Enhancing Workforce Efficiency in Public Sector Supply Chains through Predictive Analytics

Public sector supply chains are critical to the provision of essential services, but can lack efficiencies because of rigid structures, resource constraints and disjointed systems. This review delves into the benefits of predictive analytics for optimizing workforce management, through its ability to forecast, schedule and allocate resources more effectively using data. Predictive analytics helps in making proactive decisions in workforce planning, demand forecasting, and risk management, by utilizing machine learning, statistical analysis, and real-time data. The research showcases various use cases, including in procurement, logistics, healthcare, and emergency services, highlighting positive impacts on productivity, cost savings, and service delivery. While challenges like quality data, infrastructure limitations and skill shortages persist, promising technologies such as AI, IoT and digital twins suggest a future of transformation for public sector supply chains.