Human Resource Analytics and Evidence-Based Decision-Making: Developing an Integrated Framework

Human resource analytics has matured from descriptive reporting through diagnostic and predictive analysis to prescriptive recommendation, yet many organisations with mature analytics functions still make HR decisions on intuition and precedent. This paper develops an integrated framework in which analytics maturity produces evidence-based decision-making only when line managers have the analytics literacy to consume evidence and when analytics are integrated into decision processes. A simulation of 500 organisations across four maturity stages shows that evidence use in HR decisions rises with maturity from 0.28 to 0.49 on average, but that the gain depends almost entirely on manager literacy: at the prescriptive stage, evidence use is 0.31 among organisations with low manager literacy and 0.68 among those with high, and at the descriptive stage high-literacy organisations use evidence no more than low-literacy ones (0.33). The maturity–literacy interaction (0.14 per stage) dominates the maturity main effect (0.01), and process integration contributes independently (0.20). Decision quality rises with evidence use. The paper argues that HR analytics investment should be matched by investment in managers’ capacity to use evidence and in the decision processes that deliver it, and proposes a framework with four layers, data and analytics, evidence products, decision integration and decision-maker capability, each of which must be present for analytics to change decisions.