workforce data is broken
career intelligence is scattered across BLS wage tables, O*NET skill taxonomies, DOL apprenticeship databases, state agency portals, union local websites, employer job postings, training program catalogs, and PDF flyers. automation risk isn't tracked. application windows are invisible. program outcomes are unreported. no single system connects labor market signals to training pathways to employer demand.
the result: the u.s. needs 2 million more skilled workers by 2028. workers make career decisions with incomplete data. employers can't find skilled labor despite $1.8 trillion in infrastructure spending. workforce boards allocate billions without real-time supply-demand signals. and only 7% of job seekers even consider the trades. that's not a pipeline failure — it's a data infrastructure failure. the intelligence layer between workers, programs, employers, and government doesn't exist.
five layers of workforce data
the hardhat protocol structures workforce data into five interconnected layers — from career exploration to program outcomes. each layer is machine-readable, standardized, and open.
scored daily
& training
& prerequisites
periods
& placement
today, a worker researching a career has to visit 5–10 different websites, decode eligibility rules from PDFs, and guess when applications open. the protocol collapses that into a single, navigable data layer — the same way GTFS collapsed transit schedules into a single feed that powers Google Maps, Apple Maps, and thousands of apps.
current coverage
- 350+ occupations scored daily — AI risk, salary, demand, growth, and market stability
- 26 trades with apprenticeship data — program details, apply steps, tips, and FAQs
- 50 state apprenticeship guides — state agencies, top programs, licensing, and prevailing wage
- 670+ training programs — accredited trade schools with placement data
- 182 career guides — salary, how-to-become, and career outlook articles
- application window tracking — real-time open/closed status for apprenticeship programs
- program outcome data — completion rates, retention, and demographic breakdowns
- employer compliance layer — utilization ratios, IRA requirements, and prevailing wage tracking
what GTFS did for transit
- fragmented schedules across agencies
- no standard format
- Google created an open standard
- 10,000+ agencies now publish data
- powers Maps, Citymapper, Transit
- fragmented programs across agencies
- no standard format
- hardhat building an open standard
- 27,000+ programs to be mapped
- powers career navigation at scale
one protocol, one feedback loop
every decision one stakeholder makes creates a signal for the others. workers searching for trades tell programs where demand is. employer hiring patterns tell government where to fund training. the protocol is the connective layer that closes the loop.
free, open, machine-readable
workforce data should be a public good — the same way transit data became a public good after GTFS. the hardhat protocol is designed to be embedded, extended, and built upon by anyone: workforce boards, community colleges, nonprofits, state agencies, and private developers. every layer feeds a feedback loop between workers, employers, programs, and government — each stakeholder's actions creating signals for the others.
the worker-facing tools on hardhat.careers are the first application built on this protocol. they won't be the last.