U.S. Department of Labor

Evidence-Building Plan

2O22

2O26

FISCAL YEARS

U.S. Department of Labor
DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Table of Contents

Click to view page

Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .i

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

I. What is the Evidence-Building Plan and Who Should Use It? . . . . . . . . . . . . . 1

Defining Evidence � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 2

Scope and Coverage of Activities in this Plan � � � � � � � � � � � � � � � � � � � � � � � 3

Evidence Officials at the U.S. Department of Labor � � � � � � � � � � � � � � � � � � � � 4

II. Stakeholder Engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

III. Planned Evidence-Building Activities by Priority Learning Area . . . . . . . . . . . 8

Priority Learning Area 1: Ensuring Equity in Employment and Training Programs � � � � � 9

Priority Learning Area 2: Reducing Barriers to Women’s Employment � � � � � � � � � � �13

Priority Learning Area 3: Studying Effects of the COVID-19 Pandemic � � � � � � � � � �15

Priority Learning Area 4: Improving Enforcement Activities & Protections for All � � � � � �17

Priority Learning Area 5: Strengthening Unemployment to Reemployment � � � � � � � �27

Additional Planned Learning Activities � � � � � � � � � � � � � � � � � � � � � � � � � � �29

IV. Cross-Cutting Evidence Building Activities . . . . . . . . . . . . . . . . . . . . . . .33

DOL Scholars Program � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �33

Data Challenge for Emerging Scholars & Academics � � � � � � � � � � � � � � � � � � �33

Increasing Diversity Among DOL-Funded Research Partners � � � � � � � � � � � � � � �34

Clearinghouse for Labor Evaluation and Research (CLEAR) � � � � � � � � � � � � � � �35

DOL Staff Capacity Building: Evaluation, Measurement, 

and Analytics Training Program � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �36

Improved Measurement & Data Collection of Key Constructs � � � � � � � � � � � � � � �36

Improving DOL’s Data Infrastructure � � � � � � � � � � � � � � � � � � � � � � � � � � � �38

V. Potential Future Evidence-Building Topics . . . . . . . . . . . . . . . . . . . . . . .41

Appendix A. Mapping of Planned Departmental Evidence-Building Activities 

by DOL Strategic Goal � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �42
i DOL EVIDENCE-BUILDING PLAN

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Foreword

How can the Department of Labor (DOL) train vulnerable workers on health and safety practices to 

reduce workplace injuries? What are the policies that could support gainful employment for young 

adults with developmental disabilities? How can the Department of Labor encourage more participation 

in apprenticeships, especially among women workers of color? And can partnerships between the 

Department of Labor, state governments, and community-based organizations help expand access to 

unemployment insurance among eligible workers? 

These are just a few of the research questions that DOL agencies plan to study over the next four years as 

summarized in our FY 2022-2026 Evidence Building Plan. The breadth of these questions—representing 

contributions from sixteen DOL agencies—affirms DOL’s commitment to integrating evidence into agency 

functions, including policy development, budget and strategic planning, program administration, and 

performance management. These projects also highlight the close alignment between the department’s 

evidence-building activities and the short, medium, and long-run objectives of each individual agency, the 

department as a whole, and the Biden-Harris Administration. 

An especially important priority in preparing this plan has been meeting the groundbreaking charge 

issued to all federal agencies in Executive Order 13985. That Executive Order asks agencies to assess 

how federal programs, policies, and contracting opportunities reach historically excluded or marginalized 

communities, including people of color, women and persons with disabilities, and then to take steps to 

advance greater inclusion of those populations. 

At the Department of Labor, we have already embarked on a number of activities in service of this charge, 

and this Evidence-Building Plan represents a particularly integral contribution. We need high-quality, timely 

evidence to first establish which populations may be excluded from departmental initiatives and benefits; 

to formulate policy shifts targeting activities, resources, and interventions to populations in need; and 

finally, to investigate whether and how those interventions meaningfully change the material conditions of 

underserved communities. 

Taken together, the projects detailed in this plan speak to each step of the evidence-to policy lifecycle, 

thereby helping the Department of Labor deliver its programs and resources, and benefits more equitably 

to all workers.

ALEXANDER HERTEL-FERNANDEZ

Deputy Assistant Secretary for Research and Evaluation
ii DOL EVIDENCE-BUILDING PLAN

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Summary

The Department of Labor’s Evidence-Building Plan is a project-based learning roadmap, describing over 

40 new activities to generate credible information in response to important short- and long-term strategic 

and operational questions. Credible information, or evidence, may stem from program evaluations, 

foundational fact-finding or research, policy analyses, or performance data. The Evidence-Building Plan is 

the cumulative product of each DOL agency’s individual learning agenda, a prioritization process to identify 

information they need to know in order to achieve their agency and departmental mission. Sixteen DOL 

agencies have contributed to this document, coordinated by DOL’s Chief Evaluation Office in consultation 

with the department’s four Evidence Officials. 

Evidence-building activities that DOL will conduct in Fiscal Years 2022-2026 are focused on DOL’s five 

Priority Learning Areas: improving equity in employment and training programs, reducing barriers to 

women’s employment, studying the effects of the COVID-19 pandemic, improving enforcement activities 

and protections for all, and strengthening unemployment to reemployment. In addition, the department 

commits to a number of cross-cutting activities to improve capacity to develop, access, understand and use 

evidence. Lastly, the department outlines potential topics for future evidence-building activities.
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Across the department, these evidence documents are useful in helping to:

• Build upon and scale prior successes, as well as for continuous improvement of 

DOL practices, policies, and programs;

• Identify new questions to advance understanding;

• Innovate and develop data-informed approaches to answer priority questions;

• Seek opportunities to coordinate evidence-building activities across the department 

and other federal agencies; 

•

•

Monitor and assess progress along complex and multidimensional learning goals; and

Communicate to Congress, state and local partners, grantees, and the public about 

new and ongoing areas of investment for data-informed insights. 

I. What is the Evidence-Building Plan 

and Who Should Use It?

The Evidence-Building Plan, also referred to as a “learning agenda” by Office of Management and Budget 

(OMB) Memorandum M-19-23, is a systematic plan for identifying and addressing priority questions relevant to 

improving the programs, policies, and regulations of the Department of Labor (department or DOL). The plan 

identifies and prioritizes strategies to develop credible information to answer important short- and long-term 

strategic and operational questions. 

All of the department’s evidence documents, including the Evidence-Building Plan, Evaluation Plan, and 

Evidence Capacity Assessment, are developed collaboratively with the internal agency stakeholders, 

departmental leadership, and the department’s Evidence Officials. Each internal agency develops individual 

learning agendas, which roll up to the department’s evidence documents. These subcomponent learning 

agendas and processes provide an infrastructure to customize and monitor their own learning roadmaps, in 

addition to contributing to the broader departmental strategic mission. 
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Policy

Analysis

Performance

Measurement

Program

Evaluation

Foundational

Fact-Finding

Program Evaluation. Systematic analysis of a 

program, policy, organization, or a component of 

these to assess effectiveness and efficiency.

Foundational Fact Finding. Foundational 

research and analysis such as aggregate 

indicators, exploratory studies, descriptive 

statistics, and basic research.

Policy Analysis. Analysis of data, such as 

general purpose surveys or program-specific 

data, to generate and inform policy (e.g., 

estimating regulatory impacts and other 

relevant effects).

Performance Management. Development, 

analysis, and reporting of performance 

measures and milestones related to the 

achievement of strategic goals and objectives.

Defining Evidence

OMB defines evidence as the available body of facts or information indicating whether a belief or proposition is 

true or valid. Evidence can be quantitative or qualitative and may come from a variety of sources. There are four 

types of evidence-building activities included in this plan, which align with the four interdependent components 

of evidence identified in OMB Memorandum M-19-23:
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Scope and Coverage of Activities in this Plan

DOL’s Evidence-Building Plan provides key priority learning areas and corresponding activities planned for 

initiation during the same four-year time period as the department’s strategic planning cycle for FY 2022-FY 2026. 

This planning document will remain iterative in its development, with annual refinements. 

The department’s mission is broad and diverse, touching the lives of unemployed, underemployed and working 

individuals, retirees, employers, and organizations that support employment, workforce information, training, 

security, benefits, and hiring and working conditions. Everything we do is based on a worker-centered vision for 

the department to empower all workers morning, noon and night. The agencies collectively working toward that 

vision through the activities in this plan are as follows:

• Bureau of International Labor Affairs 

(ILAB)

• Bureau of Labor Statistics (BLS)

• Employee Benefits Security 

Administration (EBSA)

• Employment and Training Administration 

(ETA)

• Mine Safety and Health Administration 

(MSHA)

• Occupational Safety and Health 

Administration (OSHA)

• Office of Disability Employment Policy 

(ODEP)

• Office of Federal Contract Compliance 

Programs (OFCCP)

• Office of Labor-Management 

Standards (OLMS)

• Office of the Assistant Secretary for 

Administration and Management 

(OASAM)

• Office of the Assistant Secretary 

for Policy (OASP)

• Office of the Chief Financial Officer 

(OCFO)

• Office of Workers’ Compensation 

Programs (OWCP)

• Veterans’ Employment and Training 

Service (VETS)

• Wage and Hour Division (WHD)

• Women’s Bureau (WB)
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Evidence Officials at the U.S. Department of Labor 

The department’s evidence-building capabilities span performance measurement, statistics, policy analysis, 

data governance, and program evaluation. With the passage of the Foundations for Evidence-Based 

Policymaking Act of 2018 (Evidence Act), the leadership roles overseeing those functions have been codified. 

The department’s Evidence Officials guide efforts to build and use credible information at a departmental level, 

working in partnership with counterparts across the department and other federal agencies, with the goal of 

informing the policies and programs that improve the lives and safety of American workers. Although each 

Evidence Official has a distinct role, all support the development and use of the data the department needs to 

advance its mission, strategic goals, and priorities.

Chief Evaluation Officer

The Chief Evaluation Officer coordinates, manages, and implements the department’s evaluation research 

program and leads the Chief Evaluation Office (CEO) in the Office of the Assistant Secretary for Policy. CEO 

works closely with the department’s agencies to conduct independent evaluation research and other rigorous 

data analyses that address priorities set by the Secretary and the agencies. The Chief Evaluation Officer is 

responsible for guiding the department’s learning agenda, annual evaluation plan, and research capacity 

assessment; directing the department’s Data Analytics Unit; overseeing the department’s Evaluation Policy that 

governs this research; and coordinating the development of this Evidence-Building Plan. The Chief Evaluation 

Officer is Dr. Christina Yancey.

Chief Data Officer

The Chief Data Officer (CDO) in the Office of the Assistant Secretary for Policy is responsible for data 

governance and lifecycle data management, and supporting the department in meeting the requirements of 

the Federal Data Strategy and Open Government Data Act. The CDO serves as chairman of the DOL Data 

Board, a departmental work group charged with leading efforts to improve the department’s data management 

processes, ensure that data are fit for purpose, increase capacity to leverage data as a strategic asset, develop 

and guide data strategy, management, and policy, work with the Chief Information Officer to align infrastructure 

with mission and to support more optimal data governance, stewardship, architecture, and use. The Chief Data 

Officer is Scott Gibbons.
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Director, Performance Management Center

The department’s Performance Management Center (PMC), which reports to the Performance Improvement 

Officer, supports all of the department in results-driven management through strategic planning, continuous 

process improvement, and performance planning and reporting. Further, PMC ensures the department meets 

requirements from the Government Performance and Results Modernization Act of 2010. The Director of the 

Performance Management Center, and Deputy Performance Improvement Officer, is Dennis Johnson.

Statistical Official, Commissioner of Labor Statistics

The Statistical Official for the Department of Labor is the Commissioner of Labor Statistics, who leads the 

department’s independent statistical agency, the Bureau of Labor Statistics (BLS). BLS provides critical 

statistical data on labor market activity, working conditions, price changes, and productivity in the U.S. 

economy to support widespread decision-making across public and private sectors, including the department’s 

continuous improvement efforts. In the role of Statistical Official, the Commissioner provides statistical guidance 

to all department agencies and ensures that BLS, and thus the department, meets the requirements of the 

Confidential Information Protection and Statistical Efficiency Act, re-codified in the Evidence Act. BLS also 

participates with Statistical Officials across the Federal government to identify and enhance statistical capacity 

and a statistical learning agenda to ensure the highest-quality statistical process and content. The department’s 

Statistical Official is Dr. William W. Beach.
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II. Stakeholder Engagement 

Prior to developing this plan, the department conducted activities to collect ideas and input on priority research 

topics from a wide range of stakeholders external to DOL that work with, use, or have an interest in laborrelated research. 

Targeted Engagement in the Workforce 

Development Field

Given the critical role of the department in supporting 

the public workforce system across the country, a 

diverse set of stakeholders were consulted on their 

evidence-building needs as part of the development 

of this Plan. From November 2020 to April 2021, the 

department sponsored unstructured group discussions 

and individual conversations with 104 individuals 

representing 53 organizations spanning the U.S. 

workforce development system (see Figure 1). 

The objectives of the meetings were to encourage 

participants to discuss what research, information, or 

evidence would be most useful to them to improve the 

services they provide, and to identify future research 

topics related to employment programs and services 

and the future of work. These efforts specifically 

targeted applicable areas of research relevant to the 

Workforce Innovation and Opportunity Act (WIOA).1

1

 See: https://www.dol.gov/agencies/oasp/evaluation/currentstudies/WIOA-Research-Portfolio

Figure 1. Type of Organizations Consulted 

about Public Workforce Evidence Needs

Type of Organization No.

Federal Agencies 2

Local Workforce System 10

State Workforce System 15

Business and Industry 10

Workforce Advocacy Groups 9

Organized Labor 4

Education or Community College 3

Total 53
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In addition to this broad-based engagement, the department convened an 11-member panel of highly-qualified 

experts in the workforce development field, including representatives from workforce boards, academics, 

nonprofit organizations that partner with or study the workforce system, and labor unions. The panel provided 

DOL with targeted input on high-priority research topics related to WIOA programs and services that could build 

on the current evidence base, fill key knowledge gaps, and could be potentially suitable for rigorous evaluation. 

A summary of the findings from these engagements is available on the department’s website.2

Frequently raised topics during these engagements included: work-based learning and apprenticeships; career 

pathways, advancement, and stackable credentials; integrated services and co-enrollment; employer services 

and engagement; career planning and navigation; remote work and remote services; COVID-19-related job 

changes; changes in the value of credentials; data infrastructure; and diversity, equity, and inclusion in the 

workforce training system and the world of work. Many key knowledge gaps and research needs for the 

workforce system raised by these stakeholders were considered for and are reflected in the evidence-building 

activities included in this plan.

Ongoing and Future Stakeholder Engagement

On July 8, 2021, DOL published and subsequently disseminated to DOL’s half-million Twitter followers an 

invitation for public comment on the department’s strategic planning activities, including the five priority learning 

areas included in this plan (see Figure 2 next page). The invitation was published in English and Spanish, with 

a deadline of August 6, 2021, for public comment. 

On July 29, 2021, DOL’s Office of Congressional and Intergovernmental Affairs sponsored a Congressional 

outreach session. This session included a high-level briefing by the department on its strategic planning 

approach, including the five priority learning areas within this plan. Further, it allowed Congressional aids from 

both appropriations and authorizations to ask questions and to provide direct comment. 

After February 2022, the department will engage in further targeted stakeholder feedback, to support ongoing 

evidence development and dissemination activity. As the Evidence-Building Plan is an evolving document, the 

department anticipates refining activities based on future stakeholder inputs. DOL is especially interested in 

ensuring perspectives from a diverse array of stakeholders who represent the communities our programs serve.

2

 See: https://www.dol.gov/sites/dolgov/files/OASP/evaluation/pdf/WIOA%20Portfolio%20Stakeholder%20Summary_508_FINAL.pdf
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III. Planned Evidence-Building Activities

by Priority Learning Area

This report describes DOL’s planned evidence-building activities in three sections. This section describes the 

five Priority Learning Areas that the department will explore, as well as specific time-bound projects DOL intends 

to initiate that address each of the Priority Learning Areas. The next section (Section IV) describes overarching 

initiatives DOL plans to carry out during FY 2022-2026 that touch on many different themes and topics relevant 

to DOL’s mission. The last section (Section V), describes future research topics that are of interest to the 

department that may inform DOL’s future evidence-building commitments going forward. 

A cross-cutting theme for all of these learning areas is the need to improve equity in access to, and participation 

in, DOL programs, benefits, and protections, reflecting the department’s commitment to fulfilling the charge set 

out by this administration’s focus on equity for underserved communities. Further, these initial offerings were 

co-developed with the department’s strategic plan and will be updated as DOL continues to advance learning 

across its strategies and activities.

DOL has identified five Priority Learning Areas 

for this plan, as described in Figure 2. In the 

tables below, DOL has identified specific research 

projects it intends to initiate within FY 2022-2026 

pertaining to each Priority Learning Area. By 

project, each table describes the objective, key 

research questions, the estimated fiscal year the 

project will start, its expected duration, expected 

data sources, possible methods and analytical 

approach, and anticipated challenges and 

solutions to those challenges. The plan includes a 

mix of short-term projects (of expected duration of 

one year or less) as well as medium- to long-term 

projects (more than one year). 

The evidence-building activities included in this plan contribute to departmental priorities identified in the 

department’s FY 2022-2026 Strategic Plan. Appendix A provides a mapping of how each proposed activity 

relates to DOL Strategic goals as well as the Priority Learning Areas. 

The project descriptions below are limited to new evidence-building activities DOL plans to initiate over the time 

period covered by this plan. Details on all current and recently completed research studies supported by DOL 

can be found on the CEO website, as well as on several agency-specific websites on DOL.gov.

3

3

 See: www.dol.gov/agencies/oasp/evaluation

Figure 2. DOL Priority Learning Areas for FY 2022-2026

1 Ensuring Equity in Employment and Training Programs

2 Reducing Barriers to Women’s Employment

3 Studying Effects of the COVID-19 Pandemic

4 Improving Enforcement Activities & Protections for All

5 Strengthening Unemployment to Reemployment
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Priority Learning Area 1: 

Ensuring Equity in Employment and Training Programs

Table 1. Planned Evidence-Building Activities Related to Priority Learning Area 1

Project 1* Additional Information

Title: Analysis of Distance Learning Strategies (ETA).

To identify lessons learned for assisting customers with 

different levels of digital skills and differential access to 

high-speed Internet infrastructure to participate in distance 

learning. Could be supplemented with a synthesis under 

CLEAR, TBD.

Est. Start & Duration: Study will begin in FY 2022 

and last five years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

1. Ensuring Equity in Employment & Training Programs

3. Studying Effects of the COVID-19 Pandemic

Priority Research Questions:

1. What are the lessons learned for assisting customers with different levels of

digital skills and differential access to high-speed Internet infrastructure to

participate in distance learning?

2. Can different types of training, including skilled trades instruction, be adapted to

a distance learning format?

Data Sources: Administrative data

Methods/Approach: Descriptive Study and Behavioral/Experimental Pilot Test

Anticipated Challenges & Solutions

None identified.

Project 2* Additional Information

Title: Navigation Evidence Building Portfolio (ETA). ETA 

seeks to better understand the role of case management 

and navigators broadly in the workforce system, and 

specifically with the Trade Adjustment Assistance (TAA) 

Navigator model, an initiative aimed at facilitating access to 

TAA-related services and benefits for eligible workers. For 

the broader workforce system, a study will examine how 

navigators are used, and to serve which populations. It will 

synthesize findings across relevant studies. For the TAA 

Navigator, the evaluation will identify the key components 

of promising navigator models, how they have been 

implemented, under what conditions, and for whom (such 

as underserved communities). As part of the feasibility 

study, methodological design options to estimate impacts of 

this program to understand the effectiveness of this strategy 

will be identified and assessed.

Est. Start & Duration: Study will begin in FY 2022 

and last five years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

1. Ensuring Equity in Employment & Training Programs

Priority Research Questions:

1. How might case managers/navigators be helpful for the workforce system, more

broadly?

2. In what ways can a navigator intervention help address barriers that

disadvantaged populations face?

3. What specific navigator services are most helpful in engendering positive labor

market outcomes?

4. Are they able to help improve long-term outcomes for individuals with barriers to

employment?

5. What is the impact of Trade-Adjustment Assistance Program’s Navigator on

underserved communities?

6. What are the barriers that the dislocated worker population faces in accessing

services?

7. For the feasibility study, what are the evaluation design options for measuring

the differences in the outcomes of those served by TAA navigators compared to

outcomes of TAA program participants without navigator supports?

Data Sources: TBD for the Descriptive Study; Interviews, focus groups, 

administrative data for the Implementation/Impact Evaluation

Methods/Approach: Descriptive study, Implementation/Impact Evaluation. Initial 

phases will include a feasibility study, followed by an impact evaluation.

Anticipated Challenges & Solutions

An assessment must be conducted to determine the feasibility of an impact evaluation.

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.
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* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 4* Additional Information

Title: Disability & Employment Equity Analysis (ODEP).

As a group, persons of color with disabilities have lower 

employment levels and earnings than non-Hispanic whites 

with disabilities, and may not be equitably served by the 

workforces system and other key disability employment 

programs. Yet there is little research on racial differences 

in employment and earnings for people with disabilities; 

on racial inequities in policy and program design and 

implementation; on program participation and outcomes 

for persons of color with disabilities; or on level of program 

access and cultural competence to ensure inclusive 

programs and services. This research project would review 

extant data on racial differences in employment, earnings, 

program participation, and program outcomes for people 

with disabilities, and consult experts and conduct field 

research to identify current knowledge gaps and inequities 

and promising practices.

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

1. Ensuring Equity in Employment & Training Programs

Priority Research Questions:

1. What are racial and ethnic differences in employment, earnings, program

participation, and program outcomes for people with disabilities?

2. What are current research gaps related to how disability employment programs

serve individuals from different racial and ethnic groups, and what are promising

practices to address existing inequities?

Data Sources: Existing publicly available data sources, administrative data

Methods/Approach: This descriptive and exploratory study will rely on analysis of 

administrative data to build foundational knowledge about employment of persons 

of color with disabilities, seeking to fill in knowledge gaps currently not addressed 

by available survey data.

Anticipated Challenges & Solutions

None identified.

Project 3* Additional Information

Title: First Step Act Implementation (ETA). DOL will 

collaborate with the Federal Bureau of Prisons to develop 

an evidence-informed workforce development initiative to 

advance First Step Act (FSA) implementation and reduce 

recidivism risk in the reentering Federal prisoner population. 

This initiative will deliver workforce development services 

to prisoners, continuing with an intensive transition model, 

and ending with a transition to local service providers as 

prisoners are released. The First Step Act evaluation will 

rigorously evaluate this initiative and support its use of 

evidence-informed workforce development models.

Est. Start & Duration: Study will begin in FY 2023 

and last four years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

1. Ensuring Equity in Employment & Training Programs

Priority Research Question:

To what extent are prisoner outcomes (recidivism, labor market outcomes, etc.) 

impacted by the type, intensity, and duration of workforce development service 

provision?

Data Sources: Original data collection, federal administrative data sources

Methods/Approach: Qualitative and quantitative methods to conduct formative 

research, as well as an implementation and impact study.

Anticipated Challenges & Solutions

TBD.
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* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 6* Additional Information

Title: VETS Employment Navigators Evaluation 

(VETS). Implementation evaluation to understand how 

Employment Navigators provide support to transitioning 

service members to find employment faster and/or obtain 

higher wages. It will also include a feasibility study for an 

impact evaluation. The study will examine the elements 

that distinguish a VETS employment navigator (if any) 

from other case management support to veterans, 

including supports from Consolidated Disabled Veteran’s 

Outreach Program (DVOP) Specialists and Local Veteran’s 

Employment Representatives (LVER)s. 

Est. Start & Duration: Study will begin in FY 2022 

and last five years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

1. Ensuring Equity in Employment & Training Programs

Priority Research Questions:

1. What is the impact of VETS employment navigator pilot program for transitioning

service members?

2. What are barriers to TAP and other workforce services, particularly for those who

may face a higher risk of poverty, social exclusion, or discrimination?

Data Sources: Interviews, focus groups, administrative data

Methods/Approach: Implementation/Impact Evaluation

Anticipated Challenges & Solutions

An assessment must be conducted to determine the feasibility of an impact evaluation.

Project 5 Additional Information

Title: Research to Support Employment of People on 

the Autism Spectrum (ODEP). Professional services to 

support a project to build evidence regarding approaches 

to improve gainful employment for young adults with 

developmental disabilities, particularly those on the 

autism spectrum. The Project aligns with federal priorities 

under the Autism CARES Act of 2019 to expand access, 

opportunity, and quality of life for youth and adults on 

the autism spectrum. This work also supports broader 

efforts to enhance federal policy and practices to support 

neurodiversity at work and strengthen access to competitive 

integrated employment for youth and adults with disabilities.

Est. Start & Duration: Study will begin in FY 2021 Q4 

and last three years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

1. Ensuring Equity in Employment & Training Programs

Priority Research Questions:

Project activities will explore major gaps in the autism research literature, including 

but not limited to: 

1.

2. Outcomes of autism-focused hiring and recruitment programs;

3. Utility of accommodations, supports, and assistance programs to enhance work

performance;

4. Participation in inclusive apprenticeships and related WBL activities, including

focused strategies;

5. Use of accessible and assistive technologies for work and on-the-job training;

6.

7. 

Data Sources: Disability Analysis File, Rehabilitation Service Administration Case 

Service Report

Methods/Approach: Descriptive study, Exploratory Study, Data Analytics

Anticipated Challenges & Solutions

None identified.
12 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 8* Additional Information

Title: WANTO Descriptive Study (WB). The Women in 

Apprenticeship and Nontraditional Occupations (WANTO) 

grant program supports community-based organizations to 

recruit, mentor, train and retain more women in Registered 

Apprenticeships and nontraditional occupations. Grantees 

provide technical assistance to address the significant 

under-representation of women in apprenticeship programs 

and in general in high-growth, high-wage Science, 

Technology, Engineering, and Math-related occupations.

Est. Start & Duration: Study will begin in FY 2022 

and last three years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Areas:

1. Ensuring Equity in Employment & Training Programs

2. Reducing Barriers to Women’s Employment

Priority Research Questions:

1. For those Women in WANTO grants providing job related training, what best

practices and challenges have been identified on successfully transitioning

women into apprenticeships or nontraditional occupations by the end of the

grant’s period of performance?

2.

Data Sources: WANTO grant data and WANTO site visits

Methods/Approach: Exploratory/Descriptive Study

Anticipated Challenges & Solutions

The PRA process for a short study may be a challenge.

Project 7* Additional Information

Title: FARE Grants Implementation Study (WB).

Fostering Access, Rights, and Equity (FARE) 

implementation/impact study to accompany FARE grant 

to states and community-based organizations intended 

to assist women in understanding and accessing their 

employment rights and benefits. 

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

1. Ensuring Equity in Employment & Training Programs

2. Reducing Barriers to Women’s Employment

Priority Research Questions:

1. How are FARE grants assisting women in understanding and accessing their

employment rights and benefits?

2. What are barriers that this population faces in accessing services?

Data Sources: FARE grant data

Methods/Approach: Implementation Study

Anticipated Challenges & Solutions

None identified.
13 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Priority Learning Area 2: 

Reducing Barriers to Women’s Employment

Note: Projects 7 and 8 above also support this area.

Table 2. Planned Evidence-Building Activities Related to Priority Learning Area 2

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 9 Additional Information

Title: Understanding the Lifetime Effects of Providing 

Informal Care – 2021 Update (WB). This project will 

update the never-published 2016 WB contracted study - 

Understanding the Lifetime Effects of Providing Informal 

Care to account for more current data and trends, the 

Covid-19 pandemic, and additional analysis by race and 

ethnicity. The updated Study will provide WB a better 

understanding of the effects of child, disabled, and adult 

caregiving on women’s employment, earnings, savings, and 

retirement including projections of lifetime costs, the impact 

of the Covid-19, and the policy implications of these effects. 

The work will culminate in a series of written products 

including an updated Understanding the Lifetime Effects 

of Providing Informal Care Study; an executive summary 

of the updated Study; and public dissemination fact sheets 

highlighting key findings for a non-technical audiences.

Est. Start & Duration: Study will begin in FY 2022 

and last six months.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Areas:

2. Reducing Barriers to Women’s Employment

3. Studying Effects of the COVID-19 Pandemic

Priority Research Questions:

1. What are the lifetime effects of providing informal caregiving on women’s

economic security?

2. What are the costs caregivers (child, disabled, elder care) have incurred

including lost earnings, financial benefits and savings?

3. What are the projected costs that different cohorts of currently working women

will incur over their lifetimes due to caregiving?

4. What have been the effects of the Covid-19 Pandemic?

5. What are the projected future effects of the Pandemic?

6. What are the caregiving incidences and effects by birth cohorts, demographics of

women (e.g. education, parental status-number of children, race and ethnicity),

and type and length of caregiving?

7.

Data Sources: SIPP, HRS, ACS, CPS, NLSY, PSID, DYNASIM

Methods/Approach: Descriptive tabulations, regression analyses, projections 

using DYNASIM microsimulation model

Anticipated Challenges & Solutions

None identified.
14 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 10* Additional Information

Title: Federal Employee Paid Leave Act (FEPLA) 

Evaluation (WB). The Federal Employee Paid Leave 

Act (FEPLA) provides 12 weeks of paid parental leave to 

certain Federal employees in connection with the birth of an 

employee’s child or placement of a child with an employee 

for adoption or foster care. The law went into effect on 

October 1, 2020. Anticipated benefits of the law include 

increased time for bonding between parent and child, 

improved health of the birth mother and child, preservation 

of annual and sick leave balances for future family needs, 

increased retention and engagement of the Federal 

workforce, and a positive impact to the U.S. economy by 

addressing women’s declining labor force participation. The 

Congressional Budget Office estimated that implementing 

FEPLA would cost $3.3 billion from 2021-2024. OPM and 

DOL will collaborate to answer questions surrounding 

the effects of FEPLA. For FY 23, the questions will focus 

on short-term uptake and effects of the law and will be 

dependent on data availability. Future evaluation questions 

may be proposed in the ongoing partnership.

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

2. Reducing Barriers to Women’s Employment

Priority Research Questions:

1. What are FEPLA leave taking patterns, and do those vary by employee

demographics? Are leave taking patterns equitable across demographic groups?

2.

3. What is the effect of FEPLA on short-term retention of employees following paid

parental leave?

4. What is the effect of FEPLA on employees’ career advancement, including

promotions, salary, and performance ratings?

Data Sources: OPM and DOL will leverage existing data including payroll data (use 

of paid and unpaid leaves), employee personnel status data (for example, retention 

status, grade and step level, and pay rate), employee performance data (for example, 

award hours or pay and performance ratings), and employee demographic data (for 

example, gender, race and ethnicity, age, work schedule, and agency).

Methods/Approach: OPM and DOL will analyze secondary administrative 

personnel data that OPM maintains in its Enterprise Human Resources Integration 

(EHRI) and Electronic Official Personnel Folder (eOPF) databases, conducting 

descriptive analyses and comparisons of outcomes prior to and following 

implementation of FEPLA.

Anticipated Challenges & Solutions

1.

2. Selecting the appropriate time period for comparison. For comparisons of before

and after implementation of FEPLA, there are complicating factors regarding time

periods for comparison, including the lack of payroll codes and the COVID-19

pandemic, which is anticipated to have an effect on childbearing and leave taking

patterns. As such, we will carefully consider the appropriate time periods for both

before and after comparison and will interpret findings with caution.

Project 11 Additional Information

Title: Women and Work Report (WB/OASP). This report 

will synthesize research and data on women’s participation 

in the labor force and how it has been affected by the 

COVID-19 crisis and the ongoing recovery. It will include a 

discussion of the barriers women workers face to full and 

equal participation in the labor force and how these barriers 

were magnified during the COVID-19 crisis, especially for 

women of color and other disadvantaged groups. It will also 

discuss policy interventions that promote more equitable 

labor force participation for women, including assessing 

progress that has been made.

Est. Start & Duration: Study will begin in FY 2022 

and last one year.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

2. Reducing Barriers to Women’s Employment

Data Sources: CPS, Census Pulse, ATUS, NCS, and other labor force survey 

data; review of published research on related topics

Methods/Approach: Secondary data analysis; policy analysis

Anticipated Challenges & Solutions

None identified.
15 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Priority Learning Area 3: 

Studying Effects of the COVID-19 Pandemic

Note: Projects 1 and 9 above also support this area.

Table 3. Planned Evidence-Building Activities Related to Priority Learning Area 3

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 12* Additional Information

Title: Improving Planning and Operations to Deliver 

Services Study (ETA). To identify lessons learned from 

state and local practices that have found new and innovate 

ways to improve or more efficiently deliver services. The 

study will look at the current pandemic, as well as lessons 

learned from the Great Recession, to synthesize important 

practical takeaways.

Est. Start & Duration: Study will begin in FY 2022 

and last three years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

3. Studying Effects of the COVID-19 Pandemic

Priority Research Questions:

1. How can the public workforce system react and respond to future economic

disruptions to provide income support and assist workers upskill or reskill and

return to work effectively?

2. What services and strategies are states using to help unemployed workers

return to work as the US economy begins to recover? What strategies appear

promising for different participants (dislocated workers, low-income and out-ofschool youth)? What are state-of-the-art practices to support job search and

reemployment?

Data Sources: TBD

Methods/Approach: Descriptive study/Implementation study

Anticipated Challenges & Solutions

None identified.

Project 13 Additional Information

Title: Effects of COVID-19 on Bureau of International 

Labor Affairs technical assistance projects (ILAB). This 

cross-program evaluation will synthesize data and discern 

lessons learned and good practices pertaining to the effects 

of the COVID-19 pandemic on project implementation and 

outcomes.

Est. Start & Duration: Study will begin in FY 2022 Q1 

and last one year.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

3. Studying Effects of the COVID-19 Pandemic

Priority Research Questions:

1. What are the effects and experiences the COVID-19 pandemic has had on

programming from across different ILAB projects?

2. What good practices and lessons learned are emerging from implementing ILAB

projects during the COVID-19 pandemic?

3. What future opportunities are emerging for ILAB projects to provide relevant

technical assistance in the new landscape brought about by COVID-19?

Data Sources: Existing grantee reporting and administrative data, new qualitative 

data collection

Methods/Approach: Mixed methods study

Anticipated Challenges & Solutions

None identified.
16 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 14 Additional Information

Title: Analysis of Reasonable Accommodation (RA) 

Requests related to Telework post Covid-19 (OASAM).

The OASAM Workplace Equality Compliance Office 

(WECO) processes RA requests for workplace flexibilities. 

With initial reentry plans in place, one of the avenues for 

employees to continue telework is through the Agency’s 

RA process. WECO will analyze RA requests over the 

next 6-8 months to see if any trends can be gleaned from 

those requests such as: which agencies are requests 

coming from, which positions are requesting telework, what 

durations of telework are being requested and more. 

Est. Start & Duration: Study will begin in FY 2022 

and last one year.

Strategic Goal - Management Goal: A Department 

Grounded in Evidence, Innovation, and Employee 

Engagement

Priority Learning Area:

3. Studying Effects of the COVID-19 Pandemic

Priority Research Question:

After more than a year of working remotely, are employees more likely to request 

telework related RAs in order to continue working remotely?

Data Sources: WECO Weekly Case Reports

Methods/Approach: Statistical Analysis

Anticipated Challenges & Solutions

There should be no agency challenges since we’re using data that we gather.
17 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Priority Learning Area 4: 

Improving Enforcement Activities & Protections for All

Table 4. Planned Evidence-Building Activities Related to Priority Learning Area 4

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 15 Additional Information

Title: Audit Quality Study (EBSA). EBSA will sample 

roughly 400 Form 5500 filings submitted in the Fall of 

2021, as a quality assurance assessment of the CPA firms 

performing the audits. Once OCA performs its review, 

EBSA can compare the audit quality by firm characteristics, 

which can then be used to inform outreach and education. 

Moreover, since the American Institute of Certified Public 

Accountants (AICPA) is revising its standards, effective 

next year, a new audit quality study can provide a baseline 

compliance rate under which the new standards can be 

evaluated in the future.

Est. Start & Duration: Study will begin in FY 2022 

and last one-and-a-half years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. Has the overall quality of employee benefit plan audits improved since EBSA’s

prior audit quality study? Similarly, based on the results of a new study, we can

evaluate whether actions taken by the accounting profession have had a positive

impact on improving the work of plan auditors (e.g. enhanced peer review

process, better technical guidance, stronger disciplinary actions).

2. What additional actions/activities can EBSA take to improve audit quality?

Data Sources: Form 5500 Reports

Methods/Approach: Statistical analysis of the quality of audits based on firm and/

or plan characteristics.

Anticipated Challenges & Solutions

Concerns regarding sampling to ensure we include both calendar and fiscal year 

plans. EBSA plans on working with contractors to develop a robust sampling 

approach.

Project 16* Additional Information

Title: EBSA Enforcement Health Metrics (EBSA). EBSA 

seeks to develop health metrics in order to measure its 

impact and effectiveness in the health space. EBSA would 

like to identify how other health regulators measure their 

effectiveness, identify actions that need to be tied to an 

outcome measure, and develop ways investigators’ work 

in this area can be measured for performance reporting 

purposes.

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. How can EBSA measure its influence on health outcomes?

2. Does EBSA enforcement positively influence individual health outcomes?

Data Sources: Measures of success used by other federal and/or state regulators 

in the health space

Methods/Approach: Exploratory Study/Descriptive Study

Anticipated Challenges & Solutions

Many of the interventions and recoveries EBSA is able to achieve in the health 

space are difficult to measure. Moreover, investigations may result in prospective 

changes only to plan documents or procedures for specific conditions, which adds 

additional challenges to measuring the ultimate effect on the population benefitting 

from the change.
18 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 17* Additional Information

Title: Identifying Non-Filing MEWAs (EBSA). In order to 

pre-emptively identify non-filing Multiple Employer Welfare 

Associations (MEWAs), many of which have a history of 

fraud and abuse and MEWA violations, EBSA would like to 

undertake a pilot program to use data scraping methods 

and Robotic Process Automation (RPA) to identify MEWAs 

that have not filed Form M-1s. By identifying these plans 

while they are marketed to employers, EBSA can intervene 

early to make sure the plans are compliant and mitigate 

solvency risk.

Est. Start & Duration: Study will begin in FY 2022 

and last one year.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Question:

What are tools for EBSA to enhance detection of non-filing MEWAs, who are a high 

risk for fraud and abuse?

Data Sources: TBD

Methods/Approach: Artificial Intelligence/Robotic Process Automation and Data 

Analytics

Anticipated Challenges & Solutions

EBSA does not have any experience with data scraping. EBSA will need to identify 

terms that would be associated with marketing at risk products and developing the 

methodology to find these MEWAs. EBSA recommends a small pilot project which 

could then be expanded should it be successful.

Project 18 Additional Information

Title: Evidence to Action (Forced Labor Study - 

Argentina and Madagascar) (ILAB). This project will 

develop robust and replicable approaches to collecting and 

analyzing data on forced labor to inform evidence-based 

interventions. The project will provide new information on 

the prevalence and causes of forced labor in the garment 

sectors of Argentina and Madagascar; build capacity of 

national stakeholders to undertake and use such research; 

and catalyze actions to combat forced labor.

Est. Start & Duration: Study will begin in FY 2022 Q1 

and last one-and-a-half years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities &

Protections for All

Priority Research Questions:

1. What is the prevalence rate of forced labor in garment sectors in Madagascar

and Argentina?

2.

Data Sources: Primary data collection

Methods/Approach: Household survey with probability sample; Respondentdriven sampling approach.

Anticipated Challenges & Solutions

The COVID-19 pandemic continues to pose risk to the timely completion of data 

collection activities, and the quality of the data. DOL will closely monitor the 

situations through regular check-ins with the grantee, and coordinate actions to 

mitigate the potential issues as they arise.
19 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 19 Additional Information

Title: National Child Labor Survey of Mexico (ILAB).

ILAB plans to fund a National Child Labor Survey in Mexico 

under the proposed “Building a comprehensive government 

approach to combating child labor and forced labor in 

Mexico” project, which ILAB plans to award in the coming 

months.

Est. Start & Duration: Study will begin in FY 2023 Q1 

and last one-and-a-half years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. What is the prevalence of child labor in Mexico?

2. How has this prevalence changed since 2019?

Data Sources: Primary data collection

Methods/Approach: Household survey with probability sample

Anticipated Challenges & Solutions

The COVID-19 pandemic poses risk to the timely completion of data collection 

activities, and the quality of the data. DOL will closely monitor the situation through 

regular check-ins with the grantee, and coordinate actions to mitigate the potential 

issues as they arise.

Project 20 Additional Information

Title: Understanding the demographics of regulated 

mining community and potential workforce (MSHA).

To inform MSHA’s equity analysis, outreach, and hiring 

strategies, MSHA is interested in continuing to understand 

the demographics of miners served (which changes over 

time) and potential workforce for the agency.

Est. Start & Duration: Study will begin in FY 2022 

and last one to two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Question:

What are the demographics of the regulated mining community and potential 

workforce for MSHA and to what extent is there alignment with representation 

within MSHA?

Data Sources: American Community Survey, internal recruitment and hiring data

Methods/Approach: Data Analytics

Anticipated Challenges & Solutions

None identified.
20 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Project 21* Additional Information

Title: Black lung incidence nationwide as a result of 

burning coal for heating, and how those areas intersect 

with mining and former mining communities (MSHA).

The Navajo Nation has the highest incidence of nonmining black lung as a result of burning coal in homes for 

heat. This is an issue in certain areas of Appalachia as 

well. Understanding where those black lung cases occur 

and how they intersect with current and former mining 

communities could help inform MSHA of areas where 

undiagnosed miners may be at high risk and allow MSHA 

to target assistance.

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. Where are cases of black lung occurring across the US as a result of non-mining

activities such as burning coal for heat?

2. How do those align with former and current coal mining communities?

Data Sources: Black lung clinics, public health data

Methods/Approach: Exploratory study

Anticipated Challenges & Solutions

None identified.

Project 22 Additional Information

Title: Paid Family and Medical Leave for People with 

Disabilities (ODEP). Access to Paid Family and Medical 

Leave (PFML) is especially important for people with 

disabilities and their families who generally have lower 

income and fewer savings to rely on when taking leave. 

Like workers in general, workers with disabilities exhibit 

need for a variety of paid leave types and for people with 

disabilities who are not in the labor force, PFML provides 

income protection and support to their family members 

who may need to take time off work to care for them. This 

research project would analyze the access and use of paid 

family and medical leave by people with disabilities within 

several national datasets.

Est. Start & Duration: Study will begin in FY 2021 Q4 

and last two years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. What are the reasons for and lengths of time that people with disabilities use

paid leave, and how can a national comprehensive paid family and medical leave

program be designed to meet the unique needs of workers with disabilities or

ongoing health conditions?

2. How can program design factors (such as coverage types, leave duration, wage

replacement, job protection, benefits eligibility, and interaction with state leave

programs) be evaluated to understand the specific implications on workers with

disabilities?

Data Sources: American Time Use Survey, FMLA Employee Survey, Medical 

Expenditure Panel Survey

Methods/Approach: Data analytics

Anticipated Challenges & Solutions

ODEP anticipates that in many nationally representative surveys that ask questions 

related to access and use of paid leave, disability status is not directly included or 

the sample of workers with disabilities will be relatively small. (Solution: in the shortterm ODEP can use ongoing health conditions reported as a proxy for disability 

status and in the long term work with CEO to add disability status to the FMLA

employee survey).

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.
21 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 23 Additional Information

Title: Algorithmic Fairness (OFCCP). Technology is 

transforming how employers hire and make employment 

decisions. Employers are increasingly relying upon 

“machine learning,” and algorithms to recruit, hire, and 

assess workers. OFCCP is well positioned to ensure 

safeguards in the use of hiring and other employment 

technology. Given substantial asymmetries in workers’ 

ability to access information concerning how employment 

decisions are made, workers are often not in a position to 

file a complaint about these systems. OFCCP has a critical 

role to play in proactively and comprehensively assessing 

federal contractors’ technology-driven employment systems 

as part of OFCCP compliance evaluations to ensure 

these systems are designed to promote equity rather than 

perpetuate bias in existing employment systems.

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Question:

What standards should OFCCP consider for contractors to promote equity in 

algorithmic selection and decision-making systems and ensure meaningful 

oversight and accountability.

Data Sources: External Research

Methods/Approach: Meta-analysis or validation studies

Anticipated Challenges & Solutions

Lack of transparency on the operation of and equity impacts of assessment 

technology.

Project 24* Additional Information

Title: Construction Representation Benchmarks: 

Measuring the Potential Workforce Availability in 

Trades (OFCCP). OFCCP is currently exploring whether 

to update its construction regulations and is interested in 

better understanding the potential available workforce by 

race, gender and ethnicity as well as geographic area for 

different trades.

Est. Start & Duration: Study will begin in FY 2022 

and last one year.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Question:

What data sources and methodologies should OFCCP rely on to identify the full 

potential workforce available by race, gender and ethnicity in the construction 

industry?

Data Sources: TBD.

Methods/Approach: Data Analytics

Anticipated Challenges & Solutions

Lack of current data reflecting the full scope of workers available to work in 

construction trades absent barriers to opportunity.
22 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 25* Additional Information

Title: Using Data to Inform Scheduling and Enforcement 

(OFCCP). OFCCP seeks to continually improve its 

scheduling process to better identify risk factors for noncompliance.

Est. Start & Duration: Study will begin in FY 2022 

and last one year.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Question:

What additional data sources can OFCCP utilize to improve its neutral scheduling 

process to select contractors that have greater risk factors for non-compliance?

Data Sources: Vets 4212, EEO-1, Census, Wage and Hour and OSHA data, etc.

Methods/Approach: Data Analytics

Anticipated Challenges & Solutions

Method should meet neutrality standard.

Project 26* Additional Information

Title: Assessment of OLMS Financial Reporting Data 

(OLMS). The Office of Labor-Management Standards 

(OLMS) is interested in understanding how LM data can 

be used to characterize labor union density, mobilization, 

and penetration to better study the effect of unions on 

workplace conditions, local economies, and communities. 

This information could advance our understanding of the 

role that unions play in U.S. labor markets. 

Est. Start & Duration: Study will begin in FY 2022 

and last one year.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. What are opportunities for characterizing union density, mobilization, and

penetration from LM data?

2. Are there ways to increase the utility of the data?

3. What are additional data sources (OLMS, other DOL, or external) that could

be used as supplemental data or merged with the data to advance our

understanding of the effect of unions on workplaces and local economies and

communities?

Data Sources: Review of LM form data and other OLMS administrative datasets, 

external quantitative datasets, limited qualitative data collection

Methods/Approach: Exploratory Study/Data Analysis

Anticipated Challenges & Solutions

None identified.
23 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 27 Additional Information

Title: Impact of Algorithmic Management on 

occupational injuries and illnesses in the Warehousing 

and Storage Industry (NAICS 4931) (OSHA). Algorithmic 

management is a diverse set of technological tools and 

techniques to remotely manage workforces, relying on data 

collection and surveillance of workers to enable automated 

or semi-automated decision-making. In Warehousing, 

workers may be managed by algorithms that determine 

which items need to be picked, moved, stored, and 

shipped. Employees say they feel pressured to improve 

their “pick rate,” a metric that calculates how many items 

are retrieved from the shelves every hour.

Est. Start & Duration: Study will begin in FY 2024 

and last two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Question:

What is the impact of algorithmic management on occupational injuries and illness 

in the Storage and Warehouse Industry? 

Data Sources: OSHA Injury and Illness Logs (OSHA Forms 300 and 301); Data 

from the BLS Survey of Occupational Injuries and Illness (SOII); OSHA inspection 

data from inspections in the Warehousing and Storage Industry (NAICS 4931)

Methods/Approach: 

1. Describe the nature, severity, and extent of occupational injuries and illness

observed in establishments in the Warehousing Industry where algorithmic

management is practiced.

2. Compare the nature, severity, and extent of occupational injuries and illnesses in

establishments in the Warehousing Industry where algorithmic management is

practiced to the nature, severity, and extent of occupational injuries and illnesses

in establishments in the Warehousing Industry where algorithmic management is

not practiced.

Anticipated Challenges & Solutions

TBD.

Project 28* Additional Information

Title: Reaching Vulnerable Populations through 

Alliances (OSHA). Through the Alliance Program, OSHA 

works with organizations such as trade and professional 

associations, labor unions, educational institutions, 

community and faith-based groups, and government 

agencies to share information about OSHA’s initiative 

and compliance assistance resources with workers and 

employers, and educate workers and employers about their 

rights and responsibilities. Alliance Program participants 

are committed to working closely with OSHA to develop 

and share information with workers and employers to help 

prevent injuries, illnesses, and fatalities in the workplace 

and to educate workers and employers about their rights 

and responsibilities under the Occupational Safety and 

Health Act. Participants in the Alliance Program support 

OSHA’s strategic goals by developing Alliance agreements 

and implementing project plans that emphasize Raising 

Awareness of OSHA’s Rulemaking and Enforcement 

Initiatives; Outreach and Communication; and Training and 

Education.

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. Is the information OSHA provides to Alliance Participants getting to the most

vulnerable workers?

2. How is that information getting to the most vulnerable workers?

3. 

Data Sources: OSHA’s Compliance Assistance data base has information on 

activities related to OSHA Alliances. Limited information is available on some of the 

characteristics of program participants (e.g., temporary workers, youth, ethnicity, 

etc.) The groups with which OSHA has alliances may be able to provide information 

on members and participants in their programs.

Methods/Approach: 

1. Survey participants in Alliance events to gather information on what they learned

from participation in alliance-sponsored events and trainings. Participants getting

to the most vulnerable workers?

2. Develop and implement a tool to measure the usefulness of the information

participants received.

Anticipated Challenges & Solutions

The biggest challenge will be identifying the workers or participate in alliancesponsored events and trainings. Many of these workers may not speak English 

well enough to complete a written survey. Focus groups may be required. OSHA’s 

alliance partners should be able to assist with the data collection.
24 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 29* Additional Information

Title: Reaching Vulnerable Populations through 

training funded by OSHA’s Susan Harwood Training 

Grants (OSHA). Susan Harwood Training Grants are 

awarded competitively to provide training and education 

programs for employers and workers on the recognition, 

avoidance, and prevention of safety and health hazards in 

their workplaces and to inform workers of their rights and 

employers of their responsibilities under the Occupational 

Safety and Health (OSH) Act. The types of grants solicited 

each year vary and in the past have included Capacity 

Building grants, Targeted Topic, and Training Materials 

Development. Given the variety of grants, DOL would like to 

explore the feasibility of assessing this kind of program, and 

plans to conduct a descriptive study that can help inform 

future evaluations of the grant program. 

Est. Start & Duration: Study will begin in FY 2023 

and last two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. Is the training developed under the Susan Harwood Grant Program reaching

vulnerable populations of workers?

2. What are the practices used by those who receive Grant awards for reaching

vulnerable populations?

3. What are research options that OSHA can use to understand the implementation

and impacts of this grant program in the future?

Data Sources: Data on who participated in trainings developed using the Susan 

Harwood Grants should be available from the Education Centers and other 

institutions that provide the training.

Methods/Approach: Solicit data on age, race, ethnicity, sex and language spoken 

from participants in trainings developed using the Susan Harwood Grants by survey 

or class registration.

Anticipated Challenges & Solutions

OSHA may have to modify the terms of the Susan Harwood Grants to require 

collection of the desired data.

Project 30 Additional Information

Title: Workplace Violence in the Healthcare Industry 

(OSHA). A workgroup developed criteria statements to 

operationalize program elements for workplace violence 

prevention programs together with a scoring system. Those

statements distinguish high from low performing healthcare 

facilities, evidenced by substantial differences in scores 

between facilities that received 5(a)(1) citations and those 

that received only a hazard alert letter. The goal is to 

expand the use of this checklist/criteria statement-based 

approach to support both self-assessment and program 

improvements.

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections, and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Question:

Does the use of specific criteria statements make self-assessment by facilities and 

inspections by OSHA compliance officers more effective?

Data Sources: OSHA inspections in healthcare on violence or randomly selected 

healthcare facilities.

Methods/Approach: 

1. Provision of criteria statements to compliance officers before and after the

conduct healthcare violence inspections OR

2. Data collection through interviews of self-assessments by facilities;

3. Either way is coring based on pilot project scoring,

4. Examination of scores by whether CSHOs conducted their inspection with

or without the checklist and outcome evaluation comparing to final OSHA

enforcement action.

Anticipated Challenges & Solutions

Access to CSHOs in a timely fashion after they complete their inspection. In 

addition, as the checklist is used, it may become more widely disseminated and 

grow into use.
25 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 31 Additional Information

Title: DOL/OWCP Report on State-Level Workers’ 

Compensation Systems to Identify Additional Areas 

of Coverage Needed (OWCP). Producing a report to 

gather new factual data to consider additional programs 

or legislative initiatives on behalf of the administration. 

The initiatives will be the result of OWCP’s identification of 

areas of coverage that could be filled through the creation 

of a federal public option for certain categories of claims 

and claimants.

Est. Start & Duration: Study will begin in FY 2022 

and last one to three years.

Strategic Goal: 

3. Improve Administration of and Strengthen Worker

Safety Net Programs

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. What data can we cull from existing sources to produce a new data base?

2. What new data sources and tools can we develop for further analysis in state

workers’ compensation systems?

3. Once we have actionable data, what tools and methods can and should we

employ to best analyze and utilize that data?

4.

Data Sources: State workers’ compensation systems

Methods/Approach: Producing a data base used for further analysis

Anticipated Challenges & Solutions

Adequate legal authority for the funding of this project.

Project 32* Additional Information

Title: FMLA Survey (WHD). This is a national survey 

to gain knowledge of how employees and employers 

understand and experience the Family and Medical Leave 

Act (FMLA). The survey would build on prior waves in 1995, 

2000, 2012, and 2018.

Est. Start & Duration: Study will begin in FY 2022/2023 

and last three to four years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1.

2. What are the employer experiences and knowledge levels with administering

FMLA leave?

Data Sources: Prior FMLA surveys, survey samples

Methods/Approach: Questionnaire fielded to nationally representative samples of

employers and employees

Anticipated Challenges & Solutions

Achieving targeted survey response rates: WHD would support a CEO-led 

convening of academics and researchers to discuss the challenges and solutions 

for addressing response rates.
26 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 33 Additional Information

Title: Understanding the prevalence and costs of 

misclassification and potential remedies (WHD). This 

research will explore opportunity track the frequency of 

misclassification and costs to workers and government 

and effectiveness of different strategies (e.g. regulation, 

litigation, enforcement).

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections, and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Question:

What are opportunities for measuring the prevalence and cost of worker 

misclassification?

Data Sources: Potentially by drawing on DOL/other agency enforcement data, tax 

data, and state audits.

Methods/Approach: Exploratory and Data Analytics.

Anticipated Challenges & Solutions

TBD.

Project 34* Additional Information

Title: Worker Survey (WHD). This is a worker survey 

designed to establish prevalence and severity of violations 

among selected worker populations, occupations, and/

or industry subsectors. This survey will allow WHD to drill 

down to specific business models, business networks, and 

even enterprises by asking questions not listed in existing 

surveys, such as CPS.

Est. Start & Duration: Study will begin in FY 2022 

and last three to four years.

Strategic Goal: 

2. Ensure Safe Jobs, Essential Protections,

and Fair Workplaces

Priority Learning Area:

4. Improving Enforcement Activities & Protections for All

Priority Research Questions:

1. What is the prevalence and severity of workplace violations among selected

worker populations, occupations, and/or industry subsectors? How do these

conditions vary by demographics and geographic factors? How can this data

inform WHD’s strategic planning process, specifically to predict violation

prevalence?

2. To what extent are workers knowledgeable of wage and hour protections?

3. What is the worker experience with or awareness of wage and hour violations?

Data Sources: CPS, QCEW, AWCS (American Working Conditions Survey), LED 

Extraction Tool - Quarterly Workforce Indicators (QWI), Social media advertisement 

for survey completion for design, survey samples for data collection.

Methods/Approach: Project would require sampling techniques and robust 

statistical analysis. Sampling methods may include stratified samples designed to 

collect information on specific worker populations and/or industry subsectors and 

innovative sampling techniques designed to reach worker populations not typically 

reached through federal surveys, yet that is representative.

Anticipated Challenges & Solutions

1. Resources to support survey design methodology, data collection, and analysis:

WHD proposes using an outside vendor through CEO to design and implement

the survey. In addition, WHD’s Office of Enterprise Data and Analytics could

partner with the vendor to review data and extract potential areas for focus in

strategic planning.

2. Achieving targeted survey response rates: WHD would support a CEO-led

convening of academics and researchers to discuss the challenges and solutions

for addressing response rates. WHD’s communications team could partner

with an outside vendor to promote awareness of the survey and encourage

participation.
27 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Priority Learning Area 5: 

Strengthening Unemployment to Reemployment

Table 5. Planned Evidence-Building Activities Related to Priority Learning Area 5

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 35* Additional Information

Title: RESEA Evidence-Building Portfolio (ETA). ETA 

seeks to understand additional implementation, descriptive, 

and impact analyses to better understand effective 

Reemployment Services Eligibility and Assessment 

(RESEA) models that work, under what conditions, and for 

whom.

Est. Start & Duration: Study will begin in FY 2022 

and last five years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

5. Strengthening Unemployment to Reemployment

Priority Research Questions:

1.

2. What are promising strategies to identify UI claimants who are in need of

reemployment services to transition to new employment to participate in

reemployment services, such as RESEA or other job search assistance? How

might such strategies take into account those most likely to exhaust benefits?

How should such models developed by states be adapted and updated to reflect

changes in the labor market?

Data Sources: Interviews, focus groups, administrative data, longitudinal data

Methods/Approach: Data analytics; Implementation Study/Impact Study

Anticipated Challenges & Solutions

None identified.
28 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 36* Additional Information

Title: UI Navigation Descriptive Study (ETA). ETA seeks 

to build evidence on promising strategies of Unemployment 

Insurance (UI) navigator approaches to improve the 

connection and access to unemployment insurance 

benefits and related services for eligible workers, especially 

low-paid or historically underserved workers. Through an 

ETA discretionary grant program to states, the department 

anticipates funding between four and six UI Navigator 

Programs, for a total of approximately $15 million across 

the 36-month initiatives.

Est. Start & Duration: Study will begin in FY 2022 

and last five years.

Strategic Goal: 

3. Improve Administration of and Strengthen Worker

Safety Net Programs

Priority Learning Area:

5. Strengthening Unemployment to Reemployment

Priority Research Questions:

1. What is the potential role of UI navigators in assisting with initial and continued

claim filing and referral to additional services?

2. How do UI navigators affect potential inequities in recipiency and claims

process?

3. Across states, how do navigators differ from case managers, and what are the

elements (if any) that would distinguish these supports?

4.

Data Sources: Interviews, administrative data

Methods/Approach: Exploratory Study/Descriptive Study/Impact Evaluability 

Assessment

Anticipated Challenges & Solutions

For a potential impact analysis, it can be challenging to identify cohorts for a 

comparison group and to ensure necessary data to support a complete analysis. To 

mitigate this risk, the study will undertake a feasibility assessment.

Project 37 Additional Information

Title: UI Research Center (ETA). ETA seeks to support 

a research-to-action model partnership between the 

research grantee and their state UI agency(ies) through a 

competitive grant to an academic institution or consortium. 

A longer-term goal isto support the pipeline of researchers 

to work on UI policy and program administration-related 

projects to inform policy. 

Est. Start & Duration: Study will begin in FY 2022 

and last five years.

Strategic Goal: 

3. Improve Administration of and Strengthen Worker Safety

Net Programs

Priority Learning Area:

5. Strengthening Unemployment to Reemployment

Priority Research Questions:

1. What are the barriers different populations of workers face in accessing UI

benefits and what are potential interventions that community groups, employers,

states, and the federal government could deploy to reduce those barriers?

2.

3. How can we measure the long-term impact of UI benefits on workers, their

families, communities, and the economy?

Data Sources: TBD

Methods/Approach: Academic Grant

Anticipated Challenges & Solutions

None identified.
29 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Additional Planned Learning Activities

Table 6. Additional Planned Evidence-Building Activities

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 39 Additional Information

Title: Diversity and Inclusion Barrier Analysis 

(OASAM). Identify barriers in recruitment and retention 

in underrepresented groups in the DOL workforce (for 

example: persons-with-disabilities (PWD)).

Est. Start & Duration: Study will begin in FY 2022 

and last four years or more.

Strategic Goal - Management Goal: 

A Department Grounded in Evidence, Innovation, and 

Employee Engagement

Priority Research Question:

What are the barriers in recruitment and retention in underrepresented groups in 

the DOL workforce?

Data Sources: HRConnect; DOORs; Exit Survey

Methods/Approach: Focus Groups; Survey(s); Questionnaire(s)

Anticipated Challenges & Solutions

Given that the some of the necessary data elements in the HR systems are 

submitted voluntarily, it’s unclear if there are substantial gaps in completeness/

accuracy of the data. Data cleaning and prospective policy updates/guidance may 

be needed to improve data quality.

Project 38* Additional Information

Title: Improving Diversity, Equity, Inclusivity, and 

Accessibility (DEIA) within the Federal Workforce 

(Federal-wide Initiative with OPM). DOL will lead a 

rigorous interagency evaluation of strategies aimed at 

improving Diversity, Equity, Inclusivity, and Accessibility 

(DEIA) within the Federal workforce. A coordinated crossagency evaluation presents an opportunity to drive longterm, meaningful changes for the Federal workforce. 

DOL will lead this evaluation in close collaboration with 

the Office of Personnel Management and other agencies.

Est. Start & Duration: Study will begin in FY 2023 

and last three years.

Strategic Goal: 

1. Build Opportunity and Equity for All

Priority Learning Area:

6. Other Learning Priorities

Priority Research Question:

1. What strategies are federal agencies using to improve diversity, equity,

inclusivity, and accessibility within the federal workforce?

2. To what extent are these strategies meeting their stated objectives?

Data Sources: Federal administrative records; potentially original data collection

Methods/Approach: Qualitative and quantitative methods

Anticipated Challenges & Solutions

TBD.
30 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 40 Additional Information

Title: Enterprise RPA capability (OASAM). Supporting 

automation capabilities at the enterprise level to allow for 

the rapid development and deployment of bots to automate 

manual tasks.

Est. Start & Duration: Study will begin in FY 2021 Q4 

and last two years.

Strategic Goal - Management Goal: 

A Department Grounded in Evidence, Innovation, and 

Employee Engagement

Priority Research Questions:

1. What is the optimal process for rapidly evaluating fitness of processes for

automation?

2. How can we optimize computing to power multiple bots in production?

Data Sources: DOL data sources across agencies, other government data 

providers, third party data providers

Methods/Approach: OCIO will use the Agile Software Development Lifecycle, 

emphasizing iterative development, continuous improvement, and Human Centered 

Design. Both Agile and Human Centered Design are methods to continuously 

respond to customer feedback and optimize for project performance criteria.

Anticipated Challenges & Solutions

1. Enterprise Adoption: to facilitate enterprise adoption, the initiative will emphasize

use of Human Centered Design, and will implement change management

through OCIO and the DOL Data Board.

2. Data Access and Data Quality: to ensure data access and data quality

supporting the project, OCIO will undertake early and robust data profiling; clear

communications with stakeholders; and coordination with the DOL Data Board

on data governance and related improvements for data sources not immediately

meeting data access or quality standards for the initiative.

Project 41 Additional Information

Title: Executive (CXO) Dashboard Project (OASAM).

Create dashboards for agency and DOL management 

to enhance and standardize display of DEBS data, with 

analytics and visualization of key budget and performance 

results.

Est. Start & Duration: Study will begin in FY 2021 Q4 

and last one year.

Strategic Goal - Management Goal: 

A Department Grounded in Evidence, Innovation, and 

Employee Engagement

Priority Research Questions:

1. What is the optimal process for using predictive analytics for agency budget

execution to help focus our resources?

2. What is the optimal process for managing the data lifecycle supporting this data

product?

Data Sources: Departmental e-Business Suite (DEBS) and other data assets from 

DOL component agencies supporting Goals M.1 through M.3 of the DOL Strategic 

Plan

Methods/Approach: OCIO will use the Agile Software Development Lifecycle, 

emphasizing iterative development, continuous improvement, and Human Centered 

Design. Use cases within the project will include a range of business intelligence 

and analytic requirements and methods, including but not limited to: program 

dashboards, and data products resulting from the data science lifecycle which will 

use both traditional and advanced analytics.

Anticipated Challenges & Solutions

1. Enterprise Adoption: to facilitate enterprise adoption, the initiative will emphasize

use of Human Centered Design, and will implement change management

through OCIO and the DOL Data Board.

2. Data Access and Data Quality: to ensure data access and data quality

supporting the project, OCIO will undertake early and robust data profiling; clear

communications with stakeholders; and coordination with the DOL Data Board

on data governance and related improvements for data sources not immediately

meeting data access or quality standards for the initiative.
31 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.

Project 42 Additional Information

Title: Innovation Incubator (OASAM). Creating a 

controlled and secure environment to allow for the 

incremental exploration, development and investment in 

new technologies.

Est. Start & Duration: Study will begin in FY 2022 

and last two years.

Strategic Goal - Management Goal: 

A Department Grounded in Evidence, Innovation, and 

Employee Engagement

Priority Research Questions:

1. How can we best establish a controlled process for delivering valuable

technology solutions while balancing cost/investment?

2. What are the key metrics that will determine success? What information is

required to make go/no-go decisions on new technology?

Data Sources: DOL data sources across agencies, other government data 

providers, third party data providers

Methods/Approach: OCIO will use the Agile Software Development Lifecycle, 

emphasizing iterative development, continuous improvement, and Human Centered 

Design. Both Agile and Human Centered Design are methods to continuously 

respond to customer feedback and optimize for project performance criteria.

Anticipated Challenges & Solutions

1. Enterprise Adoption: to facilitate enterprise adoption, the initiative will emphasize

use of Human Centered Design, and will implement change management

through OCIO and the DOL Data Board.

2. Data Access and Data Quality: to ensure data access and data quality

supporting the project, OCIO will undertake early and robust data profiling; clear

communications with stakeholders; and coordination with the DOL Data Board

on data governance and related improvements for data sources not immediately

meeting data access or quality standards for the initiative.
32 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Project 44 Additional Information

Title: Feasibility of Linking Financial Data With 

Performance (OCFO). OCFO is interested in learning more 

about how other CFO Act agencies use of financial data 

and non-financial data interact to optimize operations.

Est. Start & Duration: TBD; will last 

one to two years.

Strategic Goal - Management Goal: 

A Department Grounded in Evidence, Innovation, and 

Employee Engagement

Priority Research Questions:

1. How do other CFO Act agencies manage and monitor their financial processes?

2.

Data Sources: Qualitative interviews; Financial administrative data

Methods/Approach: Foundational fact finding; feasibility assessment

Anticipated Challenges & Solutions

Timeline is unclear as financial systems are being updated, but OCFO will remain 

in close communication on changes to assess when to explore data.

Project 43 Additional Information

Title: Strengthening DOL’s SES Cadre (OASAM). Assess 

the development needs of all SES members to inform 

readiness decisions about hiring, career development, and 

executive reassignments and rotations.

Est. Start & Duration: Study will begin in FY 2022 

and last one to two years.

Strategic Goal - Management Goal: 

A Department Grounded in Evidence, Innovation, and 

Employee Engagement

Priority Research Questions:

1. Which ECQs do SES candidates struggle to demonstrate sufficient experience

(ECQs most commonly disapproved by the QRB or returned for re-write)?

Which ECQs are DOL SES rated the lowest/highest? 

3. 

4. 

2. 

What are the Technical Qualifications that separate DOL Agencies?

5. What level of experience is needed to be successful in top DOL SES positions

(DAS positions)?

Data Sources: QRB Results; Performance Results (Managerial-based ECQs); 

SES Focus Group (ERB+PRB)

Methods/Approach: Data analysis of Qualifications Review Board (QRB) results 

and feedback as well as Performance Review Board (PRB) results feedback. 

Participation in OPM’s SES Assessment Center; Piloting a Talent Management 

Program; Focusing specific SES Vacancies (DAS Positions, Occupational Series)

Anticipated Challenges & Solutions

Reduce Focus on Technical Qualifications; Inflated Performance Ratings; 

Differences in DOL Agency Missions; DOL culture & traditions.

* Denotes a CEO-sponsored project that will be included in the DOL FY 2022-2023 Evaluation Plan.
33 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

IV. Cross-Cutting Evidence Building Activities 

DOL Scholars Program 

The department will engage the academic community in efforts to build evidence on labor issues of 

importance to the department through DOL’s Research Scholars and Grants program.4 Launched in 2012 by 

the Chief Evaluation Office, this program builds the capacity of university-based researchers, and particularly 

emerging scholars, to rigorously examine labor-related issues while improving awareness and understanding of 

these issues among program administrators, policy makers, and the public. CEO will work with DOL leadership 

and DOL agencies to select priority research topics for future rounds of DOL Scholars grants. DOL has 

identified an initial list of topics that may be of interest to explore via DOL Scholars grants or the Data Challenge 

for Emerging Scholars & Academics program described below. Potential priority research topics for these 

grants can be found in the final section of this report (Section V).

Data Challenge for Emerging Scholars & Academics

In March 2021, CEO launched DOL’s first Summer Data Equity Challenge5 competition, resulting in five 

awards. This program differs from DOL Scholars in its eligibility requirements, outputs, and timeline. The Summer 

Data Challenge requires research teams to include at least one emerging researcher as author or co-author 

(defined as a current Ph.D. candidate or researcher who completed their Ph.D. no more than five years prior). 

Research teams may also include established academics (researchers who received their Ph.D. more than five 

years prior) as long as the research is co-authored with an emerging researcher. DOL intends to conduct the 

Summer Data Equity Challenge as an annual grant competition. 

The purpose of the Summer Data Challenge is to support rigorous research using public data, including DOL 

data, or other administrative data to examine how well DOL policies, protections, and programs serve traditionally 

underserved communities due to race, gender identity, sexual orientation, ethnicity, income, geography, immigrant 

status, veteran and disability status, or other factors proposed by the applicant. Conducted on a faster timeline 

than the Scholars program, the Summer Data Challenge is intended to provide faster-turnaround insights and 

data that can inform specific DOL programs. 

4

 See: https://www.dol.gov/agencies/oasp/evaluation/topic-areas/research-scholars-grants

5

 See: https://www.dol.gov/agencies/oasp/evaluation/currentstudies/Department-of-Labor-Summer-Data-Challenge

6 https://www.hud.gov/program_offices/spm/gmomgmt/grantsinfo/fundingopps/fy21_hbcu
34 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Increasing Diversity Among DOL-Funded Research Partners

DOL is currently identifying ways it can support researchers and organizations representing 

traditionally underrepresented groups in accessing and applying for research opportunities sponsored 

by DOL. To this end, CEO is currently developing a partnership with the Department of Housing and Urban 

Development (HUD) to conduct research projects through its Historically Black Colleges and Universities 

(HBCU) Research Centers of Excellence initiative.6 Given the close association between housing, community 

development, and labor-related issues, DOL will seek to partner with HUD to conduct innovative research on 

topics relevant to housing and labor through these centers. The research projects will focus on priority topics of 

interest to the department related to underserved communities and historically marginalized populations.
35 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

Clearinghouse for Labor Evaluation and Research (CLEAR)

CLEAR (clear.dol.gov) helps make research on labor topics more accessible to practitioners, 

policymakers, researchers, and the public to inform labor-related decision-making.

During FY 2022-2026, CLEAR will continue to produce different types of systematic evidence reviews to 

identify, evaluate, and summarize findings from all relevant individual studies in a particular evidence base in an 

accessible manner. These reviews primarily examine causal evidence, which sheds light on what interventions or 

strategies are most effective, while also providing information about the size of the evidence base and where gaps 

exist. Systematic reviews that also examine qualitative studies can answer questions about how those interventions 

work, facilitating the possibility of replication or scaling. These types of reviews can be structured around topic areas 

or dates. Systematic reviews driven by dates allow CLEAR to include the most up-to-date literature on a variety of 

labor topics of interest to DOL, regardless of the size of the evidence base. Other types of reviews – such as rapid 

evidence reviews – can help address time-constrained questions. Rapid reviews quickly summarize evidence on 

relevant programs and potentially promising strategies to support evidence-based decision-making in response to 

pressing labor issues, such as the COVID-19 pandemic. 

In FY 2022, CLEAR will begin to address a variety of research questions of interest to DOL agencies through its 

evidence reviews, anticipating beginning up to 4 new evidence reviews in FY 2022 of interest across DOL agencies. 

Topic areas may include reemployment programs and retraining/reemploying workers as part of a transition to a 

sustainable energy economy; effective practices for securing employer compliance with workplace protections; and 

effects of paid leave policies on workers’ employment and earnings.

CLEAR routinely conducts briefings and develops short syntheses upon completion of its evidence reviews 

for DOL staff, to support their ability to understand and use the results of the reviews to make evidence-based 

decisions. CLEAR is currently exploring how to build on past dissemination approaches to continue to support 

evidence-based decision-making, increase capacity to consume evidence, and refine or develop new types of 

relevant syntheses and dissemination approaches.
36 DOL EVIDENCE-BUILDING PLAN

FISCAL YEAR 2022-2026

DOL Staff Capacity Building: Evaluation, Measurement, 

and Analytics Training Program

CEO is developing a training program to increase the capacity of DOL staff to generate, evaluate, 

assess, and use labor-related evidence. The training will include detailed courses on the introduction and 

application of concepts related to program evaluation and data analytics, resulting in certifications for DOL staff 

who have completed the program. The development of the curriculum is still underway and has been informed 

by findings from the DOL Evidence Capacity Assessment, including results from a DOL staff survey about use 

and knowledge of evidence-related topics, as well as staff focus groups. 

Improved Measurement & Data Collection of Key Constructs

BLS, CEO, and several DOL sub-agencies plan to conduct activities during FY 2022-2026 to improve the way 

certain key labor concepts are measured, ultimately improving the quality of data available about these topics. 

DOL plans to conduct at least four initiatives of this type, as described below.

Review of Consumer Price Index (CPI) Measures

BLS frequently contracts with the independent Committee on National Statistics (CNSTAT), a branch of 

the National Academy of Sciences, to examine new sources of data and improvements to processes.

Currently, CNSTAT is reviewing the BLS Consumer Price Index to evaluate whether to take explicit steps to 

mitigate upper-level substitution bias, as well as best methods for estimating price change for complex topics, 

such as health insurance, owner-occupied housing, and durables. Separate from the CNStat review, BLS is 

exploring options for providing additional CPI indexes for sub-populations, including perhaps different income 

categories. As work in these areas continues, BLS will focus on testing, including focus groups, field testing, 

and other options to determine how best to implement change. Other work will be needed on systems, statistical 

methods, publication review, implications for data collection, and other aspects of the CPI process. Such work 

may provide evidence that can be helpful in ongoing equity-related policy discussions. Throughout FY 22-26, BLS 

expects to explore and potentially modify its current CPI processes to construct its indexes, possibly blending 

traditionally collected data with alternatively collected and sourced data. 
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Updating Supplements to the Current Population Survey (CPS)

• Review of Contingent and Alternative Work 

Arrangement Measures. A committee assembled 

by CNSTAT, the Committee on Contingent Work 

and Alternative Work Arrangements, released their 

findings and recommendations in July of 2020. In 

FY 22, BLS will focus on testing, including focus 

groups, field testing, and other options to determine 

how best to implement changes or the addition of 

new questions to the Contingent Worker Supplement 

to capture information on current and future work 

arrangements as the labor market continues to 

evolve. Going forward, other work will be needed on 

systems, statistical methods, publication review, and 

other aspects of the survey process to implement 

the changes. 

• Revisions to the CPS Disability Supplement.

In FY 2022 and FY 2023, and beyond, ODEP will 

collaborate with BLS, CEO, and internal and external 

stakeholders to engage in foundational research 

and analysis to revise a Disability Supplement that 

has been periodically fielded (FY 2012, FY 2019, 

FY 2021) as part of the CPS. This project will result 

in a detailed mapping of current data sources 

on individuals with disabilities and employment, 

identifying gaps in the data. It will also result in the 

development of new survey questions designed 

to more accurately capture the characteristics and 

labor market challenges of people with disabilities, 

including questions focusing on identifying a broader 

population of people with disabilities that may be 

used to augment or revise the current six disability 

questions included in the CPS. New survey questions 

developed as part of this project will be included in a 

CPS Disability Supplement fielded in July 2024. 

• Revisions to the CPS Veterans Supplement. In 

March 2021, BLS solicited public comments on a 

proposed revision to the Veterans Supplement, which 

is supported by DOL’s VETS sub-agency and is 

used by VETS and the U.S. Department of Veterans 

Affairs (VA), as well as external researchers to study 

the labor force status of veterans. Changes to the 

survey instrument were informed in part by an expert 

panel of external stakeholders convened by CEO 

in 2019. The revised survey instrument eliminates 

outdated questions and adds additional items related 

to veterans’ transition from active duty to civilian 

employment, details about working with serviceconnected disabilities, awareness of VA benefits, 

and work duties while in the Armed forces. The 

Supplement is expected to be conducted in August 

2021, August 2022, and August 2023.

• Update to the UI Non-Filer Supplement. The 

UI non-filer supplement provides one of the only 

sources of information about unemployed workers 

who may be eligible for UI but do not apply for 

or receive benefits. The supplement therefore 

provides important information to support equity 

assessments of the UI system. As part of DOL’s 

ongoing commitment to improving access to timely 

UI benefits, CEO will work with BLS, other units in 

DOL, and external stakeholders to understand how 

this supplement could be revised to provide timely 

and actionable information about barriers workers 

experience to claiming UI benefits—particularly in 

light of various changes to UI administration as part 

of the American Rescue Plan Act. 

Improving Foundational Knowledge of Care Economy Workers

In FY 2022 and beyond, ODEP expects to work with BLS, CEO, and internal and external stakeholders, to 

assess how federal data collections can better identify workers in caregiving professions, including workers 

who provide homebased or community-based care to others. Caregiving workers are not always identified in 

existing federal datasets that provide occupational information. Improving and standardizing the way caregiving 

occupations are measured in data collections is a necessary step toward improving foundational knowledge 

about these workers.
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Improving DOL’s Data Infrastructure

DOL continues to make significant strides to improve data infrastructure in ways that bring significant 

value to internal and external users. These efforts are intended to make access to data more efficient and 

effective, and to ensure that data are fit for purpose, interoperable, comprehensible, and have utility for the 

widest possible set of users and uses. These efforts have benefited from active cooperating and coordination 

between the Chief Data Officer, Chief Information Officer, Evidence Officials, and the agency staff comprising 

DOL’s Data Board. While some of this work involves technology, much of it involves culture change, and 

success will depend on closely aligning the proposed activities with Agency mission, existing and prospective 

departmental needs, and demonstrable value for all stakeholders. 

Improved Access to Data

DOL has created a new consolidated data portal and Application Programming Interface (API) that provides on 

demand access to machine-readable data. The new data portal and API should give Federal, private and public 

data users outside the department easier ways to find DOL data, as well as simple, consistent, and repeatable 

methods to access data that integrate well with research, analysis and reporting functions. These services have 

gone live within the department and the service is being evaluated for its adoption and customer experience, 

and the ways in which agencies integrate the service into their operations to inform decisions about opening it 

up to the public. The goal of this work is to expand the convenience and functionality with which DOL data can 

be leveraged by researchers and members of the public.
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Data Governance

DOL has been actively working to expand data management and governance to support departmental and 

administration priorities. DOL is leveraging its enterprise data inventory, network of data stewards, and 

analytical capabilities to assess the state of characteristic and demographic data across the enterprise, and 

develop plans to make that data more fully interoperable. The DOL Data Board is working towards adoption of 

a metadata standard and development of open source tools to manage that metadata and leverage it to assure 

data quality and conformity to adopted standards. DOL has set up shared services for address standardization, 

which will benefit data quality and strongly enhance our ability to perform entity resolution across different data 

sets and programs. All of these efforts are seeking to raise DOL’s data capacity and expand and improve the 

potential use cases for our data.

DOL Restricted Use Data Access Program 

DOL has extended the service it currently uses to support evaluation contracts and contractors to researchers. 

DOL has arranged data files and supporting documentation for selected prior evaluation studies and can, under 

specific circumstances, make those data sets available for secondary analysis. This capability can be extended 

as well to support primary or secondary analysis of agency data sets with sensitive or non-sensitive PII under 

specific circumstances. DOL will continue to work towards making the largest share of its data available, and 

supporting the appropriate analysis of DOL data to create insights about program impacts, stakeholder outcomes, 

and information that can support evidence based policymaking, resource allocation, and program administration. 

Examination of BLS data collection and storage alternatives

A data lake is a cloud based data repository that allow users to store large amounts of unstructured/raw or 

structured data. BLS is moving forward in exploring the feasibility of using a data lake to enhance the efficiency 

of data collection and storage. After the proof of concept period, which included demonstrations from major 

vendors in the field, a successful pilot project is now moving forward to explore the feasibility of using a data 

lake to enhance the efficiency of data collection and storage. BLS is now exploring whether a data lake can be 

a cost effective path to expand use of alternative data and automate some of BLS’ survey functions. 
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Technology Modernization Fund Data Modernization Initiative

OASAM is modernizing DOL’s enterprise data infrastructure to deliver enterprise capabilities in data 

management, advanced analytics, and open data, leveraging the DOL IT Platform’s Data Analytics Capability, 

to improve the use of data for generating evidence. As part of this initiative, OASAM is examining the optimal 

process for facilitating intra-agency data sharing using an existing modernized and consolidated data source, 

assessing what critical enhancements to enterprise data infrastructure could enable DOL data sources to be 

modernized, secured, and consolidated with data governance applied, and functioning effectively in production. 

OASAM is identifying the critical enhancements to enterprise data infrastructure to enable DOL agencies to use 

advanced capabilities (e.g. AI, ML, and/or Advanced Analytics).

Improving Accessibility of ETA Data Books 

ETA is working to improve the accessibility and usability of data books that present information on the 

characteristics, services, and outcomes of individuals served by Workforce Innovation and Opportunity Act 

(WIOA) and Wagner-Peyser Act programs. This is intended to facilitate research conducted by states, local 

areas, and DOL, using administrative data. In past years, the data books have been produced in less accessible 

formats that were difficult for researchers and practitioners to utilize. This project will enhance the usability of 

the data, providing it in more customizable and accessible formats that will facilitate researchers’ capacity to 

search, download, analyze, and create visualizations with the data. 
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V. Potential Future Evidence-Building Topics 

In addition to the confirmed projects listed above, DOL has identified a short list of future evidence-building 

topics that are of interest to the department and/or DOL stakeholders. While DOL has an interest in exploring 

the topics, it has not yet identified a specific research project to do so. The following topics may be integrated 

into research activities described in Section IV (for example, as a priority topic for research grants), or they may 

inform DOL’s future evidence-building commitments. 

• The care economy & workforce (Possible partner 

agencies: WB, ETA, ODEP, others)

These topics include:

• Equity in the workplace: hiring, retention, promotion, 

wages, pensions, protections (Possible partner 

agencies: OSHA, OFCCP, WHD, EBSA, others)

• Vulnerable workers/migrant worker rights (Possible 

partner agencies: WHD, ILAB)

• The future of work, post-pandemic and pandemic 

effects, long-COVID-19/disability issues and 

recovery among vulnerable sub-groups (Possible 

partner agencies: ETA, ODEP, VETS, WB, others)

• Re-employment services for marginalized groups 

(Possible partner agencies: ETA)

• Labor-related data gaps on marginalized groups 

(Possible partner agencies: many)

• Understanding the prevalence of retaliation against 

workers and potential remedies, including effective 

strategies for increasing workers’ awareness of their 

rights and deterring employer incentive for retaliation 

(Potential partner agencies: WHD, others)

• Inequality in hiring and employee management, 

retention, and promotion processes (potential 

partner agencies: OFCCP, others)

• Pay equity and analysis of data sources regarding 

pay (potential partner agencies: OFCCP, others)

• Job quality and essential occupations, including 

caregivers (potential partner agencies: ETA, others) 
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Appendix A. Mapping of Planned Departmental EvidenceBuilding Activities by DOL Strategic Goal 

Note: Numbers correspond to Project numbers in body of the report. 

DOL PRIORITY LEARNING AREAS

1: 

Ensuring 

Equity in 

Employment 

& Training 

Programs

2: 

Reducing 

Barriers to 

Women’s 

Employment

3: 

Studying 

Effects of the 

COVID-19 

Pandemic

4: 

Improving 

Enforcement 

Activities & 

Protections 

for All

5: 

Strengthening 

Unemployment 

to Reemployment

6: 

Other 

Learning 

Priorities

1: 

Build Opportunity 

and Equity for All

1, 2, 3, 4, 

5, 6, 7, 8

7, 8, 

9, 10, 11 1, 9, 12 22 35 38

2: 

Ensure Safe 

Jobs, Essential 

Protections, and 

Fair Workplaces

N/A N/A 13

15, 16, 17, 

18, 19, 20, 21, 

23, 24, 25, 26, 

27, 28, 29, 30, 

32, 33, 34

N/A N/A

3: 

Improve 

Administration of 

and Strengthen 

Worker Safety Net 

Programs

N/A N/A N/A 31 36, 37 N/A

4: 

Statistical Goal – 

Produce GoldStandard Statistics 

and Analyses

N/A N/A N/A N/A N/A See 

Section IV

Management Goal: 

A Department 

Grounded in 

Evidence, Innovation, 

and Employee 

Engagement

N/A N/A 14 N/A N/A 39, 40, 41, 

42, 43, 44

TEGIC GOALS STRA DOL

DOL 

STRATEGIC

GOALS
U.S. Department of Labor