The hidden pitfalls of salary Benchmarking in Europe

Salary benchmarking is a cornerstone of HR compensation strategy, yet in Europe it often becomes a murky, inconsistent process. Between varying data sources, regional pay structures, tax systems, and job title inflation, it can feel like trying to assemble a puzzle with mismatched pieces. Using the example of a medior-level Data Scientist in the Netherlands, this article dives into why salary benchmarking in Europe is more complicated than it appears—and how companies can avoid common mistakes. 

1. Benchmarking Tool Disparity: One Role, Many Numbers 

Adjust your strategy to the distinct environments of each nation. Ensure the information is relevant to the local market. Salaries can differ greatly within and between nations. Roles should be matched in terms of responsibilities rather than just job titles. Use trustworthy sources like Eurostat, Mercer, Korn Ferry, or national statistics offices.

For example, the median annual salary for a "Medior Data Scientist" in the Netherlands varies across platforms:

• Deel.com: €92,194
• Glassdoor: €60K-€80K (average €70K)
• Levels.fyi: €73,423 (25th-75th percentiles: €56K-€92K)
• SalaryExpert: €116,876 (range: €82K-€145K)
• TechPays: KLM pays €69K, Booking.com pays up to €174K
  
  

These figures can differ by more than 100%, making meaningful benchmarking nearly impossible if taken at face value.

2. Lack of Role Definition and Title Clarity

Title inflation and ambiguity cause benchmarking inconsistency. A "Data Scientist" might have different responsibilities in different organisations. For instance, one company might expect a Data Scientist to focus on data cleaning and preparation, while another might require advanced machine learning model development and deployment. This lack of standardisation can lead to significant discrepancies in salary data.

To address this, companies can adopt standardised job architecture frameworks like Mercer IPE or Radford. These frameworks evaluate roles based on scope, complexity, and impact, rather than just job titles. By doing so, organisations can ensure that they are comparing like-for-like roles, leading to more accurate benchmarking.

3. Geography Still Matters (Even in a Remote-First World)

Compliance with local employment law is essential. Minimum wage levels and collective labour agreements vary across Europe. The EU’s Pay Transparency Directive requires larger employers to disclose salary ranges and gender pay gaps.

Consider total compensation, including employer costs like social security, health insurance, and pension contributions. Benefits such as company cars, lunch vouchers, and mobility allowances are standard in many European markets.

Even in hybrid and remote work, geography shapes pay scales. A Data Scientist in Amsterdam might earn more than one in Eindhoven or Utrecht. Multinationals adopt international pay scales, while regional businesses take a conservative approach.

4. Bonus and Equity Obfuscation

Positioning your company on the pay spectrum should reflect your business priorities. Inflation and union-negotiated cost-of-living increases complicate things. Total compensation includes bonuses, equity, relocation support, and benefits.

For example, Booking.com offers €147,000 total compensation for a Machine Learning Scientist, with €115,000 base and €22,000 bonuses. Adyen offers €100,000 base with €20,000 annual equity. Benchmarking only on salary distorts competitiveness.

Statutory benefits and employment protections affect employer costs. In France, employer contributions can drive up costs by 45–50% above gross pay. The Netherlands' 30% ruling for expats can improve net income but is rarely reflected in benchmarking data.

5. Data Validity and Recency

Benchmarking platforms rely on aggregated or anonymous submissions, which can be outdated or misreported. Scrutinise data recency and sample size robustness. For example, Glassdoor's snapshot was based on 387 responses but lacked transparency on industries or regions.

Conclusion

Salary benchmarking in Europe requires nuance. Combine external data with internal insights, role clarity, regional cost-of-living, and statutory benefit awareness. Consult local experts and triangulate at least three sources before drawing conclusions. Contact our HR expert today.