Research
Compensation, market data and pay equity.
If you work in HR and need to talk about pay with confidence, start here. Three guided chapters explain, in plain language and with worked examples, how we define pay, how we read market data and how we analyse pay gaps. Each one ends with the full research text and its sources, for anyone who wants to check the reasoning.
The guide is evidence-informed, with Germany and the EU as its primary setting, and draws on statistical offices, legislation, original academic research and methodological publications. The component ladder, the data-entry design and the operating controls are our explicit recommendations, not an internationally mandated compensation taxonomy.
Chapters
Three questions, in order.
Chapter 1
Organising compensation without losing its meaning
Before you compare salaries you need to know which salary you mean. This chapter gives you a plain dictionary of pay components, a five-level ladder from base salary to total remuneration, the difference between actual and target, and the checks that keep a total honest.
For compensation leads, HR analysts and Power BI authors · guided read with diagrams, worked examples and the full text
Read the chapterChapter 2
Getting and using market compensation data
A market figure is only as good as the population behind it. This chapter explains what a benchmark is, which public sources you can use for Germany, the EU and beyond, how to acquire and document a reference, and the traps that turn percentiles into confident wrong numbers.
For compensation leads and reward specialists · guided read with diagrams, worked examples and the full text
Read the chapterChapter 3
Analysing pay gaps responsibly
One pay-gap number is asked to answer three different questions. This chapter walks through the formula and its denominator, how composition hides or creates a gap, what comparable work means, what an adjusted model can and cannot say, and the EU directive timetable.
For executives, employee representatives, statisticians and reward specialists · guided read with diagrams, worked examples and the full text
Read the chapterHow the evidence was gathered
A focused narrative review, built to be inspected.
Sources were searched and inspected on 2 October 2026, prioritising official statistical definitions and methodological documentation over commercial summaries. Academic evidence covers incentive design, wage-setting, transparency and pay-gap methods. This is a focused narrative review, not a systematic review or meta-analysis. Publisher abstracts support the limited findings attributed to papers where full text was unavailable. No claim is made to have reproduced their estimates, and no consulting sales material supplies the analytical rules.
Definitions, formulas, constructed examples, source links and limits are exposed throughout. Citations near claims distinguish external evidence from our proposed operating policy and from constructed examples. Dataset descriptions concern definitions and access, not a guarantee of future availability. Before an operational refresh, record the actual release, observation period and downloaded metadata. Before statutory reporting, check applicable national law and current reporting instructions.
Reading routes
Start where your decision is.
| Reader | Start here | Decision supported |
|---|---|---|
| Compensation lead | Framework §§1 to 5, market §§1 to 5 | Pay policy, comparability, benchmark selection |
| HR analyst or Power BI author | Framework §§4 to 7, then the product page | Prepare one employee table and reconcile it |
| Executive or employee representative | Pay gap §§1 to 4 and §8 | Interpret differences without overstating causation |
| Statistician or reward specialist | Pay gap §§5 to 7 and the cited methods | Design a separate adjusted analysis |