Build a demand sensing layer that adjusts the near-term forecast using real-time signals like orders, point-of-sale, weather, and market events.
## CONTEXT Traditional statistical forecasts are built on history, which makes them slow to react when something changes in the present. Demand sensing closes that gap by blending the baseline forecast with fresh, short-horizon signals: incoming orders, point-of-sale data, channel inventory, weather, promotions, and…
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