# Check salaries for unexplained pay gaps

Analyzes pay data within comparable roles to find gaps not explained by legitimate factors and suggests next steps.

- Topic: Data & Analysis
- Framework: RTF
- Level: Standard
- Tags: Analyze, Fill-in Template
- Source: https://www.thinkwithprompt.com/prompts/check-salaries-for-unexplained-pay-gaps

## Prompt

```text
Help me run a pay equity check on our salary data.

**Data:** [PASTE or describe columns - job title, job level/grade, job family, location, base pay, hire date, time in role, performance rating, and gender / race-ethnicity or other groups where lawfully collected]
**Pay ranges by level (if any):** [RANGES]
**Groups to compare:** [e.g. men vs. women, by ethnicity]
**Population size:** [NUMBER]

Do this:
1. **Group comparable roles** - same job family, level, and location. Tell me where groups are too small to compare (under 5).
2. **Raw gap** by group overall and within each comparable group.
3. **Adjusted view** - explain how much of the gap legitimate factors (level, tenure, location, performance) appear to account for. If the data supports it, outline a regression approach and the code (Python or Excel steps) to run it; do not fabricate results.
4. **Individual outliers** - people paid below range or notably below peers with similar factors, regardless of group.
5. **Root-cause questions** - starting salaries, promotion timing, negotiation, inconsistent off-cycle raises.
6. **Remediation options** with an estimated cost formula and prioritization.

Output: summary for leadership, a findings table, and a list of outliers to review. Treat results as a starting point; confirm methodology and any legal privilege considerations with counsel, and follow local pay equity and data protection rules.
```

## What to fill in

- RANGES
- e.g. men vs. women, by ethnicity
- NUMBER

Free to copy and use. From ThinkWithPrompt (https://www.thinkwithprompt.com/), a library of 2,663 curated AI prompts.