Every figure in every report traces back to an official federal source. No proprietary estimates, no black boxes. Here's exactly what we use, how we use it, and how you can verify it yourself.
Four public datasets. All maintained by federal agencies. All independently accessible.
Regional wages, employment levels, and location quotients for 393 metro areas across 800+ occupations. Published by the Bureau of Labor Statistics.
National 10-year growth rates, annual openings, and typical education requirements for 830+ occupations.
Canonical task statements, technology profiles, and certification data for 1,000+ occupations. Developed by the DOL.
Institution data, program completions, and student outcomes for 5,000+ institutions. Published by NCES.
Four steps between the federal source and the number in your compliance document. Nothing proprietary happens to the data along the way.
Your uploaded job postings are semantically compared against O*NET occupation task statements. Each posting sentence is matched to the canonical task list for your SOC code, identifying which tasks employers are actively requesting.
Wages, employment, growth projections, and location quotient are pulled directly from BLS datasets using your specific SOC code and metro area code. No transformation is applied — the values are read as-is.
SOC codes, MSA codes, and area titles are checked for consistency across all data sources. If an occupation–region combination has suppressed data in BLS, the report flags it rather than estimating.
Data is organized into the report format required by your framework — Workforce Pell, Perkins V, WIOA, accreditation, or planning — with the source cited next to every number.
Pick a data point and follow it step-by-step from the federal dataset to your report — then verify it yourself on the source website.
Each May, BLS surveys 1.1 million employers and publishes wage data for every occupation in every metro area. The raw dataset covers 393 metros × 800+ SOC codes.
When you select a metro area and SOC code, we query the OEWS dataset for that specific combination — for example, area_code: 12060 (Atlanta) × soc_code: 31-9092 (Medical Assistants). The value returned is the annual_median field with no transformation.
The wage is displayed alongside the MSA name and area code so reviewers can see exactly which region's data they're looking at. Reports that evaluate wage thresholds (Workforce Pell, WIOA) compare this value against the BLS national all-occupations median ($48,060).
Go to bls.gov/oes → One occupation for one area. Select your metro area and enter the SOC code shown in the report header. The Annual median wage column will match the figure in your report.
Verified across all 553,192 data points in the BLS source file. View validation study →
Every two years, BLS projects employment levels 10 years out for every occupation. The current edition covers 2024–2034. This is national data — BLS does not publish regional projections.
The change_percent and annual_openings fields are looked up by SOC code from BLS Table 1.7. Annual openings combines growth openings with replacement needs (retirements, career changes). These are national figures clearly labeled as such.
The Accreditation report displays these in a dedicated "National Employment Projections" section. Perkins and Workforce Pell reports use them in demand validation. Reports always note "national" scope when displaying this data.
Go to bls.gov/emp → Table 1.7. Search for the SOC code in the report header. The percent change and median annual wage columns will match.
All 832 occupations verified for math consistency, threshold accuracy, and cross-dataset plausibility. View validation study →
For each occupation, O*NET publishes 15–25 task statements describing what workers actually do. These are developed by occupational analysts and validated by worker surveys.
Each sentence in your uploaded job postings is embedded and compared to the O*NET task statements using semantic similarity. We report which tasks were confirmed by employer postings and which were not — even when the wording differs.
Reports show the task coverage percentage (e.g., "17 of 22 O*NET tasks confirmed across 15 postings"), with each task listed as core (80%+), common (40–79%), or occasional (<40%) based on confirmation rate.
Go to onetonline.org. Search for the SOC code in the report header. Under "Tasks," you'll see the same task statements listed in the report.
Location quotient measures how concentrated an occupation is in your metro area compared to the national average. An LQ of 1.2 means the occupation is 20% more concentrated locally. BLS computes this directly from OEWS survey data — it is not an estimate.
The location_quotient field comes straight from the OEWS dataset for your metro × SOC combination. No computation or adjustment. We display it with standard interpretation: ≥1.2 above-average, 0.8–1.19 near-average, below 0.8 below-average.
All five regional reports display LQ with the same thresholds and color coding, ensuring consistent interpretation regardless of which compliance framework you're using.
Go to bls.gov/oes → One occupation for one area. Select your metro area and SOC code. The "Location quotient" column will show the same value.
Every report draws from the same underlying data. This shows exactly which data points appear in each report type.
| Data Point | Source | Workforce Pell | WIOA ETPL | Perkins V | Accreditation | Curriculum | Employer |
|---|---|---|---|---|---|---|---|
| Median Wage (regional) | BLS OEWS | ||||||
| Wage Distribution (10th/90th) | BLS OEWS | ||||||
| Regional Employment | BLS OEWS | ||||||
| Location Quotient | BLS OEWS | ||||||
| Growth Rate (national) | BLS Projections | ||||||
| Annual Openings (national) | BLS Projections | ||||||
| Task Alignment / Coverage | O*NET + Postings | ||||||
| Certifications | O*NET + Postings | ||||||
| Technologies | O*NET + Postings | ||||||
| Emerging Requirements | Postings (derived) |
Understand our analytical methodology, review validation studies, or see how this data powers compliance documentation.