← Back to glossary Category: Operațional Demand Forecasting Quick answer: Estimating future demand per product based on sales history, seasonality and external factors. Key takeawaysMoving averages and exponential smoothing (baseline)Seasonal models (Holt-Winters)ML time-series models + external factors What demand forecasting is Demand forecasting estimates how many units will sell per SKU in a future period, using history, seasonality, promotions, trends and events. It is the basis of stock and replenishment planning. Why it matters to the board An accurate forecast simultaneously reduces dead stock and stockouts — the two opposing costs of inventory. Every point of accuracy gained frees up working capital. Methods Moving averages and exponential smoothing (baseline) Seasonal models (Holt-Winters) ML time-series models + external factors How Azuvio helps Azuvio consolidates real sales from ERP, marketplaces and the B2B portal and generates SKU-level forecasts that directly feed the reorder point and order proposals. Frequently askedWhat accuracy is realistic?It depends on the XYZ class. For stable items (X), 85-95% is realistic; for chaotic ones (Z), the forecast matters less than a correct buffer stock.Do I need AI for forecasting?Not necessarily. Statistical models cover most cases; AI adds value at high volumes and complex patterns (see AI demand forecasting). Where Azuvio fitsSoftware OMSConectori ERPSoftware WMS Related termsReorder Point (ROP) — The stock level at which a new order must be placed to avoid a stockout before goods arrive.Safety stock — Extra buffer inventory held to prevent stockouts caused by demand or supply variability.XYZ Analysis — Classifying products by demand variability (predictability): X = stable, Y = variable, Z = erratic.AI Demand Forecasting — Demand forecasting with machine-learning models that learn patterns from history and external factors, at SKU level. Last updated: 2026-07-06