ABSTRACT
Predictive analytics are increasingly important to supply chain management, making the process more accurate, reliable, and achievable at a reduced cost. To be at the top of the game as a supply chain manager, they need to understand and utilize advanced predictive analytics. As a large continuous process the supply chain has been extensively studied and is pretty well understood. It goes in well-recognized steps from: procurement, inbound logistics, parts inventory, manufacturing, finished goods inventory, fulfilment, and outbound logistics. From a predictive analytics perspective, about 90% of the problem is forecasting, starting with the demand forecast and letting that trickle back through the process to procurement and logistics planning. The role for predictive analytics is contributing the mathematics of optimization. This chapter provides list of activities that could be improved with the application of predictive analytics: demand analytics, finished inventory optimization, replenishment planning analytics, network planning and optimization, transportation analytics, and procurement analytics.
