Open Access
ARTICLE
Data-Driven Human Resource Management: Enhancing Employee Productivity Through Predictive Analytics and Performance Mapping
Issue Vol. 1 No. 01 (2025): Volume 01 , Issue 01 Oct 2025 --- Section Articles --- Published Date: 2025-10-01
Abstract
The evolution of Human Resource Management (HRM) into a data-driven strategic function has transformed how organizations recruit, manage, and retain talent. Traditional HR practices relied heavily on intuition, managerial experience, and manual evaluations, often resulting in inconsistent assessments of employee performance. In contrast, the modern workplace demands objective, evidence-based HR decisions supported by predictive analytics, machine learning algorithms, and advanced performance mapping tools. This study investigates how data-driven HRM enables organizations to anticipate employee behavior, detect performance trends, optimize workforce capabilities, and improve productivity at both individual and organizational levels. Using a mixed-method research framework, the paper presents an integrated model that aligns predictive analytics with HR metrics such as attrition probability, task efficiency, learning agility, and competency development. The findings indicate that organizations adopting data-driven HRM achieve faster decision-making, higher employee engagement, and substantial productivity improvements, especially in dynamic and competitive environments.
Article Cover Image
