The United States needs a common, trusted language for skills that is timely, local, and useful for real decisions. O*NET could provide the public foundation, but to fulfill that role, it must modernize through local detail, open standards, validation, and governance that responds to users.
CREC’s new white paper, A Common Language for a Local Labor Market: Modernizing O*NET into the Trusted Standard for Timely, Local, and Actionable Skills Data, explains why this matters.
Labor markets are local, but much of our data is not
Technology changes work first inside firms. Employers adopt new tools, reorganize tasks, and redefine jobs before those changes appear in national statistics.
These differences matter to state data offices, workforce boards, economic development organizations, colleges, and regional partners. They help employers find workers, guide students toward careers, and decide which training programs merit investment. When national data lack detail or currency, these organizations often build their own analyses. That can solve an immediate problem, but it also creates duplication and makes comparisons harder.
O*NET should provide the common language
O*NET represents a valuable inventory of knowledge, skills, and abilities, but it should not try to replace job postings, wage records, employer input, education data, or private analytics. Instead, O*NET should serve as the neutral public reference that allows these sources to connect. It can provide common definitions, identifiers, occupational descriptions, crosswalks, and validation standards.
Surveys continue to be invaluable as national benchmarks. Job postings can reveal changing demand. Wage and education records can show which skills and credentials lead to employment and earnings. Artificial intelligence can help organize text and identify emerging skills. A modernized O*NET can help provide a shared structure for the myriad sources of skills data.
Trust must remain the foundation
Faster data is not always better data. Job postings may reflect employer wish lists. Private taxonomies may rely on unclear methods. AI-generated classifications may reproduce bias or imply more precision than the evidence supports.
Skills data should show where it came from, how it was produced, what its limits are, and whether it has been tested against outcomes. O*NET should remain open to challenge. It should earn adoption by proving that it supports better decisions, not through mandate.
Private and alternative taxonomies should support comparison, validation, and possible inclusion. Independent evaluation and community engagement can help improvements flow back into the public standard.
Eight actions for a modernized system
The paper recommends that federal and state partners:
- Modernize O*NET with validated AI and local detail.
- Create interoperable standards.
- Build state capacity.
- Fund state experimentation.
- Require third-party evaluation.
- Create public-private governance.
- Strengthen legal and data-sharing systems.
- Provide durable funding for the public backbone.
The goal for O*NET is not one national database of skills. It is a common reference that helps employers, workers, educators, and public leaders make better decisions.
Read the full CREC white paper: A Common Language for a Local Labor Market: Modernizing O*NET into the Trusted Standard for Timely, Local, and Actionable Skills Data.