DIGGING DEEPER INTO THE 10 BIG IDEAS
Table of Contents
Introduction
The 10 Big Ideas
Digging Deeper
- Measure what matters to workers, capturing a full range of job quality indicators
- Center equity in measurement
- Increase mandatory human capital data disclosure
- Link public and private data to gain new insights into the quality of jobs
- Leverage business data to demonstrate the return on investment from good jobs
- Revise data systems to include and support the non-W2 workforce
- Strengthen workforce system metrics to deliver results for workers and businesses
- Use public and private spending to measure and strengthen equity and good jobs
- Strengthen state and local capacity for data-driven decision-making to advance good jobs
- Invest in strengthening job quality measurement
Understanding the Impact
Appendices
Acknowledgements
#1: Measure what matters to workers, capturing a full range of job quality indicators.
These actions are intended for…
Regularly and systematically measuring the set of job quality elements that workers most value in trusted federal datasets will change public narratives about the health of the economy, and enable data-informed decisions that propel equitable economic opportunity.
In 2022, leaders across government, business, the nonprofit sector, and labor—along with workers themselves—made important strides to align on a shared good jobs definition1 driven by worker priorities. Now, we must attach indicators and metrics to each element, and embed these in federal statistical surveys, workforce program performance measures, and commercial measurement tools to scale worker-centered job quality measurement.
To put this into practice, federal government agencies, with support from philanthropy and state and local government, should:
1. Broaden job quality indicators beyond wage:
Wage is critically important but insufficient to determine the quality of a job. The quality of other factors – such as schedule stability, benefits, or voice – is keenly important to workers,2 and directly impacts worker attraction, advancement, and retention, creating ripple effects in employer productivity and economic prosperity. Tracking and analyzing these factors systemically allows both the public and private sectors to support and tap into the full potential of workers. Capturing this information also allows researchers to assess how core aspects of job quality impact worker wellbeing, economic security, and other critical outcomes.
Partners in state and local government, business, labor, and nonprofits should:
- Adopt a shared definition of a good job which includes non-compensation aspects such as worker safety, career pathways, schedules, and worker voice. The release of shared Good Jobs Principles 3 by the U.S. Departments of Labor (DOL) and Commerce (DOC), which closely resembles the Good Jobs Champions Statement 4 utilized by the JQMI, is a groundbreaking step. The federal government should use this definition in procurements and encourage state and local governments to infuse it into their own procurements and workforce system metrics.
- Building on the work of the JQMI to identify specific metrics and indicators to capture each component of job quality (see Appendix 3), DOL can take the lead in standardizing job quality measurement across federal agencies and can provide guidance about metrics to state and local governments, nonprofits, investors, and employers. Philanthropy can support state and local agencies to develop and pilot scalable measurement systems that capture the full range of job quality indicators. Using common language, metrics, and benchmarks to track and report on job elements can help to inform a more robust, shared understanding of workers’ lived experience of the labor market and facilitate action to close equity and access gaps.
2. Refine existing survey modules to collect targeted job quality data
Existing statistical instruments managed by DOL and other federal government agencies capture critical information about market activity, working conditions, price changes, and productivity in the U.S. economy, but fall short of capturing the realities of key job quality elements for workers.
To strengthen job quality measurement, working group members proposed that federal statistical agencies...
- Add a short set of questions measuring key components of job quality to federal surveys such as the National Longitudinal Surveys (NLS) and evaluate options for future inclusion in the Current Population Survey (CPS). One important category of questions would measure work hour stability, predictability, and control to track changing configurations of scheduling practices across occupations and industries. The addition of these questions would support estimation of disparities in the quality of work schedules by worker characteristics and better understanding of how work hour instability, unpredictability and inadequacy may be interfering with workers’ fulfilling caregiving responsibilities, pursuing education or training, and carrying multiple jobs. Another category would assess workers’ ability to exercise voice and create change within their workplaces through both individual and collective action. If needed, new questions could be piloted through a private survey to validate questions and demonstrate the connection between responses and concrete economic and social outcomes for workers. See Appendix 2 for sample questions and Appendix 3 for additional details and questions.
- Explore options to update either the Employment Situation Establishment Survey or the Quick Business Response Survey, which can be deployed on an adhoc basis, module by module, much as was done during the pandemic, 5 to include a data point connecting the aggregate weekly hours and wages specifically for net jobs added or lost in each period to the existing data on average weekly hours and wages reported by subsector. This change is necessary to reflect the substantial shifts in the universe of jobs available to U.S. workers since the survey methodology was developed as many jobs classified as full time now represent fewer than 40 hours. See Appendix 2 for additional details related to measuring full-time employment.
- Run regular survey modules devoted to gathering more data on workplace climate and worker experiences of discrimination through NLSY or CPS. This will provide a fuller picture of how discrimination and biased treatment on the job contribute to turnover and decreased job satisfaction for women, workers of color, and older workers, as well as present significant health risk through their impacts on stress levels. Anti-discrimination enforcement typically takes place well after an incident has occurred, and we have few mechanisms for identifying industries and occupations that are regularly subject to higher rates of discrimination and bias. These data could help policymakers, regulatory agencies, and business proactively curtail discrimination and bias before it results in a job separation or some other major workplace disruption. The Health and Retirement Study’s “Psychosocial Leave Behind Questionnaire” 6 provides one model for comparison, and James S. Jackson’s work developing psychosocial scales for Major and Everyday Experiences of Discrimination 7 could help to guide the question format.
- Revise the Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics (OEWS) survey to request that respondents report earnings and tips separately from hourly wage rates in order to better understand employer reliance on gratuities to compensate workers, and provide a more nuanced picture of income. This breakdown would provide insights into the ratio of tips to earnings in different occupations, industries and geographies and information could be displayed in a user-friendly interface via the OEWS website. Insights on the breakdown of earnings could support workers exploring career options, as well as worker advocates seeking to provide stakeholder education on the impacts of subminimum wages for tipped occupations.
- Adjust the Job Openings and Labor Turnover Survey (JOLTS) survey questionnaire to divide the category of “layoffs and discharges” into two or more separate categories to reflect the reason for involuntary discharge including business closure, reductions in operations, temporary workforce adjustments, and performance related termination. These data are currently unavailable from any other federally-administered surveys and private surveys on this topic are limited in their scope. Data were previously collected through the Mass Layoff Statistics (MLS) program on “reason for separation” in extended mass layoff events involving 50 or more workers laid off for more than 30 days but the MLS was discontinued in 2013 due to budget cuts. Revising JOLTS would provide deeper insights into workers’ job security, drivers of unemployment, and discharge variances by industry, geography, and business cycles.
Endnotes
- The Families and Workers Fund and the Aspen Institute Economic Opportunities Program. A Shared Definition of Job Quality (2022).
- Gallup. Lumina Foundation, Gates Foundation and Omidyar Network Tell Full Story of U.S. Job Quality.
- Department of Commerce and Department of Labor. Good Jobs Principles.
- The Families and Workers Fund and the Aspen Institute Economic Opportunities Program. A Shared Definition of Job Quality (2022).
- United States Bureau of Labor Statistics. 2021 Results of the Business Response Survey (February 9, 2022).
- Philippa Clarke et al., Health and Retirement Study Psychosocial Working Group, University of Michigan. Guide to Content of the HRS Psychosocial Leave-Behind Participant Lifestyle Questionnaires: 2004 & 2006 – Documentation Report Version 2.0 (December 5, 2008).
- David R. Williams, Harvard T.H. Chan School of Public Health. Everyday Discrimination Scale.