People Analytics for Diversity
Useful D&I measurement pairs demographic composition with behavioral signals - hiring funnels, promotion velocity, regretted attrition. Composition alone flatters; the behavioral metrics reveal whether diverse hires stay and advance.
Funnels before composition
Headcount percentages describe outcomes; funnels explain them. Track applicant-to-interview, interview-to-offer, offer-to-acceptance by demographic group. A composition problem almost always enters as a specific funnel stage problem - and stages are fixable while percentages feel abstract.
| Metric | What it reveals |
|---|---|
| Stage pass-through rates | Where candidates drop disproportionately |
| Promotion velocity by group | Whether advancement distributes evenly |
| Regretted attrition by group | Inclusion failures showing up as exits |
| Survey belonging scores | Leading indicator preceding attrition |
Attrition is the honest metric
Hiring targets can be hit without changing experience; regretted attrition cannot. If a demographic group leaves at elevated rates with high performance, the environment is the finding. Pair exit data with belonging survey signals to catch it earlier.
Privacy boundaries
Small-cell suppression protects individuals - never report groups so small that identities are inferable. Collect self-identified demographics voluntarily, explain usage plainly, and restrict access to aggregated views. Inference from names or photos substitutes guesswork for consent and should be off-limits.
These analytics share infrastructure with pay equity work; both depend on data actually being visible to the people accountable for acting on it.
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Frequently asked
What sample size do we need?
Trends need enough volume to mean something; below roughly ten per cell, report directionally with explicit caveats rather than precise figures.
Should we publish our numbers externally?
Transparency builds credibility when numbers are improving and context exists; publishing without narrative invites misreading.
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