Understanding Workers' Compensation Data: How to Read and Use Key Graphs

What Workers' Compensation Graphs Show

Workers' compensation graphs translate raw claims data into visual patterns that help employers, insurers, and regulators spot trends, identify risk areas, and measure the effectiveness of safety programs. Common charts include loss‑run curves, frequency‑severity splits, and trend lines of claim costs over time.

Key Metrics Displayed in Graphs

Frequency

Shows the number of claims per 100 employees. A spike may indicate a new hazard or a lapse in training.

Severity

Measures average cost per claim. Rising severity can signal that injuries are becoming more serious or that medical billing practices have changed.

Cost per Employee

Combines frequency and severity to give a dollar figure per employee, useful for budgeting and benchmarking.

Loss Run Curve

Plots cumulative claims cost over a period, often 12‑18 months, highlighting whether costs are front‑loaded or spread out.

Trend Lines

Show year‑over‑year changes, allowing comparison against industry averages.

Reading a Frequency‑Severity Breakdown

Most organizations use a two‑axis scatter plot: frequency on the X‑axis, severity on the Y‑axis. The plot is divided into quadrants that guide action:

• High frequency, low severity: focus on repetitive tasks and ergonomic improvements.
• Low frequency, high severity: investigate high‑risk incidents like falls or equipment failures.
• High frequency, high severity: urgent safety overhaul required.

How to Build a Basic Workers' Compensation Dashboard

Select Data Sources

Gather data from your payroll system, claims management software, and external industry benchmarks.

Choose Visualization Tools

Excel, Power BI, Tableau, or dedicated safety analytics platforms can generate the needed charts.

Set Benchmarks

Compare your figures to state averages or peer groups to contextualize performance.

Using Graphs for Compliance and Reporting

Regulators often require annual loss run reports. A clear graph can demonstrate that your loss trend is stable or improving, supporting claims of proactive safety management.

Interpreting Seasonal Patterns

Many industries experience higher injury rates during peak seasons (e.g., construction in summer). Graphs that overlay seasonal markers help distinguish normal fluctuations from anomalies.

Case Study: Reducing Claim Costs with Data‑Driven Insights

A mid‑size manufacturing firm plotted its frequency‑severity scatter over five years. The graph revealed a cluster of high‑severity falls in one assembly line. After installing guardrails and retraining staff, subsequent graphs showed a 45% drop in severity and a 30% drop in frequency.

Common Pitfalls to Avoid

• Ignoring outliers: a single catastrophic claim can distort the trend.
• Not normalizing for workforce size: compare per‑100‑employee rates rather than raw counts.
• Failing to update data: use quarterly or monthly refreshes for timely action.

Resources for Further Learning

• OSHA's injury & illness data • National Safety Council's benchmarking reports • State workers' compensation boards' public data portals