What do job postings reveal about the evolving labor market and how can those insights be used to shape workforce programs and policies?

Our two-part Enhancing Labor Market Insights with Jobs Data Applied Data Analytics (ADA) Training Program equipped over 50 participants representing 25 organizations from 18 states with the tools and skills they needed to examine those questions. We led the program in partnership with the National Association of State Workforce Agencies (NASWA) and the National Labor Exchange (NLx) Research Hub from October 2024 to April 2025.

Advancing Data Literacy to Support Evidence-Based Decision-Making

Our Enhancing Labor Market Insights with Jobs Data program began with four weeks of training in basic coding concepts and use of the Administrative Data Research Facility (ADRF)–our secure cloud environment for working with restricted-use data. In the 12 weeks that followed, participants learned about exploratory data analysis, record linkages, contextualizing employment demand, labor market projects, and other key topics.

From Knowledge to Action: Collaborative Research Projects

With access to NLx job posting data from 2015 onward, participants applied their skills through collaborative research projects that explored eight key labor market questions.

Team Connecticut and Oregon: How can job postings help educators identify skills in high demand?

Using 2023–2024 NLx job postings data from Connecticut and Oregon, the team built an interactive dashboard that:

·       Identifies in-demand occupations
·       Reveals top skills currently in high demand from employers using O*NET
·       Highlights active employers
·       Links directly to current job ads

Learn more here: https://tinyurl.com/2dtuyst8

Team Mississippi and Tennessee: How do employers adjust hiring requirements in response to worker shortages?

Using 2018–2023 NLx job postings data from Mississippi and Tennessee, along with Occupational Employment and Wage Statistics, the team compared shifts in required education, skills, and experience across occupations and identified patterns of employer flexibility in response to labor market gaps.

They also highlighted how these adjustments can inform workforce development strategies and pointed to future opportunities for deeper analysis of trends across industries and occupations.

Learn more here: https://tinyurl.com/p6d542r6

Team New Jersey, Pennsylvania, and Ohio: How can job ads be used to measure labor demand across the economy?

Using NLx job postings data, the Job Openings and Labor Turnover Survey (JOLTS), and the Quarterly Workforce Indicators (QWI), the team defined demand as the total requirement for labor and examined postings to capture employer needs for workers and specific types of work. 

Learn more here: https://tinyurl.com/3u4b5tv3

Team Maryland and Virginia: Which employers are driving growth in the rapidly expanding cybersecurity market and what does the demand for labor look like?

The team used 2021–2024 NLx job postings data for their states and DC, Integrated Postsecondary Data System data, and the Maryland College Labor Sector and Wage Explorer to examine which:
- Employers are driving the regional hiring surge
- Cybersecurity roles are most in demand
- Technical skills dominate job descriptions

Learn more here: https://tinyurl.com/yzz7de47

Team Missouri and Wisconsin: How is the labor market being reshaped by the growing use of artificial intelligence (AI) tools?

Using NLx job postings, the occupations list from Wisconsin’s Taskforce on Artificial Intelligence, Occupational Employment and Wages Statistics (OEWS), states’ employment projections data, O*NET/Standard Occupational Classification, and an “AI exposure” measure developed by the Wisconsin AI Task Force, the team compared job postings across ten high-exposure and ten low-exposure occupations to see where automation might hit hardest or barely register. They also examined shifts in demand and skills requirements, highlighting which workers are most at risk and how states can prepare for the future of work.
Learn more here: https://tinyurl.com/ywkhd3k3

Team Colorado, Illinois, and Kentucky: How do layoffs correlate with trends in job postings?

Using NLx job postings and WARN data, the team examined whether new opportunities emerge where jobs are lost, evaluated the reliability of WARN notices and other signals as early warnings, and analyzed whether displaced workers can realistically fill new job openings. Their approach sheds light on how labor market shocks ripple through the system and whether affected workers can be absorbed into new demand.

Learn more here: https://tinyurl.com/5n77xby3

Team California and Washington: What are the most common requirements for occupations with low-barriers-to-entry and how do they differ for emerging occupations?

Using NLx job postings, the team identified roles with minimal credentials that lead into fast-growing fields, revealing the first rungs on new career ladders. Their analysis highlights how these entry points shape worker mobility and guide state strategies for building inclusive pathways into the workforce.

Learn more here: https://tinyurl.com/2d97n683

Team New York and Texas: How does labor demand line up with local labor supply across major metros?
Using NLx job postings as demand and American Community Survey measures as supply, the team compared patterns by O*NET Job Zones in cities like New York and Dallas, incorporating wages to identify tight or slack markets. They revealed mismatches between who is hiring and who is available to work, and highlighted data caveats, such as geographic clustering and occupation definitions, to support smarter regional workforce planning.

Learn more here: https://tinyurl.com/yc3pbhja