
Predictive analytics refers to techniques that analyze data to estimate what is likely to happen in the future, often using statistical models and machine learning. In Supply Chain, the most useful version of predictive analytics goes beyond a single point estimate and provides a full distribution of likely outcomes per SKU and period. That probabilistic view supports better decisions on safety stock, replenishment and capacity because the planner can see the risk around the forecast, not just its central value. The methodology matters because Supply Chain decisions are inherently decisions under uncertainty, and ignoring that uncertainty is what produces both stockouts and excess inventory.