Benchmark our HR metrics against industry standards
Compares your turnover, hiring, absence, and engagement figures with benchmarks you supply, and shows where you are strong or at risk.
The prompt
Help me compare our workforce data with external benchmarks and find where we stand.
Organization: [industry, size, location(s)]
Scope: [whole organization / department / team]
Our metrics, with time period and how each is calculated: [e.g. voluntary turnover %, first-year turnover %, time to fill, offer acceptance rate, absence rate, engagement score, internal promotion rate, span of control, diversity representation]
Benchmarks I have, with source and year: [PASTE - e.g. from a salary survey, industry association, government labor statistics]
What leadership wants to know: [e.g. "are we losing people faster than peers?"]
Steps:
1. Check that each pair is comparable: same definition, period, population, and region. Flag any mismatch and how it could skew the comparison.
2. Compare each metric and classify it as stronger than benchmark, in line, or weaker. Explain what the gap likely means in practice.
3. Identify the 3 biggest strengths and 3 biggest risks, and possible causes to investigate (not conclusions).
4. Suggest benchmark sources I could use for metrics where I have none, without quoting any figures from them.
Rules: never invent benchmark numbers - if I haven't given a benchmark, mark it [ADD BENCHMARK]. Do not draw conclusions about individuals, and keep any demographic analysis at a group level large enough to protect privacy.
Return a table: Metric | Ours | Benchmark (source) | Gap | Assessment | Notes on comparability. Then a half-page summary for leadership with recommended next steps.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore HR & Hiring prompts
What to fill in
- industry, size, location(s)
- whole organization / department / team
- e.g. "are we losing people faster than peers?"
- ADD BENCHMARK
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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