What is demand forecasting?
Demand forecasting predicts future customer demand for products based on existing data and trends.
Sources used in demand forecasting include:
Historical sales data
Market trends
Seasonality
External market factors, such as competitor product launches, changing lifestyle tastes and economic indicators
Modern demand forecasting increasingly uses artificial intelligence (AI) and machine learning (ML) to review vast amounts of data and identify patterns and variables that humans are unable to spot.
What is the difference between demand forecasting and demand planning?
Demand forecasting and demand planning are often used interchangeably, but they are not the same.
Demand forecasting uses data and trends to predict future demand. Demand planning takes what the forecast predicts and determines which actions are needed to make sure demand is met. Both are needed for success.
Why is demand forecasting critical for order management?
Demand forecasting is a vital part of order management. It improves inventory planning and operational efficiency by:
Optimizing inventory investment with predicted demand quantities
Reducing stockouts, which prevents lost sales and increases customer satisfaction
Decreasing inventory holding costs by avoiding excess unsold inventory
Enabling supplier planning with advance purchase commitments
Supporting pricing strategies based on anticipated demand levels
Improving cash flow by aligning production with customer demand
Close the availability gap
How technology supports demand forecasting
A forecast only helps if it reaches the systems that allocate stock and promise delivery dates. An Order Management System (OMS) connects demand signals to live inventory, so plans can change when demand does.
An OMS supports demand forecasting by:
Using predictive analytics to identify sales trends and optimal inventory levels
Showing real-time inventory across warehouses, stores and suppliers, so forecasts are checked against what is actually available
Allocating inventory by channel, location or customer priority, based on expected demand
Responding quickly to shifting buying patterns, without waiting for a manual replan
Reporting on forecast accuracy and stockouts, so teams can refine their next plan