Most importantly, reimagining job quality measurement can improve workers’ jobs and their lives. With better data about the lived experiences of workers, we can ensure that public and private investments create and support good jobs with equitable pathways into them and that our workforce systems put all workers on a path to economic mobility. Better data can also help business leaders design jobs where workers thrive, which will in turn support improved talent attraction and retention, productivity, and business resilience.

The work of measuring good jobs has never been more timely or urgent. Below are 10 ways we can transform job quality measurement in America.

Workers need basic income stability, but surveys ⁴ show that they also care about other job quality elements like benefits, schedules, safety, training and career pathways, equity, and voice. The federal government must strengthen our data ecosystem to capture the full range of job quality elements that workers most value. In the short-term, philanthropy can partner with state and local agencies and research partners to develop and pilot model measurement infrastructure and approaches with potential for scale. Ultimately, we need clear, shared, definitions of the key components of job quality, measured regularly and systematically by trusted federal agencies. Broadening and standardizing current measures in response to worker priorities can close knowledge gaps and position business and government partners to increase the number of good jobs that attract and retain workers. This effort to measure what matters should begin with the recognition that working people hold unique expertise about how jobs should be designed to increase their engagement and productivity. Workers—and especially those who have been most locked out of opportunity—should play a central role in designing data collection and use.

Women and people of color face occupational segregation ⁵ and are more likely to hold precarious jobs without pathways to economic mobility. To address these disparities in job quality, we need disaggregated data that exposes gaps and enables systems to actively tie strategic investments to more equitable outcomes. This starts with the federal government expanding the critical data equity efforts ⁶ already underway, including by requiring federally funded programs implemented by state and local agencies and nonprofits in partnership with business to collect, analyze, and report on impact by race and gender, as well as other demographic characteristics, and collecting sufficient sample sizes to enable analysis by sub-populations and intersectional identities. It also requires asking workers questions about their experiences of discrimination and bias to increase understanding of the relationship between these experiences and employment and health outcomes. Finally, we must redefine success metrics for public programs to reward equity, not just program completion or placement in any job, shifting from a focus on participants’ “worthiness” for services to the system’s ability to deliver results.

Job quality is a key indicator of business performance and resilience, and a growing number of investors recognizes that access to better human capital data will improve investment decisions. In 2020, the Securities and Exchange Commission (SEC) began requiring publicly-traded companies to report on human capital data. To strengthen such disclosure, philanthropy, investors, and nonprofits, alongside federal government agencies such as the U.S. Department of Commerce (DOC) and the U.S. Department of Labor (DOL), can align government, business, and labor behind a common set of human capital metrics and a standardized reporting framework. Federal agencies can also help to streamline business reporting by facilitating access to and linkage of the significant human capital data that firms already report to government entities. Investors can accelerate disclosure by requesting human capital data from their portfolio companies, and collaborating with researchers to continue to build the evidence base that providing good jobs supports enhanced financial performance, such as through improved operational resilience and sophistication and/or improved employee attraction, retention, and engagement. These efforts can dramatically increase the availability of firm-level data on job quality, while advancing the practice of investing for good jobs and ultimately influencing markets to raise the floor for workers at scale.

We lack a systematic way of collecting and aggregating job quality data, but we hold many pieces of the puzzle in different places, from the wage records collected through the unemployment insurance system to data held by the Occupational Health and Safety Administration (OSHA) to business data held in payroll processing systems. The Federal government, state and local government, and commercial platforms can pair their data, standardize collection processes, and create shared data goals to improve government effectiveness without burdening workers, government agencies, or businesses with additional data collection requests. In fact, over time such linkages can reduce administrative burden by making it easier to use existing data to operate more effective programs. By prioritizing transparency, privacy, consent, and equity, ⁷ these data integration efforts can also help to rebuild community trust in government, especially as data are used to address disparities and improve outcomes. To strengthen data linkage, federal, state, and local agencies can explore the establishment of interagency agreements to facilitate data sharing, as well as pilot specific use cases to test feasibility and build trust. The robust data infrastructure developed as a result of better linkage will enable researchers to surface new learning, government agencies to address silos to better coordinate service delivery, and policymakers to make data-informed decisions that produce better results for workers, businesses, and the economy.

Companies across industries and sizes increasingly recognize that providing good jobs and equitable pathways into them is a business and competitive advantage as well as a moral imperative. As we emerge from the heart of the pandemic, businesses are seeking new strategies to attract and retain talent. This presents a window of opportunity to support businesses to share and use job quality data, and to spark a race to the top to improve jobs. The federal government and workforce providers, in partnership with commercial platforms, can provide light-lift pathways and incentives for data sharing, such as offering information on marketplace or competitor trends to companies in exchange for their data, supporting businesses that provide data to learn about talent management practices that can improve performance, and providing resources and technical assistance to help employers improve job quality.

Our current data systems don’t adequately capture the size or demographic makeup of the self-employed workforce, let alone the quality of their jobs. These jobs are especially important to track because they are disproportionately held by workers of color, ⁸ can be particularly unstable, and lack many basic labor protections. To understand this growing yet undercounted workforce and better meet their needs, the federal government should build on progress underway through the Census Bureau’s Contingent Worker Supplement (CWS) by partnering with state governments to explore and pilot ways of systematically collecting earnings information on contract workers, to deepen understanding of the working conditions and needs of the “gig” workforce. In the near-term, philanthropy can partner with researchers to uncover information about the size, makeup, and job experiences of non-W2 workers.

What gets measured gets done, and the metrics we track in our vast public workforce system ⁹ don’t tell us enough about whether the jobs we train and refer people into offer a pathway to economic mobility. Reimagining performance measurement can support better job quality for hundreds of thousands of U.S. workers by shifting the focus from placement into the first available job—however precarious—to a focus on increasing the availability of jobs that sustain and uplift the people in them. The federal government, state and local governments, and workforce providers can begin to collect standardized, disaggregated job quality data across training programs, including data from employers and not just program participants, to measure indicators like provision of a living wage and benefits, scheduling practices, and advancement pathways. Targeting the federal funds that subsidize employer training and hiring to employers that meet good jobs standards can encourage businesses that benefit from this talent pool to provide economy-boosting jobs. Revisions to workforce system metrics can also serve as a model for other social service systems such as Temporary Assistance for Needy Families, Supplemental Nutrition Assistance Program Education and Training, and refugee employment services.

Procurement offers a powerful and underutilized tool for gathering employer data, and in turn directing dollars toward good jobs. Government agencies and anchor institutions ¹⁰ such as foundations, hospitals, and universities spend billions of dollars each year purchasing goods and services, creating and supporting millions of jobs. Yet we miss opportunities to align this spending with our shared goals to strengthen job quality data infrastructure and ultimately advance good jobs and workforce equity. The federal government, state and local governments, and anchor institutions including philanthropy can use contracts and grants as an engine for workforce data collection. This requires public and anchor partners to embed job quality and equity standards—including disclosures, metrics, and preference points—into proposals, and investing in technical assistance infrastructure focused on supporting diverse, community-based organizations to compete for contracts. Foundations can test and model promising practices and tools for data collection, reporting, and small business technical assistance that can in turn be scaled through government partners.

State and local leaders are eager to innovate to increase access to equitable economic mobility, but they are working with an incomplete picture of worker experience and program performance. We can’t ask for better measurement without supporting enhanced government capacity, especially at a time when many agencies are under-resourced. To lay the foundation for a stronger job quality data infrastructure, the federal government and philanthropy can provide support and incentives that enable state and local government to strengthen their data collection and utilization skills and tools. Prioritizing the creation of an intergovernmental research and analytics consortium of policy and data experts from the public and private sector can rapidly build state and local data capacity to drive more effective, equitable policies and programs. Coupled with the provision of technical assistance, financial incentives, and compliance flexibility to local governments in exchange for regular job quality reporting, this investment will help shift focus to data-driven, outcomes-based decision-making.

Diverse segments of philanthropy—from funders focused on equity to those focused on government effectiveness—can come together with corporate and government partners to meet this unprecedented moment by supporting job quality measurement. Philanthropy has played a central role in the development of economic measurement in the United States, from the days when the Rockefeller Foundation supported the creation of a measure of national income ¹¹ which became the basis for today’s Gross Domestic Product. Funders must seize this once-in-a-generation opportunity to ensure that our national measurement systems truly reflect the needs and experiences of working people. Foundation, government, and business partners can come together to advance a common vision to strengthen job quality measurement, and to coordinate investment in scalable demonstration projects that drive the development of a robust, worker-centered data infrastructure.