What is demand sensing?

Demand sensing is a short-term supply chain capability that uses AI, machine learning, and real-time data signals to detect and respond to changes in demand as they happen. Unlike traditional planning approaches that update monthly or weekly based on historical averages, demand sensing continuously analyzes market signals — point-of-sale data, order patterns, inventory positions, and external factors — to adjust near-term forecasts at a granular level (typically SKU × location × day).

The goal is not to predict demand months out, but to sharpen the next 1–14 days of the plan so that replenishment, production, and allocation decisions reflect what is actually happening in the market. This makes it a powerful complement to the broader demand forecasting process. Flowlity's probabilistic engine is built for exactly this: it continuously recalibrates short-term forecasts at the SKU-location level, giving planners an always-current demand picture without manual rework.