HR Analytics and People Analytics: Applications, Challenges, and Future Research Directions

People analytics the label has largely displaced the older “HR analytics,” though the two still get used interchangeably is no longer a fringe interest within human resource management. It has become one of the field’s most argued-about developments. This narrative review works through peer-reviewed research published mostly between 2015 and 2025 to ask three things: where in the HR function analytics has actually taken hold, what keeps getting in its way, and what researchers still owe the field. Talent acquisition, retention modelling, and workforce planning show the clearest gains; engagement, wellbeing, and learning applications are newer and less settled. Adoption overall is patchy. Bad or fragmented data, thin analytical capability inside HR teams, internal resistance, and a set of escalating ethical and legal threats—among them algorithmic bias in automated CV and résumé screening, and worker-surveillance practices that breach employee privacy—together explain a familiar pattern in this literature the field promises more than it has yet shown. The paper ends by laying out where research needs to go: firmer theory, causal evidence rather than correlational snapshots, governance frameworks built for algorithmic and AI-enabled HRM, more attention to how employees themselves experience being analysed, and work outside the usual large-firm, Western settings small businesses and developing economies chief among them

HR analytics, people analytics, workforce analytics, human resource management, evidence-based management, algorithmic HRM

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