Detecting a demand outlier

Simple forecasting methods remain useful when their fit and limits are understood. This primer explains detecting a demand outlier with a planner’s workflow in mind.

Practitioner lens

A forecast review of detecting a demand outlier should separate systematic bias from random error. The direction of misses can matter more to inventory decisions than a single accuracy score.

First experiment

Choose a horizon and aggregation level that match the decision, then evaluate a simple baseline first.

This is an original educational brief. It is a starting point for discussion, not a claim that one technique fits every supply chain.