SKILL-BASED WORKFORCE PLANNING USING HR ANALYTICS

Abstract

Skill-based workforce planning has become a strategic priority for contemporary organizations operating under conditions of technological disruption, volatile labour markets, and rapidly changing job expectations. Conventional workforce planning models generally concentrate on positions and headcount, but they often overlook the evolving mix of competencies required to sustain business performance. This study addresses that limitation by positioning HR analytics as a core enabler of skill-based workforce planning. The study examines whether analytics capability helps organizations identify skill gaps, forecast workforce needs, improve planning efficiency, and strengthen organizational performance. A quantitative design was adopted, and structured questionnaire data were obtained from 60 respondents representing different organizational roles. Structural Equation Modeling (SEM) was used to test the relationships among four constructs: HR Analytics Capability, Skill Identification, Workforce Planning Efficiency, and Organizational Performance. The findings indicate that HR analytics exerts a meaningful positive influence on skill identification and workforce planning efficiency, while efficient planning contributes directly to improved organizational outcomes. The direct path from HR analytics to organizational performance is also positive, suggesting that analytics creates value not only through planning processes but also through broader strategic alignment. The model demonstrated acceptable fit, with CFI = 0.94 and RMSEA = 0.052, confirming the adequacy of the proposed framework. The study contributes to theory by combining an analytics perspective with a skill-based workforce approach, and it contributes to practice by offering a data-informed model for HR decision making. Overall, the article shows that analytics-driven HR strategies can reduce skill mismatches, support talent optimization, and promote sustained organizational effectiveness.