Privacy, Fairness, and Model Risk Governance in Sustainable People Analytics

Whilst sustainability targets are driving organisations to make more intensive use of human data, this trend is transforming HR analytics from a reporting tool into a component of decision-making architecture. This transformation is expanding the scope of data collection, increasing the visibility of employees, and intertwining privacy, fairness, perceptions of surveillance, and model risk within the same process. This study addresses the question of how this interplay can be managed at the project level. A literature review has been combined with an analysis of publicly available corporate documents, from which a compact toolkit for sustainable HR analytics has been derived. The toolkit is structured around defining project boundaries, documenting data and model assumptions, matching risks with controls, and ensuring transparency and human oversight. In this way, the chapter provides a practical framework that ensures analytical capacity is considered alongside organisational legitimacy and employee trust.