User Case | How to build true Pay Transparency through Data & Analytics

How to establish a consistent, fair, and transparent pay policy across Europe (and beyond) ensuring readiness for Pay transparency?

This user case will outline a pragmatic approach to data readiness for a small multinational (appr 2500 EE's in about 10 countries) with HQ in Europe.

Listen to Marta Montes from Cellnext on the topic, addressing:
- Roadmap
- Methodology & Tools
- Data Harmonization

The meeting will close with Q&A

Achieving true pay transparency requires much more than executing a set of calculations. This user case shows how a multinational company must translate the EU Pay Transparency Directive into an operational reality—revisiting its Fair Pay ambition, harmonizing a global job architecture, uplifting data quality, and embedding transparency into annual reward cycles. The session emphasizes that pay transparency is both an urgent compliance requirement and an important cultural shift, demanding cross‑functional collaboration across HR, IT, payroll, and leadership.

A central insight is the role of structured governance and automation in managing unadjusted and adjusted Gender Pay Gap (GPG) results. Companies must prepare for growing reporting expectations by strengthening objective criteria, refining the use of 2–3 meaningful factors for regression, and ensuring the merit cycle becomes a practical tool for closing pay gaps. The conversation also highlighted challenges with tooling, data harmonization, and communication—areas where organizations benefit significantly from peer learning.

Key Takeaways

• Start with a clear Fair Pay ambition
  A coherent Fair Pay framework and harmonized job architecture create the structural foundation needed for compliant and credible pay transparency. This avoids misalignment between data results and organizational principles.
• Use the merit cycle as a corrective mechanism
  Embedding GPG adjustments into the annual merit process—supported by dashboards showing changes before and after merit—turns the cycle into an active lever for equity rather than a passive pay‑distribution activity.
• Limit objective factors to what truly drives pay
  Using too many regression factors dilutes clarity. Limiting analysis to 2–3 well‑justified factors makes adjusted GPG outcomes easier to interpret and communicate.
• Invest early in data harmonization with payroll and IT
  Including benefits and country‑specific elements requires a structured, repeatable pipeline—mapping 50+ pay elements per country and aligning with a global standardized template.