Pay Gap Calculation in 5 Steps: Adjusted vs. Unadjusted

· Category: AGG · Reading time: 3 min · As of 2026-05-02
Practitioner note: This is not legal advice. For specific situations, consult a qualified attorney or compliance officer.

TL;DR

  • Germany median 2025: 18% unadjusted gender pay gap, 6% adjusted (Federal Statistical Office)
  • 5-step process: data extract → job classification → median per gender → regression-based adjustment → reporting
  • Critical thresholds: <2% adjusted = unremarkable; >5% triggers Joint Pay Assessment under EU Pay Transparency Directive 2023/970
  • Tooling for SMEs: Excel + manual pivot up to 100 employees; Python/pandas for 100–500
  • Fine risk (DE BMAS draft): up to €50,000 per violation

1. Data Extract from Payroll

Per employee: gender (binary for statistics), gross annual salary, pay band/role, years of experience, position, last promotion date.

2. Job Classification

Use a 4-criteria scale (Skill, Effort, Responsibility, Working Conditions) with 5 levels each. Each role receives a score from 4 to 20.

3. Median Calculation per Gender

In Excel, build a pivot table filtered by gender with the MEDIAN formula. Calculate both absolute and relative differences.

4. Adjustment

Run a multiple regression (Excel Data Analysis or Python pandas/statsmodels) using experience, position, and pay band as variables. The adjusted pay gap is the unexplained residual after objective factors are accounted for.

5. Reporting and Measures

Gap >5%: Joint Pay Assessment required. Gap 2–5%: action plan. Gap <2%: documentation and annual re-reporting.

Summary

Adjustment typically reduces the unadjusted gap by a factor of 2 to 3. If the gap remains >5% after adjustment, structural pay reform is unavoidable. Pair this calculation with the methodology in our Pay Equity Audit 2026 guide for full EU Pay Transparency Directive 2023/970 compliance.

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Frequently Asked Questions

Which pay gap value is 'normal' and when does it become critical?

Germany median 2025: 18% unadjusted gender pay gap, 6% adjusted (Federal Statistical Office). EU average: 13% unadjusted. Critical thresholds: <2% adjusted = inconspicuous. 2-5% = monitor + justification documentation. >5% = mandatory Joint Pay Assessment from 06/2026 (EU 2023/970). >10% = immediate measures + supervisory reporting risk. Adjustment typically reduces the gap by a factor of 2-3 — i.e. 15% unadjusted yields 5% adjusted. If the unadjusted gap cannot be explained (>5% after adjustment): reform of pay structures is required.

Which tools are suitable for pay gap calculation?

Four options by SME size: 1) Excel + manual pivot (up to 100 employees): free of charge, ~2 person-days initially, export data from payroll. 2) Python + pandas/statsmodels (100-500 employees): free of charge, ~3-5 person-days initially, multiple regression with objective variables. 3) PayAnalytics SaaS (from 250 employees): EUR 5,000-15,000/year, automated reports + dashboards. 4) Mercer/Korn Ferry/Hay Job Evaluation + Pay Equity Analytics (Enterprise): EUR 30,000-100,000/year. Recommendation for SMEs with 50-250 employees: Excel template from the AGG Kit + annual manual calculation.

Who really has to submit the pay gap report from 2026?

Staggered per Directive (EU) 2023/970: 250+ employees: annually, first time 07.06.2027 (2026 data). 150–249 employees: every 3 years, first time 07.06.2027. 100–149 employees: every 3 years, first time 07.06.2031. <100 employees: no EU obligation (national regulation possible). Joint Pay Assessment trigger: from a 5% unjustified gap per worker category that is not corrected within 6 months. Content requirement: unadjusted + adjusted by gender, broken down by pay groups + variable compensation. The specific fine level in Germany is still open — German transposition delayed (status 02.05.2026), EU deadline 07.06.2026 confirmed by the EU Commission on 18.12.2025.

Which variables legitimately 'explain' a pay gap?

Objective factors according to the CJEU/Federal Labor Court (BAG): 1) Professional experience (years + industry specificity). 2) Position + hierarchy level. 3) Qualification (degree, certificates). 4) Performance (with documented evaluation). 5) Collective bargaining classification (if applicable). 6) Market value of the specialization (e.g. SAP consultant vs. generalist). NOT legitimate as explanation: salary negotiation outcome ('she asked for less'), part-time effect without pro-rata, 'historically grown', 'labor market reality'. In Joint Pay Assessment procedures, all variables are audited individually — only statistically significant ones are accepted.

Sources

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