Full transparency on how we process, analyze, and present OSHA enforcement records.
All enforcement data originates from the U.S. Department of Labor, Occupational Safety and Health Administration (OSHA). This includes:
Data is sourced from the DOL's public enforcement data systems and imported into our database. We do not modify source data fields — penalty amounts, citation counts, dates, and addresses are presented exactly as reported by OSHA.
Each facility receives a composite risk score on a 0–100 scale. The score is calculated using a weighted model that considers multiple enforcement dimensions:
| Component | Weight | What It Measures |
|---|---|---|
| Penalty Severity | 40% | Total penalties relative to industry median |
| Citation Gravity | 25% | Presence and count of willful/repeat violations |
| Violation Density | 20% | Number of citations per inspection |
| Abatement Status | 15% | Percentage of citations marked as abated |
The penalty severity component uses log-scale normalization to prevent outliers (e.g., $38M in the BP Texas City case) from distorting the scale. A facility with penalties at the 95th percentile of its NAICS sector receives a penalty component score near the maximum.
Facilities are classified into four enforcement tiers based on their risk score:
| Tier | Risk Score | Criteria | Significance |
|---|---|---|---|
| Tier 1 Critical | 75–100 | Penalties >$100K or willful violations | Most severe enforcement actions; substantial probability of death or serious physical harm |
| Tier 2 Severe | 50–74 | Penalties $25K–$100K, serious violations | Significant enforcement with elevated citation gravity |
| Tier 3 Elevated | 25–49 | Penalties $5K–$25K, multiple citations | Above-average enforcement activity for the sector |
| Tier 4 Standard | 0–24 | Penalties <$5K, routine inspections | Baseline enforcement consistent with industry norms |
Every facility report includes a comparison against its NAICS (North American Industry Classification System) sector average. This answers the critical question: "Is this facility's enforcement history unusual for its industry?"
We maintain a benchmark lookup table (svep_naics_stats) containing pre-computed statistics for each 2-digit NAICS sector:
The benchmark multiplier shown on each report (e.g., "27.2× the national average") is calculated as:
In addition to industry benchmarks, each report includes state-level positioning. The state percentile indicates where a facility ranks among all inspected facilities in its state:
State statistics are maintained in a dedicated lookup table (svep_state_stats) covering all 50 states and U.S. territories.
Our top 49,800+ facility reports include AI-generated analytical narratives that synthesize enforcement data into readable, contextual assessments. These narratives are generated using Google's Gemini language model and include:
AI-generated narratives are clearly based on the underlying enforcement data and regulatory frameworks. The AI does not fabricate facts, invent citations, or create penalty amounts. All quantitative claims in the narrative (penalty amounts, citation counts, dates) are sourced directly from the DOL database record for that facility.
The analytical commentary (e.g., "penalties significantly exceed the national median") is derived from our benchmark calculations, not from AI speculation.
OSHA citations reference Code of Federal Regulations (CFR) standards using numeric identifiers (e.g., 1926.0501). We maintain a translation table that maps the 30+ most frequently cited standards to plain-English descriptions, making reports accessible to non-specialist readers.
Users should be aware of the following limitations:
Our database is periodically refreshed from DOL source data. Analytical enrichment is applied to the highest-severity facilities first, with ongoing expansion of coverage. The current dataset includes 2,336,195 facility records with 49,800+ receiving full analytical enrichment.
The methodology described on this page drives every facility report on SVEP Navigator. Explore the platform to see how these analytical frameworks translate into actionable intelligence: