DemandPlanning

Demand planning is the process of forecasting customer demand for products or services to guide supply chain decisions. It combines historical sales data, market intelligence, promotions, and production constraints to generate a shared view of future demand that informs procurement, manufacturing, and distribution planning.

The process typically includes data collection, statistical forecasting, collaborative consensus, and scenario analysis. Teams from sales, marketing, operations, and finance work together to reconcile demand with supply, creating a forecast by product, channel, and time period. The output is used to determine inventory targets, production schedules, and capacity requirements, often within a sales and operations planning framework.

Forecasting methods range from quantitative time series models such as exponential smoothing and ARIMA to qualitative approaches like market research and expert opinion. Inputs include historical demand, promotions, pricing, seasonality, new product introductions, competitive actions, and external indicators. Outputs may cover forecast accuracy metrics, exception reports, and recommended policies for safety stock and replenishment.

Effective demand planning supports service levels and working capital management by reducing stockouts and excess inventory. Challenges include data quality and integration, forecast bias, organizational silos, seasonality effects, and rapid demand changes. Performance is tracked with metrics such as forecast accuracy (MAPE or sMAPE), bias, inventory turnover, fill rate, and service level. Technology used includes ERP and advanced planning systems, demand sensing tools, and analytics to support collaboration and scenario planning.