Forecasts Predict Demand; Demand Plans Translate It Into Action

Alexander Sandro Christesashvili highlights a recurring operating-model problem: treating a sales forecast as though it were already a demand plan.

A demand forecast estimates what the market may buy. It can combine historical patterns, pricing, promotions, pipeline information and commercial judgment. It remains an uncertain prediction rather than a commitment that operations can execute directly.

A demand plan translates that signal into a cross-functional view of what the organization intends to fulfil. It must account for inventory, capacity, lead times, product mix, supply risks and service priorities. Its purpose is to align expected demand with the company’s ability to serve customers profitably.

Confusing the two creates predictable organizational failures: sales may treat the plan as a target, operations may treat the forecast as executable, finance may lose confidence in the numbers, and customers experience the consequences through shortages or delayed fulfilment.

The distinction also matters for system design. Forecasting models and AI can improve the quality of the demand signal, but they do not independently resolve capacity constraints, inventory policies or commercial trade-offs. Those decisions require governed cross-functional planning, named owners and agreed override rules.

A practical planning process should therefore preserve separate versions for the statistical forecast, commercial adjustments and the approved demand plan. Changes should be documented, measured through forecast value added and reconciled with supply planning before the plan becomes an operational commitment.