Demand forecasting basics: clean history, simple methods and forecast error
Prepare demand history (stock-outs, promotions, one-offs), make simple forecasts (naive, seasonal naive, moving and weighted averages), measure error with MAE, MAPE and bias, and decide when judgment and overrides add value.
- Level
- Intermediate
- Length
- About 55 minutes
- Contents
- 3 lessons · 1 video · final exam
- Status
- Published · updated 1 Oct 2026
Skills you'll practise
- Explain why shipments can understate demand and correct or flag history before forecasting
- Calculate naive, moving-average and weighted moving-average forecasts and explain why averages lag a trend
- Calculate forecast error, mean absolute error, MAPE and bias with a stated sign convention, and say when MAPE misleads
- Compare forecast versions (naive, statistical, overridden) on the same error measure and recommend which to use
Course outline
- 1.Demand forecasting basicsVideo · 3 min
- 2.Demand history: what the numbers really meanLesson · 17 min
- 3.Simple methods that work surprisingly oftenLesson · 18 min
- 4.Measuring error and adding judgmentLesson · 20 min
- 5.Demand forecasting basics: clean history, simple methods and forecast error: knowledge checkKnowledge check · 17 questions
- 6.The promotion that never soldScenario
- 7.Final exam7 questions · passing it completes the course, so people who already know the material can test out
Sources it draws on
The lessons and questions are written from these references, so learners can go back to the original.
- Nau, R. (Duke University): Averaging and smoothing models (moving averages lag turning points; random walk)
- Mean absolute percentage error: definition and known limitations (zero actuals, asymmetry)
- ASCM (APICS) supply chain dictionary and body of knowledge: scheduling, sequencing rules, forecasting, time fences
- General operations and warehouse practice
See it with your own jobs and topics
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