HR Analytics as a Catalyst for Organisational Performance: An Evidence-Based Approach

Abstract

Human resources (HR) analytics is the new weapon to enhance workforce performance, increase employee engagement and retention. The purpose of the study was to empirically examine the effects of HR practices on three organisational outcomes – employee satisfaction, turnover, and the effectiveness of training. The data from 150 information technology (IT) sector employees were subjected to correlational and regression analysis. Research indicates that both satisfactions with salary and work-life balance are important predictors of turnover, so this analysis underscores the need for HR approaches to be informed by data in addressing employee attrition and skill shortages. The research also reinforces the significance of predictive analytics and artificial intelligence (AI) in driving strategic workforce intelligence, enabling businesses to enhance productivity and secure sustainable competitive advantage in an ever-shifting business climate. In addition, the study highlights the growing importance of integrating advanced analytical tools into HR decision-making processes to improve organisational efficiency and workforce planning. The findings suggest that evidence-based HR interventions can support better alignment between employee expectations and organisational goals. By leveraging real-time workforce data, organisations can proactively identify performance gaps, enhance training effectiveness, and foster a culture of continuous improvement. Overall, the study emphasises that strategic use of HR analytics contributes not only to improved employee outcomes but also to long-term organisational sustainability and competitiveness

Keywords: HR Analytics, Employee Satisfaction, Turnover Rate, Predictive Analytics, Data-Driven HR

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