Frame the question
- Define the populations and pay decisions in scope
- Agree what "fair" means and how it's tested
Reward & Pay Equity
The headline pay gap tells you nothing about cause. A controlled analysis separates the gap you can explain from the adjusted gap that shouldn't exist — the version a board, a regulator and a works council will each accept.
The need
Pay decisions get challenged on fairness — and the raw number can't defend them.
Useful ahead of pay-transparency regulation, a board or works-council review, or whenever "our gap is X%" invites a question no one can answer.
What this builds
- A controlled pay-gap regression — explained vs adjusted gap, by grade, role and geography
- Reward benchmarking that positions pay against the market, not just internally
- A defensible, board- and regulator-ready pay-equity position with a remediation view
Live example · synthetic data (Crescent Consulting Ltd)
Live view · like-for-like cohorts, the method stated on the page, and every flagged cohort named
Equal pay is measured inside cohorts of the same grade, department and country, with a minimum cohort size so no individual is identifiable. The method is on the screen, because a number a board can challenge has to be a number you can explain.
The delivery path
Every step uses the same inHR model.
Run the analysis
- Controlled regression: isolate explained vs adjusted gap
- Benchmark reward against the external market
Build the response
- Owners, budget and a phased remediation plan
- A board- and regulator-ready narrative
Completion standardThe engagement is complete when you can explain every point of the gap and defend the adjusted number to a board or a regulator.
Business Intelligence