Review on Predictive Workforce Planning Using Big Data Analytics: A Strategic Hr Perspective

Predictive workforce planning powered by big data analytics has emerged as a cornerstone of strategic human resource management (SHRM), enabling organizations to move beyond reactive staffing toward proactive talent optimization. This critical review synthesizes 16 high-impact empirical and conceptual studies published between 2021 and 2026 to evaluate the integration of big data infrastructure, machine learning forecasting algorithms, and strategic HR decision-making. Utilizing the PRISMA 2020 systematic framework, this study examines how enterprise data integration, real-time talent telemetry, and predictive modeling enhance workforce capacity planning, attrition risk mitigation, and skills gap forecasting. The review critically analyzes key socio-technical paradoxes, including algorithmic bias, employee data privacy concerns, and HR analytical skill gaps. Findings demonstrate that predictive analytics capabilities significantly enhance strategic HR decision-making (β = 0.48, p < 0.001) and organizational agility (β = 0.45, p < 0.001) when paired with robust data governance and analytical competency. The paper provides an integrative framework and actionable recommendations for HR leaders navigating data-driven workforce transformation.