in the agency being able to meet the 

performance goal for this program.

Exhibit 5: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.1.2 Number of 

borrowers/subscribers 

receiving new or 

improved 

telecommunication 

services (millions)

0.78 0.19 0.14 0.18 0.06 0.09 0.119 Exceeded

Allowable Data Range for Met: Annual targets for this measure are based on historic

activity and adjusted according to the program level received each fiscal year. The allowable 

data range for this measure to be considered met is +/– 7 percent.

Completeness of Data — Data are actual, final, and complete. The subscriber data are 

collected from each approved loan application. Applicants are required to detail their proposed 

service territories and subscribers. Loan funds are advanced only for approved purposes. The 

data on the number of subscribers to be served for each loan are derived from applicants’ loan 

applications. Data must be complete before loans can be approved. 

Reliability of Data — While in many cases applicants are required to perform market surveys 

of their proposed service areas, the actual subscribers served may vary from the plan if all 

funds are not used, or the borrower later requests a change of purpose from the original loan 

application. Overall, data on subscribers are reliable.

Quality of Data — All applications undergo an extensive review to determine eligibility.

Additionally, all approved applications must show feasibility from a financial and technical 

standpoint. Applicants also are required to perform market surveys of their proposed service 

areas. Therefore, the data are reliable. As previously noted, the data on the number of 

subscribers to be served for each loan approved come from the applicant’s loan application. 

The data depend on the borrower drawing down loan funds and constructing the system as 

portrayed in the applicant’s loan design. Loan funds may be used only for the approved 

purposes for which the loan was made. Variance may result if a borrower does not draw down 

all loan funds or request approval for a change of purpose from the original loan. This could 

result in a different number of subscribers from the number specified in the plan.
PRIORITY GOALS

8

Challenges for the Future

USDA’s telecommunications program portfolio rose by more than $3 billion in American 

Reinvestment and Recovery Act of 2009 (ARRA) funding. The hundreds of new ARRA 

broadband projects must be monitored to ensure the projects’ completion within the required 

timeframe. The Department will coordinate with the FCC as it implements the National 

Broadband Plan and USF regulations. USDA must incorporate existing and proposed USF 

program changes into its underwriting process and determine the impact on its loan portfolio. 

The Department must also evaluate the impact of USF program changes and uncertainty in the 

industry on demand for telecom loan programs in the next few years.

Objective 1.2: Create Thriving Communities

Population receiving new or improved service from agency-funded water and wastewater 

facilities or projects

Analysis of Results

USDA exceeded the target for this performance measure. Communities awarded loans and grants 

had an average population of 3,531 residents. Priority is given to communities with populations 

of 5,500 or fewer.

Exhibit 6: Performance Goal Results

Annual Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.2.1 Population 

receiving new or 

improved service 

from agencyfunded water and 

wastewater 

facilities or 

projects (millions)

3.4 1.9 3.4 2.9 2.5 1.4 1.8 Exceeded

Allowable Data Range for Met: The allowable data range for this measure to be considered 

met will be +/- 5 percent.

Completeness of Data — The Water and Environmental Programs (WEP) collect data initially 

through the Community Programs Application Processing (CPAP) system. CPAP is a nonfinancial system in which agency field staff input data about applicants, borrowers, funding, 

and services provided. The data obligations flow through the Commercial Loan Servicing 

System to the Program Loan Accounting System, and through a data server to a data 

warehouse.

Reliability of Data — USDA’s data warehouse stores historical information on Department 

programs and such non-agency data as census information. Program data are downloaded to the 

warehouse every evening from several accounting databases. Data generally are current through 

the previous day. The warehouse provides data about obligations and can be used to measure 

the number of loans, loan amounts, number of borrowers, and funds advanced. The warehouse 

is an easy, accessible online method of extracting information and data for reports and analyses.

Quality of Data — Based on information in CPAP, the population receiving new or improved 

water or wastewater service can be extrapolated from the data warehouse. The WEP national 
PRIORITY GOALS

9

office and USDA field offices use data from CPAP, the data warehouse, and Department 

accounting systems to review or evaluate the financial, operational, and managerial programs of 

the utilities serving rural customers.

Challenges for the Future

Rural communities must invest in modern water and wastewater facilities to attract families and 

businesses vital to thriving communities. The communities must decide how to balance investing 

in new facilities to serve new or proposed customers with investing in upgrades to facilities that 

serve existing customers. They must weigh growing their customer base, controlling costs, and 

modernizing or upgrading aging facilities. Gaining access to credit markets and leveraging funds 

from Federal, State, and private sources will continue to challenge rural communities.

Homeownership Opportunities Provided

Analysis of Results

USDA met its homeownership target by providing over 170,000 funding opportunities in 

FY 2013 which was an 11 percent increase over the record achievements of FY 2012. 

In January 2013, the President expanded the Rural Refinance Pilot loan initiative, adding 15 

states, as well as Puerto Rico to the original 19 hardest hit states.

This initiative allows existing USDA direct and guaranteed loan customers in the pilot-eligible 

areas to take advantage of lower interest rates by providing our customers with streamlined 

refinancing opportunities which do not require current credit reports, appraisals or property 

inspections. As a result, rural homeowners were able to lower their monthly costs, and reduce 

the likelihood of default, which is profoundly disruptive to households and can ultimately impact 

taxpayers, as well.

Exhibit 7: Performance Goal Results

Annual Performance 

Goals, Indicators 

and Trends

2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.2.2 Homeownership 

opportunities 

provided 

56,613 127,735 140,100 153,027 183,303 170,055 Met

Allowable Data Range for Met: Historically, the number of homes financed by the Guaranteed 

and Direct Single Family Housing Loan Programs have varied. The allowable data range for this 

measure to be considered “Met” is +/- 20 percent.

Completeness of Data- Homeownership data are complete and final. Homeownership data are 

entered in the Web-based Dedicated Loan Origination and Servicing (DLOS) system. This 

centralized server application ensures viable data collection. DLOS tracks performance and can 

be used to forecast needs. Information is entered into UniFi and uploaded nightly to 

MortgageServe System. This system obligates funds, establishes closed loans, administers 

escrow accounts, and performs other administrative functions. Hyperion, a query and reporting 

tool, serves as the interface between the data warehouse and USDA staff.
PRIORITY GOALS

10

Reliability of Data- Homeownership data originate in systems used to obligate funding and are 

reliable. Data for initial placement of households into their own home are reliable. They are 

linked directly to homeownership loans maintained in USDA’s financial accounting systems. 

No adjustments are made for later defaults and the resulting loss of homeownership.

Quality of Data- Homeownership data are based on loan obligations collected in DLOS, and 

stored in USDA’s data warehouse. Thus, the data on the number of households are auditable. 

Data represent the popultion served based on the available U.S. Census Data.

Challenges for the Future

Demand for the single family loan programs remains strong. USDA’s most pressing challenge is 

the management of its increased loan volume with reduced staffing levels. 

The guaranteed program has also taken dramatic steps toward leaner, more efficient operation 

with its emphasis on increased automation and process reengineering. In FY 2013, the program 

embarked on a three-phase Signature Process Improvement effort to eliminate the paperintensiveness associated with the traditional processing of loan applications and issuance of 

conditional commitments and loan guarantees. Once fully operational, the newly automated 

processes will eliminate the need for the printing and signing of physical loan documents. 

Percentage of customers who are provided access to new and/or improved essential community 

facilities

Analysis of Results

Community Programs (CP) has chosen health care; fire/rescue and public safety facilities; and 

education facilities as proxies for measuring the program’s effectiveness. These three areas have 

historically been the areas of greatest demand for funding. In FY 2013, CP exceeded the targets 

in each of its performance measures. 

Exhibit 8: Performance Goal Results

Annual Performance Goals, 

Indicators 

and Trends

2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.2.3 Percentage of customers who 

are provided access to new 

and/or improved essential 

community facilities 

Health Facilities

Safety Facilities

Educational Facilities

5.4

5.0

3.5

3.2

3.2

3.8

3.2

3.2

3.8

7.3

3.7

6.4

4.5

2.7

4.0

5.4

3.4

9.3

Exceeded

Exceeded

Exceeded

Allowable Data Range for Met: Results within 0.2 points on either side of the target are 

considered met.
PRIORITY GOALS

11

Completeness of Data- Program data are complete and final. The Finance Office records and 

reports total loan and grant obligations as of the date of obligations. Additionally, USDA 

collects information for management and evaluation purposes. Data on delinquencies are 

reported by the Finance Office for CF direct loans, and by lenders for CF guaranteed loans.

Reliability of Data -- CF data are entered into the Guaranteed Loan System (GLS) and the 

Commercial Loan Application Processing system (CPAP) by field staff as the program funds are 

obligated. GLS and CPAP are official accounting and financial management systems of the 

Department’s. These data are final, complete, and reliable. They include the population served 

based on available U.S. census information. The service area for each facility is based on 

estimates. The Department screens the data regularly for irregularities. Given the variety of 

areas served by different types of community facilities, estimating the service is not a precise 

science. Population estimates are based on engineering studies used for the design of new or 

expanded facilities. USDA is developing mapping technologies to improce this process.

Quality of Data- Data are projected on historical performance. The target information uses data 

dependent upon the baseline projections from other agencies in the Departmental.

Challenges for the Future

The CF program is experiencing significant servicing challenges due to: increased demand for 

large, complex community infrastructure investments (hospital replacements, new school 

districts, port modernizations, bridges, etc.); and the number and dollar amount of loans in the 

portfolio which have more than doubled in the past 7 years. This onset of servicing issues is 

compounded by the economic challenges in rural America. Economic conditions have forced 

many non-profits into bankruptcy and loan defaults. Likewise, local governments are 

experiencing decreased revenue also resulting in loan defaults (e.g. a rural hospital district closed 

its doors during construction). 

The ever-increasing cost and complexity of many facilities, especially in health care and 

education, also pose a challenge. Many rural communities are, by definition, small with a 

limited (and often dwindling) population, and often, a limited tax base. It will be a challenge for 

them in the future to find ways to maintain quality services, with up-to-date technology, while 

keeping costs affordable, all of which will be vital as capital markets remain unavailable for most 

rural communities.

Number of borrowers/subscribers receiving new and/or improved electric facilities

Analysis of Results

USDA exceeded the target for this performance measure by almost 43 percent. Department 

electric loans help borrowers provide new or improved electric service to more than 8.7 million 

retail consumers. At the end of FY 2013, USDA estimates that there were approximately $2 

billion in pending loan applications on hand for FY 2014, which were under National 

Environmental Policy Act (NEPA) reviews and other required pre-loan evaluations.

The Department has approved over $1 billion in loans for renewable electricity generation in 

rural areas since 2009. In December 2013, USDA published final rules for the new Energy 

Efficiency and Conservation Loan Program. This program will help borrowers finance customer 

energy efficiency improvements. USDA continued its commitment to deployment of smart grid 

technologies by providing over $151 million in new loans for smart grid technologies. More 
PRIORITY GOALS

12

than $3 billion of new investments in improved electric transmission and distribution facilities 

was approved in FY 2013.

Exhibit 9: Performance Goal Results

Annual Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.2.4 Number of 

borrowers/ 

subscribers 

receiving new

and/or improved 

electric facilities

(millions)

8.1 9.8 9.4 7.1 8.3 6.1 8.7 Exceeded

Allowable Data Range for Met: The allowable data range for this measure to be considered 

met will be +/- 5 percent.

Completeness of Data — The electric program’s performance data are collected from various 

agency documents, including agency Form 740c, Borrower’s Statistical Profile, Information 

Publication 201-1, borrower annual operating reports, and loan applications. The data are 

complete and accurate, and collected at the time of loan approval and/or reported annually. 

Reliability of Data — First-time loan applicants must submit extensive financial and electric 

system data in support of their loans. Existing borrowers are required to report financial and 

operating data annually to the agency. The data are used to administer Department loan funds 

and ensure the security of the loans. Borrower information and loan and grant obligations and 

advances are tracked in the Commercial Loan Servicing System. Borrower financial and 

system reports and information are collected and maintained through the data collection 

system in the Rural Development data warehouse.

Quality of Data — Performance goal data on the number of borrowers receiving new or 

upgraded electric service are derived from information in loan applications and annual reports. 

All applications are reviewed for compliance with all eligibility requirements for the various 

electric programs’ loans, guarantees, and grants. All approved applications must demonstrate 

financial feasibility and adequate loan security. Loan funds may be used only for approved 

purposes for which the loan was made. Borrower loan applications and annual submissions are 

reviewed by field representatives and Headquarters staff for completeness and accuracy and 

are subject to audit by program accounting staff.

Challenges for the Future

Rural electric providers face many challenges and uncertainties because of economic conditions, 

as well as new environmental and energy policy initiatives that could increase retail rates. The 

availability of low-cost financing through the electric program helps moderate those cost 

impacts.

Since FY 2007, the electric program has not approved any loans for new baseload electric 

generation to meet future needs or replace aging plants. USDA anticipates that borrowers will 

have to make substantial investments in new electric transmission lines, new generation capacity,

and pollution controls on existing plants to meet customer demand growth in an economic 

recovery, replacing aging plants in the near future. The Department has experienced a reduction 

in loan requests, reflecting the broader economic slowdown and deferred investment in utility 
PRIORITY GOALS

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plants. Trends in loan volume are expected to reverse, placing additional demands on the 

program. Meeting customer needs with limited program staffing and resources will be a 

challenge as major new projects will require detailed reviews to comply with NEPA.

Objective 1.3: Support a Sustainable and Competitive Agricultural System 

Percentage direct and guaranteed lending to socially disadvantaged farmers (SDA)

Analysis of Results

FSA accomplished its goal for lending to SDA farmers and ranchers in FY 2013. The 

percentage of SDA farmers and ranchers nationwide (per the 2007 Census of Agriculture) that 

have credit through the FSA direct and guaranteed loan programs increased to 13.6 percent. The 

newly implemented Microloan program, which expands the potential customer base for FSA 

operating loans by offering a streamlined application process and modified eligibility and 

security requirements, directly contributed to the Agency's ability to meet this goal. Of the 3,433 

microloans obligated in FY 2013, 1,270 were to minority and women farmers. As of September 

30, 2013, FSA has more than 18,750 SDA customers in its loan portfolio. During FY 2013, FSA 

issued more than 7,100 direct and guaranteed loans to SDA farmers, a 9 percent increase in loan 

volume from the previous fiscal year. The year over year increase in SDA lending is significant 

given that overall FSA lending declined slightly in FY 2013 in comparison to FY 2012.

Exhibit 10: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.3.1 Percentage direct 

and guaranteed 

lending to socially 

disadvantaged

farmers (SDA)

12.2 12.7 12.9 13.1 13.3 13.3 13.6 Met

Allowable Data Range for Met: +/-0.5 

Completeness of Data — The FY 2013 result is based on actual final data.

Reliability of Data — FLP data is considered reliable. A limitation is that Ag Census data is 

only updated every 5 years (current results based on data from the 2007 Ag Census). With the 

release of the 2012 Ag Census FSA will reevaluate the measure and targets.

Quality of Data — FLP data are of high quality. Most FLP data originate from accounting 

systems, which are subject to Office of Inspector General audit. FLP data are collected for 

multiple purposes and gathered throughout the normal lending process.
PRIORITY GOALS

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Challenges for the Future

The U.S. agricultural sector continues to change. Farms are growing and becoming increasingly 

dependent on technology. Thus, entry into farming is much more capital intensive. Farm 

operating costs also continue to rise, resulting in significant barriers and challenges for the 

groups that USDA Farm Loan Programs (FLPs) are intended to assist.

USDA has implemented multiple FLP process improvement initiatives in recent years, resulting 

in improved operational effectiveness and efficiency. Additional process improvement 

initiatives are underway; these are increasingly important as program demand remains strong and 

program resources are expected to be flat or decline in the coming years. Process improvement 

efforts will help ensure continued high-quality service for farmers and ranchers, allowing the 

Department to achieve program goals and objectives. 

Percentage direct and guaranteed lending to beginning farmers

Analysis of Results

FSA met its FY 2013 goal for providing credit assistance to beginning farmers. At the end of FY 

2013, 70 percent of beginning farmers and ranchers (based on the 2007 Census of Agriculture) 

had agricultural credit through FSA's direct and guaranteed loan programs. FSA obligated 

nearly 15,600 operating loans and farm ownership loans to beginning farmers, which were 

valued at greater than $1.7 billion. FSA's Microloan program, a direct operating loan with a 

maximum loan amount of $35,000 and simplified application process specifically designed to 

meet the needs of SDA and beginning farmers, as well small family farms and niche operations, 

directly contributed to accomplishment of this performance goal. Microloans were implemented 

in January 2013 and by the end of FY 2013 FSA had obligated 2,336 microloans to beginning 

farmers. These loans were valued at more than $44.6 million and represented 67% of all 

Microloans obligated. Perhaps most importantly, 1,887 microloans were issued to first time FSA 

customers. As of September 30, 2013, FSA had nearly 42,500 beginning farmers in its direct 

and guaranteed loan portfolios.

Exhibit 11: Performance Goal Results

Annual Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.3.2 Percentage direct 

and guaranteed lending 

to beginning farmers 

45.2 49.5 60.3 64.9 68.8 67.9 70.0 Exceeded

Allowable Data Range for Met: +/-0.5

Completeness of Data — The FY 2013 result is based on actual final data.

Reliability of Data —FLP data is considered reliable. A limitation is that Ag Census data is 

only updated every 5 years (current results based on data from the 2007 Ag Census). With the 

release of the 2012 Ag Census FSA will reevaluate the measure and targets.

Quality of Data — FLP data are of high quality. Most FLP data originate from accounting 

systems, which are subject to Office of Inspector General audit. FLP data are collected for 

multiple purposes and gathered throughout the normal lending process. 
PRIORITY GOALS

15

Challenges for the Future

The U.S. agricultural sector continues to change. Farms are growing and becoming increasingly 

dependent on technology. Thus, entry into farming is much more capital intensive. Farm 

operating costs also continue to rise, resulting in significant barriers and challenges for the 

groups that USDA Farm Loan Programs (FLPs) are intended to assist.

USDA has implemented multiple FLP process improvement initiatives in recent years, resulting 

in improved operational effectiveness and efficiency. Additional process improvement 

initiatives are underway; these are increasingly important as program demand remains strong and 

program resources are expected to decline in the coming years. Process improvement efforts 

will help ensure continued high-quality service for farmers and ranchers, allowing the 

Department to achieve program goals and objectives.

Maintain or increase percentage of Farm Service Agency (FSA) program delivery applications 

at USDA Service Centers that are web-enabled

Analysis of Results

USDA met its target for this performance measure. Web-enabled applications allow users to 

access the information systems applications via standard web browsers. Web modernization 

projects delivered in FY 2013 included MIDAS capability which integrated previously separate 

customer information, farm records, and farm geographic boundary management tools into a 

single platform to improve customer service at USDA Service Centers. Additional Noninsured 

Crop Disaster Assistance Program (NAP) and conservation program processes were provided on 

the web. 

Exhibit 12: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.3.3 Maintain or 

increase 

percentage of FSA 

program delivery 

applications at 

USDA Service 

Centers that are 

Web enabled

54 51 57 68 72.7 77 78.2 Met

Allowable Data Range for Met: The allowable data range is +/- 5 percent

Completeness of Data — Data reported are final results for the fiscal year. The FSA System 

Inventory Report includes all systems used by FSA for delivering its assigned missions. An active 

stewardship process is in place to ensure that new or retired systems are promptly recorded.
PRIORITY GOALS

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Challenges for the Future

USDA is retiring or replacing applications that depend on a previously used system that is now 

obsolete. Applications are targeted for modernization to the web and MIDAS. The archiving of 

all historical data and the full decommissioning of the hardware is expected to span beyond 

FY 2014. 

Value of trade preserved through resolution of foreign market access issues such as U.S. 

export detainment, restrictive sanitary and phytosanitary and technical barriers to trade issues, 

and trade regulations

Analysis of Results

USDA met the target for this performance measure. Barriers created by SPS or TBT limit 

exports and impose additional costs on exporters that can range from a few thousand to billions 

of dollars. These barriers reduce farm income and prevent job growth in the U.S. agricultural 

sector. The Department measures the value of trade preserved by resolving trade barriers arising 

from SPS and TBT measures imposed by international Governments. Trade issues and their 

impact on U.S. exports depend primarily on international action. Sometimes this action is in 

response to domestic events such as a livestock disease outbreak. Both the problems and the 

solutions are difficult to predict. Solutions can range from a quick agreement with officials at the 

port of entry, to a long negotiation process followed by a lengthy regulatory or legislative 

process in the importing country. 

Although USDA can establish priorities in advance for known barriers, unforeseen events will 

occur that require realigning priorities. In addition, volatile exchange rates affect the results 

reported for this measure.

Reliability of Data — Data are considered reliable. The measurement process involves counting 

the number of web-enabled program delivery applications used in the service centers identified in 

the FSA Systems Inventory Report. That number is then divided by the total number of program 

delivery applications used in the Service Centers to calculate the percentage of these program 

delivery applications that are web-enabled. The report is updated weekly. The numerator is the 

number of web-enabled program delivery applications used at USDA service centers. The 

denominator is the total number of Service Center program delivery applications in use.

Quality of Data — The FSA Systems Inventory Report is derived from the MEGA Enterprise 

Architecture Repository. The data are reviewed regularly by the system custodians. Changes are 

approved by a change control board and incorporated prior to the developing and reporting of this 

measure.
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Exhibit 13: Performance Goal Results

Challenges for the Future

Meat and poultry exports continue to be hampered by a variety of unjustified SPS barriers 

including those related to animal diseases (e.g., bovine spongiform encephalopathy [BSE] and 

avian influenza), maximum residue limits (MRLs) for veterinary drugs, zero-tolerance pathogen 

standards, and onerous slaughter and processing plant requirements, particularly international 

insistence on plant-by-plant approvals. Many of these problems manifest themselves in 

international export certification requirements that are not science based or consistent with 

international guidelines. 

Trade barriers related to biotechnology also require continual attention from USDA as U.S. 

development and approval of biotechnological innovations in agriculture often outpace 

international approvals. To date, the most broadly accepted new technology has been genetically 

engineered (GE) crops (soybeans, corn, and cotton) and products derived from these crops (oils, 

meal, and feed). Together, they comprise about one-third of total U.S. agricultural exports. In 

addition, it is estimated that some 80 percent of processed foods sold in the United States contain 

ingredients from GE crops. 

Finally, country-by-country variation in MRLs for pesticides poses a significant ongoing risk to 

U.S. fruit and vegetable exports to many countries. As with biotechnology, while the 

United States is a global leader in developing and approving safer and more effective pesticides, 

their approval in other countries and by Codex (which has made immense progress in recent 

years in streamlining the MRL review process) often lags behind the United States. The variation 

in approved pesticides between trading partners appears to be growing, increasing the potential

Annual Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.3.4 Value of trade 

preserved through 

resolution of foreign 

market access issues 

such as U.S. export 

detainment, 

restrictive SPS and 

TBT issues, and trade 

regulations 

($billions). 

N/A N/A 4.1 4.1 3.7 3.7 3.8 Met

Allowable Data Range for Met: Data assessment metrics to meet the target allow for an 

actual number in the range $3.6-4.0 (billions).

Completeness of Data: USDA uses a performance tracking system to collect and analyze 

actual performance data. The data are collected from the Department’s network of overseas 

offices and headquarters staff. The staff conducts trade compliance and enforcement activities, 

and provides trade negotiation support to the U.S. Trade Representative

Reliability of Data: Data are reliable and used by agency officials to highlight successes in the 

trade policy arena.

Quality of Data: In addition to audits and internal control review of the performance tracking 

system, an established procedure is maintained to verify each reported success and prevent 

double counting.
PRIORITY GOALS

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for disruption to U.S. agricultural trade as new pesticides are introduced. Specialty crop products 

have a particularly high risk of incurring MRL violations because they require extensive pest 

control measures.

Value of agricultural exports resulting from participation in foreign food and agricultural 

trade shows

Analysis of Results

USDA exceeded the target for this performance measure. One-third of all U.S. agricultural cash 

receipts come from export sales, making economic well-being of rural America heavily 

dependent on international trade. U.S. farmers and ranchers are among the world’s most 

productive and efficient. However, they face complex and unfair obstacles in the global 

marketplaces where 95 percent of the world’s consumers live. A comparative effort with the U.S. 

industry is needed to ensure the U.S. producers have fair market access, a strong understanding 

of key market trends, and support in overcoming constraints such as tight credit in international 

markets. 

USDA supports U.S. industry efforts to build, maintain, and expand overseas markets for U.S. 

agricultural, fish and forest products. FAS manages several export development programs that 

provide matching funds to U.S. non-profit organizations to conduct a wide range of activities 

including market research, consumer promotion, trade services, capacity building and market 

access support. 

FAS staff around the world support industry efforts by providing market intelligence and 

introducing U.S. exports to potential foreign customers. FAS Trade Services Staff, overseas 

office and cooperators all provide services that help U.S. companies successfully access potential 

buyers in wide-range of international trade shows. In FY 2013 over 1,050 U.S. companies and 

organizations participated in 29 USDA-endorsed trade shows in 19 countries. Trade show 

participation is key component of Small and Medium Enterprises program participation and 

cornerstone of cooperators’ investments. 

Exhibit 14: Performance Goal Results

Annual Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.3.5 Value of agricultural 

exports resulting 

from participation in 

foreign food and 

agricultural trade 

shows ($billions)

0.81 0.77 1.07 1.12 1.26 1.28 1.46 Exceeded

Allowable Data Range for Met: The allowable data range is +/- 0.1

Completeness of Data: Data are through September 30, 2013.

Reliability of Data: Data are self-reported but are considered reliable, good quality and used by 

agency officials to highlight in the trade promotion area.
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Challenges for the Future

The economic fragility of the European Union, the political unrest in the Middle East, and the 

slowdown in the Chinese economy, all can have a detrimental impact on the export results of 

market development programs, including dampening U.S. company sale prospects at 

international shows. 

Value of Federal Crop Insurance Corporation (FCIC) risk protection coverage provided 

through FCIC-sponsored insurance

Analysis of Results

USDA exceeded the target for this performance measure. The high commodity prices observed 

in 2012 persisted into the spring of 2013. High commodity prices directly increase the total value 

of risk protection provided. The total amount of planted acres for the major crops, and proportion 

of planted acres covered by insurance, both increased compared to last year. USDA also 

expanded a new program that allows growers in selected crops and counties to adjust their 

insurance guarantees to reflect long-term yield trends. This change created coverage that better 

matched growers' true expected levels of production

Exhibit 15: Performance Goal Results

Annual Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.3.6 Value of FCIC risk 

protection coverage 

provided through 

FCIC-sponsored 

insurance ($billions)

89.9 79.6 77.9 110.9 116.2 82.4 122.8 Exceeded

Allowable Data Range for Met: Annual targets for this measure have consistently had a 

variation of +/- $4.4 Billion.

Completeness of Data — The data used in conjunction with performance information are 

based on actual information. The Department receives the actual data from insurance 

companies. It then maintains data through two integrated processing systems that validate the 

information. The data then are sent through the system to generate all accounting functions. 

These processing systems ensure that data received are accurate, errors are corrected quickly, 

and timely monthly accounting reports are provided.

Reliability of Data — USDA deems this information to be reliable. The insurance companies 

receive data from the producers and transmit them to the Department. Once received, USDA 

takes extensive steps to verify the data’s accuracy and validity. The Standard Reinsurance 

Agreement (SRA) also provides reinsured companies with disincentives for not following 

prescribed guidelines and procedures. 

Quality of Data: Data are self-reported but are considered a good indicator of aggregate 

company sales. In 2011, The OTP conducted a test on the reliability of the data; OTP analyzed 

reported projected sales of three trade shows. This analysis compared reported projected sales to 

actual 12-month sales that were obtained through an extensive telephone survey. This review 

demonstrated that overall the projections understand actual sales. Prior to the review, many 

assumed projections were considerable overstating final sales.
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Quality of Data — Data are projected based on historical performance. The target information 

uses data dependent upon the baseline projections from numerous USDA agencies. To the 

extent that any of the Department’s projections are inaccurate, the projection of value will also 

be inaccurate.

Challenges for the Future

To the extent that commodity prices decrease in the future, so will the value of risk 

protection. USDA will need to find ways to continue enhancing participation in the crop 

insurance program, especially in the South and underserved States. Provisions in the 2014 Farm 

Bill will help participation. 

Normalized value of FCIC risk protection coverage provided through FCIC-sponsored 

insurance

Analysis of Results

USDA exceeded the target for this performance measure. As previously mentioned in Exhibit 15

the total amount of planted and insured acres increased compared to last year, likely due to 

continued high commodity prices. Also, the Department’s new program that allows corn and 

soybean growers in selected States to adjust their insurance guarantees to reflect long-term yield 

trends resulted in coverage that better matches their true expected level of production. Thus, the 

amount of risk protection for those growers increased and, likely, boosted participation in the 

crop insurance program.

Exhibit 16: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.3.7 Normalized value of 

FCIC risk protection 

coverage provided 

through FCICsponsored insurance 

($billions)

51.6 53.9 55.0 56.3 62.1 54.9 66.0 Exceeded

Allowable Data Range for Met: Annual targets for this measure have consistently had a 

variation of +/- $4.4 billion.

Completeness of Data — The data used in conjunction with performance information are 

based on actual results. Analysis has shown that normally 99 percent of the final actual data 

will be reported to USDA during the first quarter of the next fiscal year. USDA receives the 

actual data from insurance companies. It then maintains data through two integrated 

processing systems that validate the information. The data then are sent through the system to 

generate all accounting functions. These processing systems ensure that data received are 

accurate, errors are corrected quickly, and timely monthly accounting reports are provided.

Reliability of Data — USDA deems this information to be reliable. The insurance companies 

receive data from the producers and transmit them to the Department. Once received, USDA 

takes extensive steps to verify the data’s accuracy and validity.
PRIORITY GOALS

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Quality of Data — Data are projected based on historical performance. The target information 

uses data dependent upon the baseline projections from numerous Department agencies. To the 

extent that any of USDA’s projections are inaccurate, the projection of value will also be 

inaccurate.

Challenges for the Future

As the average level of coverage increases, continued increases will become more difficult to 

attain. Should commodity prices decrease, there could potentially be a decrease in acres planted 

and the normalized value of risk protection. Provisions in the 2014 Farm Bill will help 

participation. 

Percent of industry compliance with the Packers and Stockyards Act

Analysis of Results

USDA exceeded the target for this performance measure. Industry compliance with P&SA 

reached 83 percent in 2013, sustaining 2012’s improvement over the 76 percent rate in 2011. 

Results of the individual component inspections and audits that comprise the aggregate index 

show year-to-year decreases in some compliance rates compared to 2012 but increases from 

2008-2011 averages. 

Exhibit 17: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

1.3.8 Percent of industry 

compliance with the 

Packers and Stockyards 

Act

80 80 80 76 87 81 83 Exceeded

Allowable Data Range for Met: The variance is +/- 7 percent.

Completeness of Data — The industry compliance rate is a composite index taken as the 

simple average from five compliance areas: 1) the percent compliance of prompt payment by 

livestock markets, dealers, and packers; 2) custodial account compliance of livestock markets; 

3) livestock scale checks for packers slaughtering more than 1,000 head; 4) livestock scale 

checks of livestock markets, dealers, and live poultry dealers; and 5) poultry contract payment 

compliance reviews. The data represent a complete statistical sample to achieve a 90-percent 

confidence level for the industry as a whole based on the samples of each of the five sample 

areas.

Reliability of Data — The compliance levels for random sample audits are done with a 90-

percent confidence level for each of the five component areas. Data reliability appears strong 

as the measure is subject to replication and confirmation with a larger non-random sample set 

of data of all field inspections. Overall standard deviations are relatively small but subject to 

uncontrolled external factors, such as the economy and how that affects regulated firms.

Quality of Data — In addition to the standard deviation of the estimates, an annual 

independent review of the sampling process is conducted to ensure that the established 

standard operation procedures are followed during the onsite sampling process.
PRIORITY GOALS

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Challenges for the Future

While additional focus on activities to achieve industry compliance has resulted in increased 

compliance, general economic conditions within the industry will also affect year-to-year 

compliance. Weak economic conditions may increase the incentive for industry non compliance 

more quickly in the financial components than in the business practice areas. The full effect of 

these external conditions on the compliance rate is unknown. This measure has only a 6-year 

history, so understanding the interaction of these variables on the overall compliance rate and its 

variance will be a challenge that USDA will assess in future years. 

Strategic Goal 2: Ensure Our National Forests and Private Working Lands 

are Conserved, Restored, and Made More Resilient to Climate Change, While 

Enhancing Our Water Resources

Objective 2.1: Restore and Conserve the Nation’s Forests, Farms, Ranches and Grasslands

Conservation Reserve Program: Restored wetland acreage

Analysis of Results

Due to the 3.3 million acres of CRP expiring in FY 2013, the uncertainty around and delay in

extension of Farm Bill authority, and relatively high commodity prices, USDA faced challenges 

in maintaining the magnitude of CRP’s conservation benefits. At the end of FY 2013 USDA had 

CRP contracts with landowners covering 2.09 million acres of wetlands (including upland 

buffers), falling short of its FY 2013 target of 2.25 million acres. 

FY 2014 began with 25.6 million acres under contract. These acres annually reduce nitrogen, 

phosphorus, and sediment by more than 85 percent, and sequester carbon dioxide in soils and 

vegetation. CRP also contributes to increased wildlife populations. CRP wetlands and grasslands 

have added more than two million ducks to the Prairie Pothole Region annually, and increased 

ring-necked pheasant and other grassland bird populations.

Exhibit 18: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

2.1.1 CRP restored 

wetland acreage 

(millions of acres)

1.98 2.04 2.05 2.23 2.29 2.25 2.09 Unmet

Allowable Data Range for Met: The allowable data range is +/-0.05 million acres

Completeness of Data — The data source for this measure is the National Conservation 

Reserve Program Contract Data Files. The targets and actual data are annual. Data reported 

are based on final results for the fiscal year. The measure reports national acres under contract 

with the following wetland practices: wetland restoration, marginal pastureland buffers, 

bottomland trees, shallow water areas for wildlife, duck nesting habitat, and farmable wetlands 

programs. There are no known data limitations. Acres reported include associated upland 

buffers. 

Reliability of Data — USDA considers the data to be reliable. 
PRIORITY GOALS

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Quality of Data — Overall, the quality of the data is acceptable. There are no known data 

limitations. Acres reported include associated upland buffers.

Actions for Unmet Measures

Due to delayed extension of Farm Bill authority, FY 2013 signup for CRP did not begin until the 

middle of May 2013. The shortened enrollment period, combined with expiring wetland 

contracts and high commodity prices led to lower wetland enrollments than targeted for the year.

Challenges for the Future

The Agricultural Act of 2014 reduces CRP enrollment authority to no more than 24 million acres 

by 2017. FY 2014 enrollment is expected to end at about 25.7 million acres. Due to the 2.0 

million acres of CRP expiring in FY 2014, combined with relatively high commodity prices, 

USDA faces challenges in maintaining the magnitude of CRP’s conservation benefits. USDA 

remains strongly committed to attaining its conservation objectives. Special focus will be placed 

on accelerating the protection of clean and abundant water resources.

Cropland with conservation applied to improve soil quality – Conservation Technical 

Assistance (CTA) (millions of acres)

Cropland with conservation applied to improve soil quality – Environmental Quality 

Incentives Program (EQIP) (millions of acres)

Analysis of Results

USDA met the performance targets for CTA and EQIP by helping farmers and ranchers install 

conservation practices across the Nation that help manage the impacts of the drought, improve 

soil health, and store greenhouse gases. In addition, the programs provided the support to partner 

conservation programs in helping better implementation practices important to improve and 

sustain soil quality. The Department establishes technical specifications for conservation 

practices, ensuring that public investment for conservation is in accordance with scientific data 

demonstrating the desired outcome.

Several NRCS conservation practices directly impact soil carbon storage. For example, 

conservation crop rotations (5.8 million acres applied in 2013) or planting cover crops (with 1.1 

million acres applied in 2013) help increase carbon storage in soil. These crops take carbon 

dioxide out of the atmosphere and deposit it into the soil as organic matter. They also help 

reduce erosion and increase water-holding capacity and water infiltration, which increases the 

resiliency to drought, heavy precipitation and extreme temperatures. If carbon can be quantified, 

verified, and then sold into carbon markets, it could become another potential revenue stream for 

producers. 

In 2013, across all NRCS programs, over 13 million acres of cropland had conservation applied 

to improve soil quality. This measure is used as the USDA indicator for maintaining or 

enhancing sustained production of a safe, healthy, and abundant food supply. These annual 

outputs contribute significantly to long-term outcome measurements. According to the sciencebased USDA National Resources Inventory, between 1982 and 2007, soil erosion on U.S. 
PRIORITY GOALS

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cropland decreased 43 percent. Water (sheet & rill) erosion on cropland in 2007 declined from 

1.68 billion to 960 million tons per year, and erosion due to wind declined from 1.38 billion to 

765 million tons per year.

Exhibit 19: Performance Goal Results

Annual Performance 

Goals, Indicators 

and Trends

2008 2009 2010 2011 2012 Fiscal Year 2013

Target Actual Result

2.1.2 Cropland with 

conservation applied to 

improve soil quality 

(CTA - millions of acres)

8.3 7.6 8.2 8.2 8.7 8.0 8.4 Met

2.1.3 Cropland with 

conservation applied to 

improve soil quality 

(EQIP - millions of 

acres)

5.6 4.8 4.8 4.6 4.6 4.6 4.2 Met

Allowable Data Range for Met: Data assessment metrics to meet the target allow for an actual 

number in the range 7.3 (90 percent) – 8.8 (110 percent) for CTA and 4.1 (90 percent) – 5.1 (110 

percent) for EQIP.

Completeness of Data— The performance reported for these measures is based on actual data 

reported for FY 2013. Numerous data quality mechanisms within Performance Results System 

(PRS) ensure the completeness of each performance record entered into the system. All 

conservation practices that are applied have been certified in the National Conservation Planning 

database (NCP) by a qualified conservation planner, and certified as complete and final by the 

State conservationist by September 30 of each fiscal year.

Reliability of Data— For FY 2013, the data reported for these performance measures were 

calculated within PRS based on information validated and retrieved from the NCP and ProTracts. 

Conservation practices are planned in consultation with the customer and included in 

conservation plans stored in NCP. Periodic reviews are conducted to assess the accuracy of 

reported data.

Quality of Data—Field staffs report performance where the conservation work is occurring. 

Error checking enhancements and reports within the PRS application maintain data quality 

allowing users at local, State, and national levels to monitor data inputs. Data on the linkage of 

programs and conservation practices applied are accurate because the conservation program 

responsible for applying each practice is documented in the conservation plan developed in 

Toolkit. The same land unit may benefit from the application of more than one conservation 

practice and program. Where multiple practices are applied with multiple programs on the same 

land unit, each program is credited under the performance measure. NRCS is in the process of 

implementing its Conservation Delivery Streamlining Initiative which will further improve data 

quality.
PRIORITY GOALS

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Challenges for the Future

Improved soil quality on America’s cropland is vital to meeting the challenges of the future, 

especially with respect to climate change. Organic matter increases the capacity of the soil to 

take in and hold onto water. Thus, during periods of heavier rainfall, the soil retains more water. 

During periods of lesser rainfall, the water can be extracted by the plant, much in the same 

manner as a sponge releases water when squeezed. Increasing organic matter through carbon 

sequestration reduces the amount of carbon dioxide (considered a greenhouse gas) in the 

atmosphere, possibly mitigating impacts of carbon emissions elsewhere. 

Demands for agricultural products, for food, fiber and energy continue to increase as populations 

rise. These demands can adversely impact soil heath and quality, reducing its ability to produce 

at previous levels. Sustainable agriculture, producing agricultural products in a manner so that 

the natural resources are maintained or enhanced, is necessary to meet the demands of tomorrow. 

Drought will have a negative impact on soil quality. Exposed and dry topsoil are more 

susceptible to erosion due to dry surface conditions and reduced crop residues and vegetation to 

prevent soil movement. 

Grazing land and forest land with conservation applied to protect and improve the

resource base (CTA, millions of acres)

Grazing land and forest land with conservation applied to protect and improve the resource 

base (EQIP, millions of acres)

Analysis of Results

USDA met the target for the CTA measure and exceeded the target for EQIP by assisting with 

the installation of conservation practices on the Nation’s grazed lands with lower costs for 

producers. In 2013, additional outreach efforts, especially in wildlife habitat improvement, 

resulted in higher state and partner participation and improved conservation management. In 

addition, the impacts of the drought in 2012 caused delayed implementation of the conservation 

installations that happened in 2013. Weather impacts can happen with conservation activities and 

no corrective actions are needed to improve the EQIP measure. 
PRIORITY GOALS

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Exhibit 20: Performance Goal Results

Annual Performance 

Goals, Indicators 

and Trends

2008 2009 2010 2011 2012 Fiscal Year 2013

Target Actual Result

2.1.4 Grazing land and 

forest land with 

conservation applied 

to protect and improve 

the resource base 

(CTA, millions of 

acres)

16.0 16.0 17.6 17.1 17.1 17.1 16.6 Met

2.1.5 Grazing land and 

forest land with 

conservation practices 

applied to protect and 

improve the resource 

base (EQIP, millions 

of acres)

16.9 17.2 17.5 16.3 17.2 16.2 17.9 Exceeded

Allowable Data Range for Met: Data assessment metrics to meet the target allow for an actual 

number in the range 15.4 (90 percent) – 18.8 (110 percent) for CTA and 14.6 (90 percent) – 17.8 

(110 percent) for EQIP.

Completeness of Data— The performance reported for these measures is based on actual data 

reported for FY 2013. Numerous data quality mechanisms within PRS ensure the completeness 

of each performance record entered into the system. All conservation practices that are applied 

have been certified in NCP by a qualified conservation planner, and certified as complete and 

final by the State conservationist by September 30 of each fiscal year.

Reliability of Data— For FY 2013, the data reported for these performance measures were 

calculated within PRS based on information validated and retrieved from the NCP and 

ProTracts. Conservation practices are planned in consultation with the customer and included in 

conservation plans stored in NCP. Periodic reviews are conducted to assess the accuracy of 

reported data.

Quality of Data—Field staffs report performance where the conservation work is occurring. 

Error checking enhancements and reports within the PRS application maintain data quality 

allowing users at local, State, and national levels to monitor data inputs. Data on the linkage of 

programs and conservation practices applied are accurate because the conservation program 

responsible for applying each practice is documented in the conservation plan developed in 

Toolkit. The same land unit may benefit from the application of more than one conservation 

practice and program. Where multiple practices are applied with multiple programs on the same 

land unit, each program is credited under the performance measure. NRCS is in the process of 

implementing its Conservation Delivery Streamlining Initiative which will further improve data 

quality.
PRIORITY GOALS

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Challenges for the Future

Producers’ willingness and ability to implement conservation measures on private forest land, 

range, and grasslands is affected by economic conditions, climate variability, drought, and 

invasive species. While drought conditions may create long-term interest in adopting 

conservation treatments for grazing and forest land, operators in grazing and forest lands will 

face increased management challenges short term. Such a scenario reduces their ability to apply 

conservation on their land. An uncertain economic climate will increase the threat of conversion 

of these lands to non-agricultural uses.

In many areas, especially in the West, watersheds and landscapes include public land managed 

by several Federal agencies intermingled with private, State, and Tribal lands. Protecting the 

natural resources in these areas requires cooperation among a large number of stakeholders, 

especially when taking a watershed approach.

Prime, unique, or important farmland protected from conversion to non-agricultural uses by 

conservation easements (FRPP, thousands of acres)

Analysis of Results

USDA did not meet the target for this performance measure. In the development of the annual 

target, best estimates on which easements would be closing during the fiscal year were made. 

Some easements were behind schedule or with fewer acres of prime farmland than expected, 

which caused the target to be unmet. No corrective actions are needed.

The growth of State and local programs and landowner demand ensure that every dollar allocated 

will protect farmland. The impact of protecting prime, unique, and important farmland is 

sustained and healthy agricultural communities. A strong agricultural community supports 

farmers’ markets, restaurants, grocery stores, school cafeterias, and communities across 

America. The farms and ranches enrolled in FRPP ensure the preservation of open space along 

with community support. 

Exhibit 21: Performance Goal Results

Annual Performance 

Goals, Indicators 

and Trends

2008 2009 2010 2011 2012 Fiscal Year 2013

Target Actual Result

2.1.6 Prime, unique, or 

important farmland 

protected from 

conversion to nonagricultural uses by 

conservation easements 

(FRPP, thousands of 

acres)

27.4 38.3 53.9 51.5 45.2 50.0 27.8 Unmet

Allowable Data Range for Met: Data assessment metrics to meet the target allow for an actual 

number in the range 45.0 (90 percent) – 55.0 (110 percent).
PRIORITY GOALS

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Completeness of Data— The performance reported for these measures is based on actual data 

reported for FY 2013. Numerous data quality mechanisms within PRS ensure the completeness 

of each performance record entered into the system. All conservation practices that are applied 

have been certified in NCP by a qualified conservation planner, and certified as complete and 

final by the State conservationist by September 30 of each fiscal year.

Reliability of Data— For FY 2013, the data reported for these performance measures were 

calculated within PRS based on information validated and retrieved from the NCP and 

ProTracts. Conservation practices are planned in consultation with the customer and included in 

conservation plans stored in NCP. Periodic reviews are conducted to assess the accuracy of

reported data.

Quality of Data—Field staffs, trained and skilled in conservation planning and application 

suited to the local resource conditions, report performance where the conservation work is 

occuring. Error checking enhancements and reports within PRS application maintain data 

quality allowing users at local, State, and national levels to monitor data inputs. Data on the 

linkage of programs and conservation practices applied are accurate because the conservation 

program responsible for applying each practice is documented in the conservation plan 

developed in Toolkit. The same land unit may benefit from the application of more than one 

conservation practice and program. Where mulitple practices are applied with multiple 

programs on the same land unit, each program is credited under the performance measure. NRCS 

is in the process of implementing its Conservation Delivery Streamlining Initiative which will 

further improve data quality.

Actions for Unmet Measures

There are two actions required to address performance for this unmet measure: revision of the 

measure to more accurately reflect program rules, and improved forecasting using NEST project 

status and likelihood of closing by the end of the fiscal year. The previous data source was not as 

consistent and strict as the NEST data, so adjusting the forecasting method along with the 

verification and validation method to align with Agricultural Conservation Easement Program 

(ACEP) rules as developed from the 2014 Farm Bill will be required. Deviations from the set 

target will be reduced using these corrective actions.

Challenges for the Future

The increased value of farmland, especially around urban areas may decrease the amount of 

prime, unique, and important farmland acreage FRPP can protect. Although local farmland 

protection programs have grown in the last decade, the demand for agricultural easements 

outpaces available funds. Budget challenges in State and local Governments will affect their 

ability to match FRPP funds, along with declining non-Federal revenues in programs that raise 

matching funds. 

In addition, the added consistency using NEST and other data systems for reporting will provide 

a better forecasting method for all easement-related programs. The revision of the Farm Bill 

easement programs provides an opportunity to simplify and streamline performance measures for 

the program.
PRIORITY GOALS

29

Non-Federal land with conservation applied to improve fish and wildlife habitat quality –

Wildlife Habitat Incentives Program (WHIP) (millions of acres)

Non-Federal land with conservation applied to improve fish and wildlife habitat quality 

(EQIP) (millions of acres)

Analysis of Results

USDA did not meet the targets for these performance measures. The lack of performance in 

these measures is a result of program changes and funding in FY 2012 when contracts were 

established that would have been implemented in FY 2013. The Wildlife Habitat Incentives 

Program (WHIP) faced some realignments and decreased funding that have produced reductions 

in performance.

Two primary factors contributed to the shortfall. First, budget authority for WHIP decreased 

from $85 Million in 2011 to an enacted level of $47 Million in the following year, FY 2012. 

Second, the agency strategically focused WHIP work on the Working Lands for Wildlife 

(WLFW) Partnership, which targeted priority wildlife species of concern. The reduced funding 

and as well as the targeting of the funding limited the number of contracts that could be obligated 

in FY 2012 that would result in performance in FY 2013.

Exhibit 22: Performance Goal Results

Annual Performance 

Goals, Indicators 

and Trends

2008 2009 2010 2011 2012 Fiscal Year 2013

Target Actual Result

2.1.7 Non-Federal land with 

conservation applied to 

improve fish and 

wildlife habitat quality 

(WHIP, millions of 

acres)

0.3 0.3 0.9 1.3 0.9 0.7 0.4 Unmet

2.1.8 Non-Federal land with 

conservation applied to 

improve fish and 

wildlife habitat quality 

(EQIP, millions of 

acres)

4.8 5.2 6.0 4.8 6.2 2.5 2.0 Unmet

Allowable Data Range for Met: Data assessment metrics to meet the target allow for an actual 

number in the range 0.6 (90 percent) – 0.8 (110 percent) for WHIP and 2.3 (90 percent) – 2.8 

(110 percent) for EQIP.

Measure definition was revised in FY 2010 from 3 wildlife management practices to the full 

suite of 17 practices used to provide improvements to wildlife habitat. While these practices 

have always been used for wildlife habitat improvement, they were excluded from the measure 

definition. Values for FY 2008 through FY 2009 are estimates based on the revised definition, 

and reflect the long-term use of these practices. 
PRIORITY GOALS

30

Completeness of Data— The performance reported for these measures is based on actual data 

reported for FY 2013. Numerous data quality mechanisms within PRS ensure the completness 

of each performance record entered into the system. All conservation practices that are applied 

have been certified in the NCP by a qualified conservation planner, and certified as complete and 

final by the State conservationist by September 30 of each fiscal year. 

Reliability of Data— For FY 2013, the data reported for these performance measures were 

calculated within PRS based on information validated and retrieved from the NCP and 

ProTracts. Conservation practices are planned in consultation with the customer and included in 

conservation plans stored in NCP. Periodic reviews are conducted to assess the accuracy of 

reported data.

Quality of Data—Field staffs, trained and skilled in conservation planning and application 

suited to the local resource conditions, report performance where the conservation work is 

occuring. Error checking enhancements and reports within the PRS application maintain data 

quality allowing users at local, State, and national levels to monitor data inputs. Data on the 

linkage of programs and conservation practices applied are accurate because the conservation 

program responsible for applying each practice is documented in the conservation plan 

developed in Toolkit. The same land unit may benefit from the application of more than one 

conservation practice and program. Where mulitple practices are applied with multiple 

programs on the same land unit, each program is credited under the performance measure. 

NRCS is in the process of implementing its Conservation Delivery Streamlining Initiative which 

will further improve data quality.

Actions for Unmet Measures

Actions to address unmet performance goals include addressing the existing backlog in the 

WLFW initiative and assuring that the targets with wildlife practices are in line with any changes 

to the EQIP rules with respect to wildlife. These actions will also need to be evaluated within 

the context of any funding changes in the 2014 Farm Bill for initiatives.

Challenges for the Future

USDA works with other agencies and private organizations to provide producers with technical 

and financial assistance, information, and other resources. This work helps evaluate and 

encourage the adoption of conservation measures and management practices beneficial to 

wildlife. Many wildlife projects are supported by a combination of Federal, State, local, and 

private funds. Because of continuing State and local budget issues, constraints may impact 

project evaluations and implementation. Commodity prices, economic conditions, weather, 

wildfires, and developmental pressures can impact the ability and willingness of agricultural 

producers to invest in wildlife habitat unless there are clearly multiple benefits. In addition to 

adjusting the performance reporting rules to increase the quality of habitat acres, NRCS is 

continuing to strategically focus on higher-value acres in relationship to regulatory predictability 

for landowners with identified priority species habitat. Additional agreements, national guidance 

and staff training, as well as landowner outreach and adoption are needed. Additional analysis 

will be done for setting appropriate targets based on the strategic approach to higher-value 

habitat acres.
PRIORITY GOALS

31

Number of communities with urban and community forestry programs resulting from Forest 

Service assistance

Analysis of Results

The Department met its goal of providing assistance to 7,200 communities. This assistance 

helped communities develop and maintain urban forestry programs, which protect their urban 

trees and forests. As a result of assistance provided by the Urban and Community Forestry 

program, in FY 2013, 47 percent of people in the U.S. are living in communities that are 

managing programs to protect and maintain their urban forests.

Exhibit 23: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

2.1.9 Number of communities 

with urban and 

community forestry 

programs resulting from 

Forest Service 

assistance

(number of 

communities)

7,139 6,853 7,102 7,172 7,499 7,200 7,292 Met

Allowable Data Range for Met: The tolerance range for the measure to be met is +/- 5

percent or from 6,840 to 7,560.

Completeness of Data — Values shown for FY 2013 include final, complete results.

Reliability of Data — The data for urban and community forestry programs are reliable and of 

good quality. It is provided by the States in the Community Accomplishment Reporting 

System (CARS).

Quality of Data — The Forest Service has a control system to ensure national performance 

data quality and validity. This framework includes data reviews, regional and national data 

certifications, and measure change control processes.

Challenges for the Future

The Urban and Community Forestry program will continue to work with State forestry agencies 

and other partners to assist communities in developing and advancing their urban forestry 

programs. Funding is provided to the highest priority activities that can demonstrate results in a 

transparent manner. The program will place special emphasis on landscape scale demonstration 

projects that have regional and national significance for urban and community forest 

management across landscapes.
PRIORITY GOALS

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Annual acres of public and private forest lands restored or enhanced

Analysis of Results

USDA met its goal of restoring or enhancing over 4.3 million acres of public and private forest 

lands. A major driver of these efforts was over 2.5 million acres treated to restore watershed 

function and resilience by the Integrated Resource Restoration (IRR) program. In the second 

year of a pilot effort approved by Congress, the program worked toward improved outcomes at 

the landscape scale. A key example of these outcomes achieved in 2013 is the improvement of 

15 watersheds to an improved condition class through treatments associated with watershed 

action plans.

Exhibit 24: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

2.1.10 Annual acres of public 

and private forest 

lands restored or 

enhanced. 

(millions of acres)

N/A* N/A*4.777 4.925 4.425 4.322 4.704 Met

*

This was a new measure implemented for the 2010 USDA Strategic Plan

Allowable Data Range for Met: The tolerance range for the measure to be met is +/- 10 

percent or from 3.89 to 4.75.

Completeness of Data — Values shown for FY 2013 include final, complete results.

Reliability of Data — The data for programs contributing to restoration treatments are reliable 

and of good quality. It is provided by Forest Service field units in several source reporting data 

systems.

Quality of Data — The Forest Service has a control system to ensure national performance 

data quality and validity. This framework includes data reviews, regional and national data 

certifications, and measure change control processes.

Challenges for the Future

With forests at risk from drought, invasive species, severe wildfires, and outbreaks of insects and 

disease, USDA faces a sustained forest restoration challenge. By using the best science available 

and focusing on programs like IRR and the Collaborative Forest Restoration Program, we will 

continue to focus on increasing the scale and pace of restoration and conservation work on both 

public and private lands.
PRIORITY GOALS

33

Volume of timber sold

Analysis of Results

The Department met its goal by selling 2.61 billion board feet of timber. Using an all-lands 

restoration approach, USDA is working in collaboration with partners, agencies, and Tribes in 

achieving restoration and maintenance goals resulting from mechanical harvesting of trees. 

Timber harvest also makes important contributions to rural economies; each year forest products 

from NFS lands contribute approximately 42,000 jobs and $2.7 billion to the national economy.

Exhibit 25: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

2.1.11 Volume of timber 

sold (million 

board feet).

2,484 2,415 2,592 2,533 2,644 2,475 2,610 Met

Allowable Data Range for Met: The tolerance range for the measure to be met is +/- 10

percent or from 2,228 to 2,723.

Completeness of Data — Values shown for FY 2013 include final, complete results.

Reliability of Data — The data for the timber program is reliable and of good quality. It is 

provided by Forest Service field units in the timber information management reporting data 

system.

Quality of Data — The Forest Service has a control system to ensure national performance 

data quality and validity. This framework includes data reviews, regional and national data 

certifications, and measure change control processes.

Challenges for the Future

As USDA works to increase restoration accomplishments, timber harvest is an important tool 

used to achieve multiple resource objectives. Its integration with other activities including road 

decommissioning, stream restoration, and others helps to achieve the agency-wide goals of 

increasing watershed health, improving resilience at the landscape level, and accelerating the 

pace of restoration. 

Objective 2.3: Protect and enhance Americas water resources

Land with conservation applied to improve water quality (CTA, millions of acres)

Land with conservation applied to improve water quality (EQIP, millions of acres)
PRIORITY GOALS

34

Analysis of Results

In FY 2013, USDA met its targets for CTA and EQIP programs. In 2013, USDA assisted 

landowners and managers in application of 35 million acres of conservation designed to improve 

water quality across all NRCS programs. USDA conservation practices are science-based and 

have a demonstrated effect. A scientific study was done by the Conservation Effects Assessment 

Project (CEAP) showed that adoption of conservation practices in Chesapeake Bay agriculture 

has reduced edge-of-field sediment loss by 55 percent, losses of nitrogen with surface runoff by 

42 percent, losses of nitrogen in subsurface flows by 31 percent, and losses of phosphorus 

(sediment attached and soluble) by 41 percent.

Farmers have significantly reduced the loss of sediment and nutrients from farm fields through 

voluntary conservation work in the lower Mississippi River basin. In the Mississippi River 

basin, conservation work, like controlling erosion and managing nutrients, has reduced the edgeof-field losses of sediment by 35 percent, nitrogen by 21 percent and phosphorous by 52 percent. 

These losses are derived from comparing losses of sediment and nutrients from cultivated 

cropland to losses that would be expected if conservation practices were not used. The results 

show an increase in cover crops will have a significant impact on reducing edge-of-field losses 

of sediment and nutrients and improve water quality. In 2013, NRCS assisted with the 

application of 1.1 million acres of cover crop nationwide.

Over the past few years, similar assessments were completed in the upper Mississippi River, 

Tennessee-Ohio, Missouri and Arkansas-Red-White basins. As a whole, assessments in this 

project have shown:

Conservation on cropland prevents an estimated 243 million tons of sediment, 2.1 billion pounds 

of nitrogen and 375 million pounds of phosphorus from leaving fields each year. These figures 

translate to a 55 percent, 34 percent and 46 percent reduction in sediment, nitrogen and 

phosphorus edge-of-field losses, respectively, compared to what would have been lost if no 

conservation practices were in place. 

Similarly, conservation has resulted in an estimated 17 percent reduction in nitrogen and 22 

percent reduction in phosphorus entering the Gulf of Mexico annually. An additional reduction 

of 15 percent of nitrogen and 12 percent of phosphorus can be achieved by implementing 

comprehensive conservation plans on all cropland in the basin in areas that have not adequately 

addressed nutrient loss. 

The scientific-based modeling also pointed out that higher rainfall and more intense storms lead 

to higher edge-of-field losses of sediment and nutrients in the lower Mississippi River basin than 

the other four basins in the Mississippi River watershed. Because of this, more soil erosion 

control and better management of nutrients are important in the basin.
PRIORITY GOALS

35

Exhibit 26: Performance Goal Results

Annual Performance Goals, 

Indicators 

and Trends

2008 2009 2010 2011 2012 Fiscal Year 2013

Target Actual Result

2.3.1 Land with conservation 

applied to improve water 

quality (CTA, millions of 

acres) 

8.7 20.5 22.3 24.0 23.8 22.0 22.4 Met

2.3.2 Land with conservation 

applied to improve water 

quality (EQIP, millions of 

acres) 

14.8 14.5 14.2 14.5 13.6 12.8 13.0 Met

Allowable Data Range for Met: Data assessment metrics to meet the target allow for an actual 

number in the range 19.8 (90 percent) – 24.2 (110 percent) for CTA and 11.5 (90 percent) – 14.1 

(110 percent) for EQIP.

Completeness of Data— The performance reported for these measures is based on actual data 

reported for FY 2013. Numerous data quality mechanisms within PRS ensure the completness of 

each performance record entered into the system. All conservation practices that are applied have 

been certified in NCP by a qualified conservation planner, and certified as complete and final by 

the State conservationist by September 30 of each fiscal year.

Reliability of Data— For FY 2013, the data reported for these performance measures were 

calculated within PRS based on information validated and retrieved from the NCP and ProTracts. 

Conservation practices are planned in consultation with the customer and included in 

conservation plans stored in NCP. Periodic reviews are conducted to assess the accuracy of 

reported data. 

Quality of Data—Field staffs, trained and skilled in conservation planning and application suited 

to the local resource conditions, report performance where the conservation work is occuring. 

Error checking enhancements and reports within the PRS application maintain data quality 

allowing users at local, State and national levels to monitor data inputs. Data on the linkage of 

programs and conservation practices applied are accurate because the conservation program 

responsible for applying each practice is documented in the conservation plan developed in 

Toolkit. The same land unit may benefit from the application of more than one conservation 

practice and program. Where mulitple practices are applied with multiple programs on the same 

land unit, each program is credited under the performance measure. NRCS is in the process of 

implementing its Conservation Delivery Streamlining Initiative which will further improve data 

quality.

Challenges for the Future

The quality of ground and surface waters to support intended uses is continuing a concern. The 

supply of these waters to meet expanding demand also is a challenge. The landowner cost-share 

capital investment for conservation structures to address water quality is a challenge in the 

current economic environment. USDA use of outcome-based performance measures will 

encourage producers see the cost and benefits of their conservation investment.
PRIORITY GOALS

36

To further evaluate the outcomes of Departmental investments, USDA uses the multi-agency 

Conservation Effects Assessment Project (CEAP) to quantify the environmental benefits of 

conservation practices. Private landowners are cooperating with the Department in the CEAP 

effort. Watershed-based assessments are directed at evaluating interactions among practices and 

hydrology in the landscape. With additional knowledge of the dynamic relationship between 

conservation activities undertaken on individual farms and ranches and the resulting off-site 

benefits, USDA can more effectively utilize its programs. Much of this effort is focused on the 

impacts of livestock, irrigation and drainage management, and conservation practices with 

significant watershed level impacts.

While water conservation has always been considered a major factor in reducing soil erosion, 

runoff, and leaching of nutrients from cropland, as the focus has shifted to consumptive use of 

water, USDA has accelerated water conservation efforts on agricultural operations. The 

Department is developing an additional performance measure for assisting agricultural producers 

with irrigation efficiencies. This measure will be implemented nationwide in 2013.

Wetlands created, restored or enhanced (WRP, thousands of acres)

Analysis of Results

USDA did not meet the target for this performance measure. There were several challenges in 

FY2013 that hampered the ability to make progress on WRP easements. A combination of 

sequestration, no authority for new enrollment until January 2013, full funding delays until midApril 2013, and program uncertainties caused the target not to be met. USDA set an aggressive 

target and focused resources to address restoration backlog. In addition, there were external 

challenges such as contracting and permitting delays and weather that can affect wetland 

planting if not enough rain or inundation that delays work if rainfall is too heavy.

Exhibit 27: Performance Goal Results

Annual Performance Goals, 

Indicators 

and Trends

2008 2009 2010 2011 2012 Fiscal Year 2013

Target Actual Result

2.3.3 Wetlands created, restored 

or enhanced (WRP, 

thousands of acres)

128.9 106.4 129.1 131.8 189.0 212.3 164.0 Unmet

Allowable Data Range for Met: Data assessment metrics to meet the target allow for an actual 

number in the range 191.1 (90 percent) – 233.5 (110 percent). 

Completeness of Data— The performance reported for these measures is based on actual data 

reported for FY 2013. Numerous data quality mechanisms within PRS ensure the completness 

of each performance record entered into the system. All conservation practices that are applied 

have been certified in NCP by a qualified conservation planner, and certified as complete and 

final by the State conservationist by September 30 of each fiscal year.
PRIORITY GOALS

37

Reliability of Data— For FY 2013, the data reported for these performance measures were 

calculated within PRS based on information validated and retrieved from NCP and ProTracts. 

Conservation practices are planned in consultation with the customer and included in 

conservation plans stored in the NCP. Periodic reviews are conducted to assess the accuracy of 

reported data.

Quality of Data—Field staffs, trained and skilled in conservation planning and application 

suited to the local resource conditions, report performance where the conservation work is 

occuring. Error checking enhancements and reports within PRS maintain data quality allowing 

users at local, State and national levels to monitor data inputs. Data on the linkage of programs 

and conservation practices applied are accurate because the conservation program responsible 

for applying each practice is documented in the conservation plan developed in Toolkit. The 

same land unit may benefit from the application of more than one conservation practice and 

program. Where mulitple practices are applied with multiple programs on the same land unit, 

each program is credited under the performance measure. NRCS is in the process of 

implementing its Conservation Delivery Streamlining Initiative which will further improve data 

quality.

Actions for Unmet Measures

There are two actions required to address performance for this unmet measure, which are already 

underway: revision of the measure to more accurately reflect program rules, and improved 

forecasting using NEST project status. The previous data source was not as consistent and strict 

as the NEST data, so adjusting the forecasting method along with the verification and validation 

method to align with Agricultural Conservation Easement Program (ACEP) rules as developed 

from the 2014 Farm Bill will be required. Deviations from the set target will be reduced using 

these corrective actions.

Challenges for the Future

Considering the budget and program uncertainty in the expiring Farm Bill, along with program 

alignment in the 2014 Farm Bill, challenges will continue for FY2014 and beyond. Although 

additional care will be taken to assess the likelihood of progress accomplishments for the fiscal 

year, and improved target forecasting methods, the new targets will need to match revised 

program rules. 

In addition, commodity prices, economic conditions, weather, and developmental pressures can 

impact the ability and willingness of agricultural producers to restore and protect wetland and 

habitat areas. The operational difficulties and program uncertainties will continue through 

FY2014 which will impact future performance as well.
PRIORITY GOALS

38

Objective 2.4: Reduce Risk from Catastrophic Wildfire and Restore Fire to its 

Appropriate Place on the Landscape

Acres of Wildland-Urban Interface (WUI) fuels treated to reduce the risk of catastrophic fire

Analysis of Results

USDA exceeded the target for this performance measure. USDA continues to emphasize WUI 

treatments even where those acres are more expensive to operate in or require mechanical 

treatment. This emphasis was demonstrated last year by achieving well over 1.5 million acres of 

WUI fuels treated—a result matched in each of the past 5 years.

Exhibit 28: Performance Goal Results

Annual Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

2.4.1 Acres of WUI fuels 

treated to reduce the 

risk of catastrophic fire 

(millions of acres)

1.944 2.190 1.955 1.612 1.867 1.100 1.737 Exceeded

Allowable Data Range for Met: The tolerance range for the measure to be met is +/- 5 

percent or from 1.05 to 1.16.

Completeness of Data — Values shown for FY 2013 include final, complete results.

Reliability of Data — The data for the hazardous fuels program is reliable and of good quality. 

Forest Service accomplishments are entered at the field level into the Forest Activity Tracking 

System (FACTS) database, and data from the state fire assistance funding is captured in the 

National Fire Plan Operations and Reporting System (NFPORS).

Quality of Data — The Forest Service has a control system to ensure national performance 

data quality and validity. This framework includes data reviews, regional and national data 

certifications, and measure change control processes.

Challenges for the Future

WUI treatments have become more expensive and increasingly more complex. They are 

challenging because of the treatment proximity to communities and infrastructure, as well as 

associated air quality regulations and safety concerns. WUI treatment cost per acre can be up to

four times more expensive than treatments in non-WUI areas because most work is done 

mechanically, by hand crews, or with machinery. There is no economy of scale when working 

on lands adjacent to or in between homes. Projects completed using hazardous fuels funds will 

support the goals of the National Cohesive Wildland Fire Management Strategy.
PRIORITY GOALS

39

Percentage of acres treated in the WUI that have been identified in Community Wildfire 

Protection Plans

Analysis of Results

USDA exceeded the target for this performance measure and continued its strong focus on 

treating hazardous fuels in the WUI that are identified in a Community Wildfire Protection Plan 

(CWPP) or equivalent plan—including working with partner communities to provide technical 

assistance in developing CWPP’s. Each of the past two years the goal has been for 75 percent of 

the acres treated to be identified in a CWPP and we have surpassed that both years. We expect 

to continue this work with communities to develop and implement plans that help us target 

treatments and reduce the risk of wildfire. 

Exhibit 29: Performance Goal Results

Annual Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

2.4.2 Percentage of acres 

treated in the WUI that 

have been identified in 

Community Wildfire 

Protection Plans

36 41 45 61 93 75 85 Exceeded

Allowable Data Range for Met: The tolerance range for the measure to be met is +/- 10 

percent or from 67.5 to 82.5

Completeness of Data — Values shown for FY 2013 include final, complete results.

Reliability of Data — The data for the hazardous fuels program is reliable and of good quality. 

This measure is calculated from accomplishments entered at the field level into the Forest 

Activity Tracking System (FACTS) database.

Quality of Data — The Forest Service has a control system to ensure national performance 

data quality and validity. This framework includes data reviews, regional and national data 

certifications, and measure change control processes.

Challenges for the Future

With an increasing area of wildland-urban interface, USDA focuses on targeting fuels treatments 

in those communities that are working to prepare for wildland fire, including by having a CWPP 

in place. We also support communities that are working to achieve Firewise standards, and have 

made an investment in implementing local solutions to protect against wildland fire.
PRIORITY GOALS

40

Strategic Goal 3: Help America Promote Agricultural Production and 

Biotechnology Exports as America Works to Increase Food Security

Objective 3.2: Enhance America’s Ability to Develop and Trade Agricultural Products 

Derived from New Technologies

Cumulative number of genetically engineered plant lines reviewed by USDA and found safe 

for use in the environment

Analysis of Results

USDA exceeded the target for this performance measure by issuing additional determinations for 

nonregulated status plant lines. This action brought the cumulative total of determinations to 102. 

The determinations included two varieties of herbicide-tolerant canola, five varieties of corn 

(two herbicide-resistant, enhanced hybridization system, insect-resistant, rootworm-resistant), 

and a herbicide-tolerant/insect resistant cotton and soybean.

In FY 2012, the Department changed the process to decrease the length and variability of the 

petition review process, without compromising the quality of the analysis supporting 

Departmental decision making. Previously, this activity took up to 3 years or longer. The 

determinations in FY 2013 for nonregulated status occurred, on average, 12 months faster than 

the issuance of nonregulated status for petitions from 2009 - 2012. The change to the enhanced 

process increased efficiency and makes agricultural products more readily available to producers 

and growers. 

Exhibit 30: Performance Goal Results

Annual 

Performance 

Goals, Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

3.2.1 Cumulative 

number of 

genetically 

engineered plant 

lines reviewed 

by USDA and 

found safe for 

use in the 

environment

76* 78* 81* 87* 93* 99 102* Exceeded

Allowable Data Range for Met: USDA conducts a thorough scientific analysis and considers 

public comments for each submitted petition. If the GE organism is reviewed and found safe for 

use in the environment, the Department may determine nonregulated status. USDA then 

publishes a Federal Register notice announcing its determination of nonregulated status. There 

is no allowable range for this target as it is a whole positive integer that is verified and tracked as 

a count at the end of the fiscal year as publications in the Federal Register. A successful 

measure will be met or exceeded. The cumulative number of GE plant lines reviewed by the 

Department and found safe for use in the environment is an indicator of GE technologies that 
PRIORITY GOALS

41

can be commercialized by developers.

Data Source: http://www.aphis.usda.gov/biotechnology/petitions_table_pending.shtml

Completeness of Data: USDA maintains a web site that is updated weekly. When a 

determination of nonregulated status is made, the web site is updated to reflect the decision. 

This data is complete.

Reliability of Data: This data is used by both internal managers and external stakeholders as 

authoritative sources of information.

Quality of Data: For each petition submitted, USDA conducts a thorough scientific analysis to 

determine whether the GE organism poses a plant pest risk. USDA also prepares additional 

environmental analyses to evaluate the possible impacts of the GE organism on the human 

environment. During the petition process, there are two opportunities for public involvement, 

once when the petition is complete through the Federal Register process and a second time after 

the associated environmental documents and plant pest risk documents are developed and 

published in the Federal Register. If the Department determines nonregulated status for the GE 

organism, the information is shared on the Web site to ensure transparency of regulatory 

decision making.

Challenges for the Future

Biotechnology is an evolving set of technologies, and the cost of developing GE products is 

significant. As issues such as climate change or dependence on international oil continue to be 

explored, it is reasonable to expect that the biotechnology sector will look for opportunities to 

meet existing needs or to take advantage of new markets.

New scientific advances open up new approaches for the field of biotechnology. These advances 

may challenge USDA to determine its role in the regulation of technologies that were not 

anticipated when its current regulatory system was established. 

Other countries continue to invest in biotechnology, both in the public and private sectors. As 

GE organisms are developed in other countries and are imported into the United States, it is 

important to have adequate domestic regulatory systems in place to address their safety. In turn, 

it is important to coordinate with other countries to allow exports of GE products.

Strategic Goal 4: Ensure that All of America’s Children Have Access to Safe, 

Nutritious, and Balanced Meals

Objective 4.1: Increase Access to Nutritious Foods

Participation rates for the major Federal nutrition assistance programs: Supplemental 

Nutrition Assistance Program

Analysis of Results

USDA met the target for this performance measure. The Department estimates the number of 

people eligible for the program along with the rate at which those eligible are participating. The 
PRIORITY GOALS

42

latest study shows that, in 2010, 75 percent of all persons eligible for SNAP participated. The 

number of those eligible has grown in recent years, in response to economic conditions: levels in 

2009 increased by 15 percent over 2008, and by 14 percent from 2009 to 2010. Also, in 2010, the 

neediest among those eligible for the program were most likely to participate.

Exhibit 31: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

4.1.1 Participation levels for 

the major Federal 

nutrition assistance 

programs (millions per 

month): Supplemental 

Nutrition Assistance 

Program

28.4 33.5 40.3 44.3 46.6 47.1 47.6 Met

2013 Allowable Data Range for Met: The actual number represents information as of June 

30. Thresholds for 4.1.1 reflect the margin of error in forecasts of future participation. For 

SNAP participation, results from 2 independent assessments suggest that predictions of the 

number of SNAP participants are accurate to within +/- 7.5 percent on average.

Completeness of Data — SNAP participation data are drawn from USDA administrative 

records. State agency reports are certified accurate and submitted to regional offices. There, 

they are reviewed for completeness and consistency. If the data are acceptable, the regional 

analyst posts them to the National Data Bank (NDB) Preload System. NDB is a holding area 

for data review prior to release. Otherwise, regional-office personnel reject the report, and the 

State agency is contacted. The Department reviews data posted by regional personnel into 

NDB. If data are reasonable and consistent with previous reports, they will be downloaded to 

NDB for public release. If not, USDA works with regional offices and States to resolve 

problems and inconsistencies. This process of review and revision ensures that the data are as 

accurate and reliable as possible. Final figures represent 12-month fiscal year averages. 

Participation data are collected and validated monthly before being declared annual data. 

Reported estimates are based on data through June 30, 2013.

Reliability of Data — Participation-data reporting is used to support program financial 

operations. Data is used to support dialogue with, and information requests from, the 

Government Accountability Office, the Office of Inspector General, and the Office of 

Management and Budget.

Quality of Data — The data used to develop this measure are used widely for multiple 

purposes, both within and outside USDA. The measure itself is reported in stand-alone 

publications as an important, high-quality indicator of program performance.
PRIORITY GOALS

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Challenges for the Future

Studies and analyses show many SNAP-eligible people who do not participate may be unaware 

of their eligibility. Efforts to improve access to and promote awareness of SNAP, as well as seek 

improvements in policy and operations to make applying easier, are ongoing challenges for 

USDA.

The quality of program delivery by third parties — hundreds of thousands of State and local 

Government workers and their cooperators — is critical to USDA’s efforts to reduce hunger and 

improve nutrition. Proper program administration, including timely determination of eligibility, 

is of special concern.

SNAP payment accuracy rate

Analysis of Results

USDA met the target for this performance measure. SNAP payment accuracy reached a record 

high of 96.58 percent in 2012, the latest for which data are available. The number reflects the 

excellent performance by State agencies in administering the program. This combined rate 

reflects 2.77 percent in overpayments and 0.65 percent in underpayments, for a total of 3.42 

percent in erroneous payments.

Forty-six States had a payment accuracy rate greater than 94 percent, including 32 States with 

rates greater than 96 percent. This is two more States with 94 percent accuracy and three more 

States with 96 percent accuracy from the previous year.

Exhibit 32: Performance Goal Results

Annual 

Performance 

Goals, 

Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

4.1.2 SNAP 

Payment 

Accuracy 

Rate

Baseline: 

2001 = 

91.34%

94.3% 94.9% 96.19% 96.2% 96.58% 96.58% 96.58% Met

Allowable Data Range for Met: The 95-percent confidence interval around the estimate of 

payment accuracy is +/- 0.20. For 2013, this confidence level allows for actual performance that 

meets the target in the range 95.90 – 96.50 percent.
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Completeness of Data — SNAP, formerly the Food Stamp Program, uses annual payment 

accuracy data from a QC process to support its management. The data are based upon 

statistically valid methodology. The QC process uses a systematic random sampling of SNAP 

participants to determine a combined payment error rate for each State. The combined error rate 

is composed of over- and under-issuances of SNAP benefits. A regression formula is applied to 

the results of the reviews to calculate official error rates. State agencies review selected cases 

monthly to determine the accuracy of the eligibility and benefit-level determination. The 

process includes a client interview and verification of all elements of eligibility and the basis of 

issuance. Federal reviewers validate a sample of the State’s reviews by conducting a re-review.

The most current data available for this measure are for FY 2012. The payment accuracy rate of 

96.58 percent met the performance goal/measure target. FY 2013 performance will be reported 

in next year’s report.

Reliability of Data — QC data are valid and accepted by State SNAP agencies as a basis for 

performance-incentive payments and penalties. The U.S. Government Accountability Office 

and the Office of Inspector General also use it regularly.

Quality of Data — As described above, the data used to develop this measure are used widely 

for multiple purposes, both within and outside USDA. The measure itself is frequently cited as 

an important, high-quality indicator of program performance.

Challenges for the Future

The most critical challenge impacting future success is continuing resource limitations for State 

agencies. State budgets have been, and will continue to be, extremely tight. This factor could 

hurt State performance in payment accuracy. USDA will continue to provide technical assistance 

and support to maintain payment accuracy in the context of this difficult program environment.

Participation levels for the major Federal nutrition assistance programs – National School 

Lunch Program (NSLP) (millions per day) and School Breakfast Program (SBP) (millions per 

day)

Analysis of Results

USDA met the targets for these performance measures. The increased use of direct certification 

for free school meals for children enrolled in means-tested programs such as SNAP or the 

Temporary Assistance for Needy Families (TANF) program has helped to provide easy access to 

school meal benefits. During the 2011–2012 school year, 89 percent of school districts used 

direct certification, to enroll 11.6 million children in the lunch program – 1.7 million more than 

in the previous year. TANF provides financial assistance for children and their parents or 

relatives who are living with them. The numbers detailed below for NSLP and SBP participation 

show a continuing trend of increases over the last several years.
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Exhibit 33: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

4.1.3 Participation levels for

the major Federal 

nutrition assistance 

programs (millions per 

day)

• National School 

Lunch Program 30.9 31.6 31.7 31.8 31.6 31.7 30.6 Met

• School Breakfast 

Program 10.6 11.0 11.7 12.1 12.9 13.4 13.1 Met

Allowable Data Range for Met: Thresholds for these measures reflect the margin of error in 

forecasts of future participation, estimated at 5 percent for school meals programs. This figure 

reflects the pattern of variance between actual and target performance for both programs 

during the past 5 years. For FY 2013, this percentage range allows for actual performance that 

meets the targets in the range of 30.1-33.3 million for NSLP and 12.7-14.1 million for SBP.

Completeness of Data — School meals participation data are drawn from USDA 

administrative records. State agency reports are certified accurate and submitted to regional 

offices. There, they are reviewed for completeness and consistency. If the data are acceptable, 

the regional analyst posts them to the National Data Bank (NDB) Preload System. NDB is a 

holding area for data review prior to release. Otherwise, regional-office personnel reject the 

report, and the State agency is contacted. Data posted by regional personnel into NDB are 

reviewed at USDA. If data are reasonable and consistent with previous reports, they will be 

downloaded to NDB for public release. If not, USDA works with regional offices and States to 

resolve problems and inconsistencies. This process of review and revision ensures that the data 

are as accurate and reliable as possible.

Figures for NSLP and SBP are based on 9-month (school year) averages. Participation data are 

collected and validated monthly before being declared annual data. 

Reliability of Data — Participation-data reporting used in published analyses, studies, and 

reports. They also are used to support dialogue with, and information requests from, the 

Government Accountability Office, the Office of Inspector General, and the Office of 

Management and Budget.

Quality of Data — As described above, the data used to develop this measure are used widely 

for multiple purposes, both within and outside USDA. The measure itself is reported in standalone publications as an important high-quality indicator of program performance.
PRIORITY GOALS

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Challenges for the Future

While almost all schoolchildren have access to Federally-subsidized school lunches, significantly 

fewer schools operate SBPs. USDA will continue to pursue strategies to ensure that all students 

are able to start the day with a nutritious breakfast, at home or at school.

As with other nutrition assistance programs, the Department relies on its partnerships with third 

parties—hundreds of thousands of State and local Government workers and their cooperators—

to sustain effective school meals program delivery.

Participation levels for the major Federal nutrition assistance programs: The Special 

Supplemental Nutrition Program for Women, Infants and Children (average)

Analysis of Results

USDA met the target for this performance measure, showing its ongoing commitment to 

providing sufficient program resources to support participation for all eligible people who apply 

for benefits.

The Department estimates the number of WIC-eligible people and calculates the rate at which 

they are participating. The latest study shows that, in 2010, WIC served an estimated 62.6 

percent of the population eligible for benefits. This figure reflects participation by almost 85 

percent of eligible infants, almost 71 percent of eligible pregnant women, more than 85 percent 

of eligible breastfeeding women, and 81 percent of eligible postpartum women.

Exhibit 34: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

4.1.4 Participation levels for 

the major Federal 

nutrition assistance 

programs (millions per 

month): WIC Program 

(average)

8.7 9.1 9.2 8.9 8.9 8.9 8.7 Met

Allowable Data Range for Met: Thresholds for this measure reflect the margin of error in 

forecast of future participation, estimated at 3 percent for the WIC program. This reflects the 

pattern of variance between actual and target performance over the past 5 years. For FY 2013, 

this percentage thus allows for actual performance that meets the target in the range of 8.6-9.2 

million for WIC.
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Completeness of Data — WIC participation data are drawn from USDA administrative 

records. State agency reports are certified accurate and submitted to regional offices. There, 

they are reviewed for completeness and consistency. If the data are acceptable, the regional 

analyst posts them to the National Data Bank (NDB) Preload System. NDB is a holding area for 

data review prior to release. Otherwise, regional-office personnel reject the report, and the State 

agency is contacted. Data posted by regional personnel into NDB are reviewed at USDA. If 

data are reasonable and consistent with previous reports, they will be downloaded to NDB for 

public release. If not, USDA works with regional offices and States to resolve problems and 

inconsistencies. This process of review and revision ensures that the data are as accurate and 

reliable as possible.

Figures represent 12-month, fiscal year averages. Participation data are collected and validated 

monthly before being declared annual data.

Reliability of Data — Participation-data reporting is used to support program financial 

operations. Data is used to support dialogue with and information requests from the 

Government Accountability Office, the Office of Inspector General, and the Office of 

Management and Budget.

Quality of Data — The data used to develop this measure are used widely for multiple 

purposes, both within and outside USDA. The measure itself is reported in stand-alone 

publications as an important high-quality indicator of program performance.

Challenges for the Future

Ensuring that adequate, timely funding is available to USDA’s program partners to support 

participation among all eligible applicants is an ongoing challenge. The Department and its 

partners must continue to work together to manage funds carefully and maintain efficient 

operations to serve all those in need.

Objective 4.2: Promote Healthy Diet and Physical Activity Behavior

Application and usage level of nutritional guidance tools

Analysis of Results

USDA exceeded the target for this performance measure. The Department continued to meet its 

commitment to link science-based information to the nutrition needs of Americans across the life 

cycle. It successfully reached Americans through the use of print materials and electronic tools. 

The Department also used social media and partnerships, as well as 

http://www.choosemyplate.gov/, http://nutritionevidencelibrary.gov/, and the Food and Nutrition 

Information center at http://fnic.nal.usda.gov/, to provide information that consumers can use to 

improve their diets and maintain active lifestyles.
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Exhibit 35: Performance Goal Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

4.2.1 Application and usage 

level of nutrition 

guidance tools (billions 

of pieces of nutrition 

guidance distributed) 

Baseline: 2006 = 1.5

3.2 3.5 1.7 1.7 6.6 4.0 9.9 Exceeded

Allowable Data Range for Met: The precision of USDA’s tracking system and forecasting 

allows for determination of the degree to which the 2013 target range of 3.6 to 4.4 billion is 

met. Thresholds reflect trends of usage levels at http://www.choosemyplate.gov/, 

http://nutritionevidencelibrary.gov/, other USDA Web sites, such as SNAP-ED Connection at 

http://snap.nal.usda.gov/, as well as the distribution of MyPlate and Dietary Guidelines print 

materials. 

Completeness of Data —Data related to http://www.choosemyplate.gov/ are collected 

instantaneously, indicating the number of e-hits to the Web site and the number of registrations 

to the SuperTracker. For print materials, data from national headquarters represent counts of 

what was distributed among divisions of USDA and FNIC.

Reliability of Data — The electronic data are instantaneously recorded, and the number of 

distributed print materials is tracked.

Quality of Data — The data report on the use of information and tools at 

http://www.choosemyplate.gov/ and http://nutritionevidencelibrary.gov/. Because of the 

simultaneous recording of data, the Department is able to estimate accurately the degree to 

which consumers are using or requesting nutrition materials at http://www.choosemyplate.gov/

and http://nutritionevidencelibrary.gov/, and other Department Web sites that provide 

materials related to the 2010 Dietary Guidelines for Americans. 

Challenges for the Future

Individuals and families make choices every day about what they will eat and drink and their 

level of physical activity. Today, Americans must make these choices within a social 

environment that often promotes overconsumption of calories and discourages physical activity. 

The ability of existing nutrition guidance and promotional materials to achieve behavior change 

remains challenging. Physical activity and other lifestyle issues also significantly impact body 

weight and health.

Crafting understandable, science-based, consistent, and consumer-friendly nutrition messages 

and education programs that help people make better food choices will continue to be 

challenging. The relationships between choices people make and their attitudes toward and 

knowledge of diet/health links are key factors that must be addressed. The data that can address 

this information gap, however, are limited. Work is planned to develop helpful metrics to 

measure the success of communications and promotion programs. 
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Objective 4.3: Protect Public Health by Ensuring Food is Safe

Percent of broiler plants passing the carcass Salmonella Verification Testing Standard

Total illnesses from all Food Safety and Inspection Service products

Percent of establishments with a functional food defense plan

Analysis of Results

USDA did not meet its goal for the first two measures, but exceeded the goal for the third.

Percent of Broiler Plants Passing the Carcass Salmonella Verification Testing Standard

In July 2011, USDA updated Salmonella standards and established new Campylobacter 

performance standards for young chickens and turkeys that took effect with Department 

verification sample sets. The Salmonella standards are tighter than previous standards and are 

based on more recent USDA baseline data. USDA started assessing establishments using the 

2011 standard in July 2011, but this performance measure was first reported in the USDA 

Performance and Accountability Report in 2012.

Total Illnesses from All USDA Products

The Department calculates a measure that estimates all foodborne illnesses for Salmonella, 

Listeria monocytogenes (Lm), and E. coli O157:H7 from USDA-regulated products. Salmonella

contributes the largest burden of illnesses to the All Illness Measure, with 92% of all illnesses in 

the Measure associated with Salmonella. Estimates of total illness from all USDA-regulated 

products are based on case rates from the Centers for Diseases Control and Prevention’s (CDC)

FoodNet data. They also are based on simple food attribution estimates derived from the CDC’s 

Foodborne Disease Outbreak Surveillance System (FDOSS) outbreak database. These estimates 

then are linked to the Department of Health and Human Services (DHHS) Healthy People 2020

pathogen reduction goals. Healthy People 2020 provides a set of goals and objectives with 10-

year targets, designed to guide national health promotion and disease prevention efforts, 

improving the health of all people in the United States.

Percent of Establishments with a Functional Food Defense Plan 

The food defense measure was developed to increase the number of establishments with 

functional food defense plans. USDA considers such an increase important to prevent intentional 

product adulteration. To be considered functional, plans should be developed, written, 

implemented, assessed, and maintained by establishments. The Department has developed and 

distributed guidance materials for establishments to assist in the development and understanding 

of what constitutes a functional food defense plan. This performance metric is measured by a 

USDA survey of its inspection personnel that collects data on industry’s voluntary adoption of 

food defense plans. Results from the first survey, conducted in August 2006, established a 

baseline adoption rate of food defense plans, by industry, of 34 percent of all establishments 

(large, small, and very small). The Department’s goal for the voluntary adoption of functional 

food defense plans by FY 2015 is 90 percent. USDA exceeded Measure 4.3.3 with 83% of 

establishments adopting functional food defense plans in FY2013. USDA is also taking actions 

such as mailing and calling establishments that lack a food defense plan to encourage the 
PRIORITY GOALS

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development of a plan. USDA has also developed a scenario-based kit for industry that focuses 

on the importance of food defense plans and written recall procedures. These kits include 

webinars instructing industry on how to use the exercise kit. Adoption of food defense plans will 

be evaluated by the 2014 Food Defense Survey, which is scheduled to be conducted in August 

2014.

Exhibit 36: Performance Goals Results

Annual 

Performance 

Goals, 

Indicators, 

and Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

4.3.1 NA NA NA 89% 90% 91% 90% Unmet

4.3.2 457,797 428,280 470,137 491,353 479,621 394,770 427,171 Unmet

4.3.3 46% 62% 74% 75% 77% 81% 83%

Exceede

d

Allowable Data Range for Met: There is no range of tolerance for USDA measures.

4.3.1 - The target was set as an attainable target based on the agency’s baseline assessment of 

industry performance, and past agency experience with industry’s response to Salmonella

policies (see the “New Performance Standards for Salmonella and Campylobacter in Young 

Chicken and Turkey Slaughter Establishments; New Compliance Guides” Federal Register

Notice for further details).

4.3.2 - Estimates of total illness from all USDA-regulated products are based on case rates from 

CDC’s FoodNet data and simple food attribution estimates derived from the FDOSS outbreak 

database. They are linked to the DHHS Healthy People 2020 pathogen reduction goals.

4.3.3 - Data for 2008 represent the percentage of facilities with a written plan. The data from 

2009-2012 represent the percentage of facilities with a functional plan, as defined above. 

USDA has been working with establishments to encourage them to voluntarily adopt functional 

food defense plans. 

Completeness of Data

4.3.1 - Results are based upon USDA’s laboratory final results. 

4.3.2 - CDC FoodNet case rates lag by one quarter, meaning that illness estimates lag by one 

quarter. In early FY2012, USDA obtained new attribution data from the CDC. Using this data, 

USDA updated the attribution estimates to include the years 2008-2010. These 2008-2010 

attribution estimates were used to calculate the All Illness Measure beginning in Q1 FY 2013.

4.3.3 - The Food Defense Plan Survey is conducted annually. 
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Reliability of Data

4.3.1 - The data are based on testing and verification from the USDA’s field service 

laboratories for regulated establishments. Each sample is subjected to highly specific 

verification testing. The primary goal of the Salmonella sampling program is to monitor how 

well each establishment is maintaining control of food safety through its Hazard Analysis and 

Critical Control Points (HACCP) program, sanitation, and supporting programs. USDA 

recognizes that its verification testing samples for Salmonella in raw classes of product are 

biased in favor of being collected at establishments with poor process controls or higher 

volume. This factor may result in over-estimates of public exposure to this pathogen. 

4.3.2 - The CDC FoodNet program provides active, population-based surveillance for 

laboratory-confirmed infections. However, these data are subject to limitations. The CDC 

FDOSS program is a passive surveillance system. CDC collects reports of foodborne outbreaks 

due to enteric bacterial, viral, parasitic, and chemical agents. State, local, and territorial public 

health agencies report these outbreaks to the FDOSS. The CDC surveillance team analyzes 

these data to understand the impact of foodborne outbreaks, and the pathogens, foods, settings, 

and contributing factors (for example, food not kept at the right temperature) involved. As with 

the FoodNet program, these data are subject to limitations.1

4.3.3 - USDA Inspection Program Personnel (IPP) complete the food defense plan survey based 

on discussions with establishment management. 

Quality of Data

4.3.1 - USDA collects pathogen verification samples at a range of establishments. Testing is 

conducted to verify establishment pathogen reduction activities. 

4.3.2 - The CDC FoodNet data include 10 States and about 15 percent of the U.S. population. 

The surveillance area is generally representative of the U.S. population.2 State, local, and 

territorial public health agencies report the outbreaks to the CDC and the quality of the data can 

vary by reporting agency.

4.3.3 - USDA IPP complete the food defense plan survey based on discussions with 

establishment management. The data are complete, with surveys conducted at approximately 96 

percent or higher (since 2010) of targeted establishments.

 

1 http://www.cdc.gov/foodsafety/fdoss/faq/faq-food-tool.html

2 http://www.cdc.gov/foodnet/about.html
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Actions for Unmet Measures 

Salmonella Verification Testing Measure (4.3.1):

USDA nearly achieved the FY 2013 target of 91% set for Measure 4.3.1. To achieve the FY 

2013 target, only 2 more broiler establishments would have needed to pass the performance 

standard (171 establishments passing as compared to 169 establishments passing). Historically, 

since USDA began tracking the pass/fail rate of broiler plants, the percent passing has steadily 

increased. Aside from the performance of the establishments, which is not in the direct control 

of USDA, the Department can and has improved on the operating parameters that influence the 

Salmonella verification testing program, such as improving the discard rate for collected samples 

and adjusting the sampling frame to account for eligibility factors not programmed into the 

original measure. 

All Illness Measure (4.3.2):

Although USDA did not achieve the FY 2013 illness reduction targets set for the All-Illness 

Measure, there were nearly 28,400 fewer estimated illnesses in FY 2013 as compared to FY

2012, with the majority of the reductions in estimated illness coming from Salmonella. Further, 

while the All-Illness Measure is not within the direct control of USDA, as a public health 

agency, reducing attributable illnesses will always be our goal. 

As the Salmonella performance measure focuses on reductions in Salmonella contamination at 

the establishment level and Salmonella illnesses are the largest contributor (90 percent) to the 

All-Illness Measure, USDA has focused much of its attention on addressing this pathogen. 

These efforts include establishing in September, 2012 a Strategic Performance Working Group 

(SPWG), which first focused on identifying potential interventions or actions to decrease USDAattributable Salmonellosis. Additionally, since the All-Illness Measure was created, 

Salmonellosis estimates have continued at a steady high or slightly increased rate despite USDA 

interventions. The SPWG organized a series of meetings and hosted a blog for internal USDA 

discussions, with representation from all USDA program areas, to identify actions that the 

agency should take to help decrease USDA-attributable Salmonella illnesses. From those 

discussions, the SPWG developed a Salmonella Action Plan. Among the major initiatives 

discussed in the Plan are: 1) finalizing the Poultry Slaughter rule, 2) implementing new sampling 

programs, 3) developing new in-plant strategies, 4) developing new policy documents (sanitary 

dressing for hogs), 5) modifying Salmonella performance standard category posting, 6) 

developing new performance standards, 7) developing new enforcement strategies, 8) exploring 

and utilizing new scientific research on Salmonella contamination in regulated carcasses (lymph 

node study), 9) investigating pre-harvest activities, and 10) focusing the Agency’s education and 

outreach tools on Salmonella. Released publicly on December 4th, 2013, the plan delineates the 

Department’s combined, future plans to combat Salmonella.

Additionally, USDA has completed a baseline for Salmonella on chicken parts and is using these 

data to develop new standards. Given that chicken parts are processed from whole carcasses, 

standards to lower Salmonella on parts may have the effect of encouraging establishments to 

lower Salmonella further on carcasses.
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USDA plans to analyze all samples collected for Shiga toxin-producing E. coli (STEC) for 

Salmonella. This will significantly increase data available to USDA on Salmonella in beef 

products, which is important because Salmonella outbreaks associated with beef products 

continue to occur. USDA will use the new data to estimate prevalence and develop new 

Salmonella stands for beef products. USDA is currently analyzing comments and intends to 

announce final plans soon. 

USDA also published a Federal Register Notice (FRN), December 6, 2012, that required 

establishments to reassess their HACCP plans for comminuted not-ready-to-eat (NRTE) chicken 

or turkey products, including final products or intermediary product for further processing as 

NRTE product. Such product includes any NRTE chicken or turkey product that has been 

ground, mechanically separated, or hand- or mechanically-deboned and further chopped, flaked, 

minced or otherwise processed to reduce particle size. In addition, the FRN announced that 

USDA would begin sampling non-breaded, non-battered, comminuted product for Salmonella. 

USDA began this new sampling in June 2013. USDA expects to use this exploratory testing 

program as the mechanism to obtain samples to determine prevalence of Salmonella in 

comminuted poultry and will use the results from this sampling to develop performance 

standards for these products. USDA also expects to analyze the samples for Campylobacter and 

for other microorganisms that could serve as indicators of process control. 

USDA has expanded on work conducted using CDC outbreak data to estimate the All-Illness 

Measure and the total number of estimated Salmonella illnesses. Specifically, the USDA is 

using CDC outbreak data to conduct analyses to estimate the number of Salmonella illnesses 

associated with each regulated product. This analysis will be used to rank and prioritize those 

products that are causing the most illness for the purpose of directing USDA policy. For 

example, this analysis has indicated that USDA should potentially focus more verification 

resources on pork products as a relatively substantial portion of Salmonella illnesses are 

attributed to consumption of pork. Therefore, USDA is currently developing an exploratory pork 

sampling program, with the intention of developing performance standards for pork products, 

which should have the effect of lowering Salmonella illnesses attributed to pork. USDA has also 

developed guidance on how establishments can work to reduce Salmonella in market hogs. 

In FY 2013, USDA entered into an interagency agreement with FDA to develop and implement a 

new consumer food safety survey in FY 2014, with results published in 2015. The proposed 

Food Safety Survey is designed to meet the information and evaluation needs of the regulatory 

and consumer education food safety initiatives underway at USDA and FDA. FDA has begun to 

develop the FY 2014 survey instrument and will collaborate with USDA during the fall months 

on question design. This survey will be the sixth in a series of consumer surveys conducted by 

FDA since 1988. 

Further, as the All-Illness Measure includes illnesses from both E. coli O157:H7 and Lm, USDA 

is also taking steps to reduce illnesses from these pathogens. USDA has changed its E. coli O157 

sampling program so that it can increase the likelihood of detecting the pathogen in beef 

manufacturing trimmings. The Department also has updated its guidance to help very small 

meat and poultry plants meet initial validation requirements and is analyzing comments on the 

guidance. The Department is analyzing samples of beef manufacturing trimmings for E. coli

O157:H7 and also for the six non-O157 STECs that USDA declared to be adulterants. 
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USDA’s efforts to address Lm include drafted best practice guidelines for retailers, based on risk 

assessment findings, to help protect public health by decreasing the potential for Lm

contamination at retail. USDA will announce the availability of the guidance in the Federal 

Register and encourage retailers to begin using the guidance. USDA also plans to develop a 

surveillance tool that will be used to evaluate conditions at retail – part of Phase II of the Retail 

Lm Project. In summary, these actions are designed to reduce the presence of pathogens, improve 

the protection of the food supply and reduce the overall number of foodborne illnesses 

experienced by American consumers.

Challenges for the Future

Ensuring the safety of the Nation’s meat, poultry and processed egg products is a significant 

undertaking that requires a strong and robust infrastructure coupled with sound science. USDA 

uses a data-driven, scientific approach to food safety that incorporates public health data critical 

to combating evolving threats. Educating producers about best practices on the farm, and 

educating retailers and the public on the best food-handling practices, are important tools for the 

Department to utilize.

While USDA firmly believes that its day-to-day activities directly impact the prevention of 

foodborne illness in this country, it is often challenging to link Department activities, such as 

pathogen verification testing, to reductions in foodborne illness. 

In 2011, the Department teamed with CDC and the Food and Drug Administration (FDA) to 

form the Interagency Food Safety Analytics Collaboration (IFSAC). IFSAC’s primary objective 

is to better estimate source attribution of infections to specific foods and settings. Better 

estimation of the attribution of illnesses across the broad range of commodities and points in the 

food chain will help improve food safety practices. It is anticipated that results from attribution 

projects developed out of the IFSAC initiative will be used to establish specific illness reduction 

performance goals for the All Illness Measure for Campylobacter and E. coli non-O157 STEC. 

Objective 4.4: Protect Agricultural Health by Minimizing Major Diseases and Pests to 

Ensure Access to Safe, Plentiful, and Nutritious Food

Value of damage prevented and mitigated annually as a result of selected plant and animal 

health monitoring and surveillance efforts

Analysis of Results

USDA exceeded the target for this performance measure by preventing and mitigating 

$1.26 billion in damage from of selected plant and animal health monitoring and surveillance 

efforts. By controlling the spread of animal diseases, the Department preserves animal health, 

improve the Nation’s economy, and minimize the spread of diseases from animals to humans. In 

FY 2013, there were no significant outbreaks of animal diseases that spread beyond the point of 

introduction. The USDA Animal Disease Traceability framework improves cooperation and 

coordination of Federal, State, Tribal, and private animal health professionals in identifying

diseased animals, quickly tracing their movements, and controlling disease spread to protect the 

livestock industry. USDA published a final rule on January 9, 2013, establishing general 

regulations for improving the traceability of interstate movement of U.S. livestock. On March 

11, 2013, the final rule became effective, which unless specifically exempted, livestock moved 
PRIORITY GOALS

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interstate must be officially identified and accompanied by documentation, such as ownershipper statements or brand certificates. USDA is working with all 50 States and several Tribal 

nations to develop long-term strategic plans to implement the final rule. As a result, USDA is 

better positioned to know where diseased and at-risk animals are located to help preserve animal 

health, reduce the number of animal illness and deaths if outbreaks occur, ensure a rapid 

response if an animal disease event should take place, and decrease the cost to producers, 

consumers, and the government. 

USDA takes a similar approach to plant pests and diseases by focusing on the early detection of 

new introductions, the prevention of outbreaks, and the eradication or mitigation of economically

significant pests and diseases. The Department also documents pest and disease status to support 

farmers in the export of their products. These activities help ensure the availability of fresh fruits 

and vegetables for U.S. consumers and those abroad by preventing crop damage. In FY 2013, 

USDA supported surveys in all 50 States and 2 United States territories for exotic pests. Survey 

targets included pests of a variety of specialty crops, including grapes, citrus, stone fruits, and 

tomatoes, as well as honeybee pests. Also, in FY 2013, USDA targeted 334 unique pests for 

survey. The Department also continued control or eradication efforts against economically 

significant pests that threaten fruit and vegetable production. For example, USDA continued a 

successful program targeting the European grapevine moth in Napa County and surrounding 

areas in California in FY 2013. Cooperative efforts with the State and industry have reduced 

detections of this devastating grape pest to 40 months in FY 2013 (compared to 78 the previous 

year and down from more than 10,000 moths in the program’s first year).

Exhibit 37: Performance Goals Results

Annual Performance 

Goals, Indicators, and 

Trends 2008 2009 2010 2011 2012

Fiscal Year 2013

Target Actual Result

4.4.1 Value of damage 

prevented and 

mitigated annually as a 

result of selected plant 

and animal health 

monitoring and 

surveillance efforts 

($billions)

1.38 1.05 1.07 1.11 1.19 1.18 1.26 Exceeded

Allowable Data Range for Met: The aggregate value of protected agricultural resources 

fluctuates every year due to the size and scope of pest/disease outbreaks and the annual price 

levels of resources. For FY 2013, the allowable data range for the aggregate value of protected 

agricultural resources is estimated to be between $1.12 billion to $1.24 billion.
PRIORITY GOALS

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Completeness of Data — Data for animal health programs are entered by State partners into a 

USDA database. They are verified by agency officials to document the results of surveillance 

efforts and the health status of the U.S. herd. Data for plant health programs are maintained in 

the Cooperative Agricultural Pest Survey program database. The estimated value of savings is 

a calculation of the costs associated with conducting monitoring and surveillance programs, 

versus potential losses of not having these programs in place.

Reported data are actual results.

Reliability of Data — The surveillance results are used by both internal managers and 

external partners and stakeholders as an authoritative source of information.

Quality of Data — USDA ensures the information reported on its web site accurately reflects 

the status of U.S. plant and animal health. 

Challenges for the Future

USDA must continually prioritize the list of major pest and disease threats. These threats are 

increasing both domestically and internationally. In addition, the Department’s monitoring and 

surveillance efforts will need to be adjusted to respond to these threats. This action will protect 

agricultural resources and help ensure that America has access to nutritious foods. 

National security is a significant, ongoing priority for the Department. USDA is working with 

the U.S. Department of Homeland Security to help protect agriculture from intentional and 

accidental acts that might impact America’s food supply or natural resources.

Cross Agency Priority Goals

The Federal Government has adopted a limited number of Cross-Agency Priority (CAP) Goals to 

improve cross-agency coordination and best practice sharing. Per the Government Performance 

and Results Act Modernization Act of 2010, the Department is required to address CAP Goals in 

its strategic plan, annual performance plan, and annual performance report. Please refer to 

http://www.performance.gov/ for the U.S. Department of Agriculture (USDA) contributions to 

the interdepartmental CAP goals and progress, where applicable. 

Agency Priority Goals (APGs)

The U.S. Department of Agriculture (USDA) identified three short-term Agency Priority Goals 

for fiscal years (FYs) 2012 and 2013. These APGs are:
PRIORITY GOALS

57

APG: Rural Prosperity through Exports

Goal Statement: Assist rural communities build and maintain prosperity through increased 

agricultural exports. 

Proposed Results: By September 30, 2013, the U.S. Department of Agriculture (USDA) will 

expand U.S. agricultural exports to at least $150 billion to assist rural communities to build and 

maintain prosperity through increased agricultural exports.

Results Achieved: While USDA did not achieve its short-term target, agricultural exports 

reached $141 billion in FY 2013. For every $1 billion of agricultural exports, an estimated 6,577

jobs are created and an additional $1.27 billion in economic activity is generated. USDA 

continued to use all available resources to increase exports and adjust market development and 

maintenance efforts based on changes in the global economic environment. The Department 

supported trade agreement negotiations; monitoring and enforcing of existing trade agreements; 

capacity building in emerging trading partners; and promotion of U.S. products overseas. USDA 

supported access to international markets through market development programs and trade 

shows, which leads to direct sales by connecting exporters with foreign buyers. USDA also 

resolved technical barriers to trade and unjustified sanitary and phytosanitary measures.

APG: Enhanced Water Resources

Goal Statement: Accelerate the protection of clean, abundant water resources. 

Proposed Results: By September 30, 2013, accelerate the protection of clean, abundant water 

resources by advancing USDA’s capacity to measure the effectiveness of conservation 

investments in addressing water resource concerns. In FY 2012 and FY 2013 USDA will 

develop and implement an interagency water resource outcome metric in two pilot watersheds 

and quantify improvements in those watersheds.

Results Achieved: USDA implemented two project watersheds, the St. Joseph River Watershed 

Project in Indiana, and the Cienega Creek Watershed Project in Arizona. The research from these 

projects demonstrates why both condition and effectiveness frameworks consisting of monitoring 

and modeling are needed to assess and evaluate water-quality improvements. These approaches 

will enable USDA agencies and their partners to build better performance measures into their 

programs and use the results to improve their work and guide future investments so as to more 

efficiently and effectively achieve the Nation’s water goals.
PRIORITY GOALS

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APG: High Payment Accuracy

Goal Statement: Further improve payment accuracy of the Supplemental Nutrition Assistance 

Program (SNAP). 

Proposed Results: By September 30, 2013, USDA will improve the Supplemental Nutrition 

Assistance Program (SNAP) payment accuracy rate, which is at an all-time high of 96.58 

percent.

Results Achieved: Payment accuracy has reached a record high of 96.58 percent. This 

combined rate reflects 2.77 percent in overpayments and 0.65 percent in underpayments for a 

total of 3.42 percent in erroneous payments. USDA’s Food and Nutrition Service (FNS) has 

continued to work to improve payment accuracy through partnerships with States and by 

rewarding exemplary performance while holding low-performing States accountable. FNS uses 

an early detection system to target States that may be experiencing a higher incidence of 

payment errors. FNS then intervenes to address situations identified in individual States. FNS 

provides technical assistance and knowledge to State agencies to improve payment accuracy and 

shares best practices among States.