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How do I forecast intermittent or lumpy demand for slow-moving items?

Use methods designed for intermittent demand, such as Croston's method or its variants, which model how often demand occurs and how large it is when it does. Alternatively, aggregate to a longer period or product group, or manage slow items with min-max stock rules rather than precise forecasts.

Standard methods perform badly when most periods are zero. Spiky series also make MAPE useless, so evaluate with measures such as MAE, scaled errors or service-level outcomes.

Practical options:

The real goal is usually a stocking decision, so test the policy rather than only the forecast.

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Published by Zansa · Last updated 2026-11-06 · Category: Forecasting and data science