Forecast accuracy is an input to the decision—not the business outcome
A more accurate forecast creates value only when it changes inventory, capacity, service or financial decisions in a measurable way.
Forecast accuracy is often treated as the prize. It is better understood as an input to a broader planning decision.
Observation
Recent practitioner commentary challenges the tendency to optimize MAPE, WAPE or bias without connecting those measures to service, inventory and financial outcomes.
Operational implication
A forecast can become statistically better while the organization still makes poor replenishment, allocation or capacity decisions.
Decision architecture
Each forecast should be linked to the decision it supports, the owner of that decision and the cost of being wrong.
Data requirements
Forecast history, overrides, actual demand, service, stock, margin and working capital should share consistent product, location and time definitions.
What should remain lightweight
Model comparison and experimentation can remain in a controlled analytical layer.
What should be integrated
Approved metrics and decision thresholds should be embedded into Demand Planning, APS and BI workflows.
The best forecast is not the one with the lowest error. It is the one that improves the decision.
Source discussion: LinkedIn practitioner commentary.