Demand Forecasting

What Is Demand Forecasting?

Demand forecasting is the process of predicting future customer demand for a product, using historical sales data, market trends, and other relevant signals, to guide inventory, production, and supply chain planning decisions.

How Does Demand Forecasting Work?

Forecasting methods range from simple historical averaging to sophisticated statistical and machine learning models that incorporate seasonality, promotions, pricing changes, and external factors like economic indicators or weather. Forecasts are typically generated at multiple levels, by SKU, by region, by time period, and are continuously updated as new sales data comes in.

Common Demand Forecasting Methods

• Qualitative methods: expert judgment, market research, sales team input
• Time series methods: analyzing historical demand patterns and trends
• Causal methods: modeling the relationship between demand and external drivers
• Machine learning methods: combining many data sources to improve accuracy

Why Demand Forecasting Matters

Forecast accuracy directly drives inventory decisions, over-forecasting leads to excess stock and waste, under-forecasting leads to stockouts and lost sales. Even modest improvements in forecast accuracy translate into meaningfully lower inventory costs and better service levels.