HR Analytics

The goal of an HR analytics project is to help an organisation make better decisions about its workforce. Hiring, retention, and development decisions are often made based on intuition or experience rather than data. HR analytics brings the same rigour to those decisions that finance and operations teams apply to theirs.

The daily work involves working with HR data such as employee records, survey results, performance ratings, and exit interviews. You clean and analyse this data, build models to identify patterns or predict outcomes, and present findings to HR teams or senior management. A large part of the work is making sure that conclusions are well-supported and that the analysis accounts for confounding factors.

The main tools are Python and SQL for analysis, and Excel or BI tools for reporting. Statistical methods including regression analysis, survival models for employee tenure, and survey analysis are commonly used. Privacy is an important constraint: employee data is sensitive and must be handled carefully under GDPR.

HR analytics projects appear across any sector where organisations are large enough to have dedicated people analytics teams, including financial services, retail, and government. In the Netherlands, large employers and public institutions increasingly invest in this type of work. The project connects to the Data Analyst and Data Scientist roles and draws on methods also used in Evaluation Research.