What are the use cases of predictive analytics in supply chain?

Common use cases include demand forecasting, safety stock optimization, supplier risk management, logistics planning, and predictive disruption alerts. The value compounds when these use cases share the same underlying probabilistic model rather than running in isolation. A consistent view of demand uncertainty and lead time risk feeds safety stock sizing, replenishment proposals and supplier prioritization at the same time, which keeps decisions aligned across functions. In practice, the highest-return entry point is usually demand forecasting combined with dynamic safety stock, since those two together unlock most of the service level improvement and working capital reduction that justify the investment in the first place.