FORECAST REVIEW · PRACTICAL GUIDE

Forecast Error & Bias Calculator

Understand MAE, WAPE and signed forecast bias with a small worked example.

What this tool helps you examine

Compare actual demand with a forecast over matching periods. MAE describes typical absolute error; WAPE relates total absolute error to total actual demand; signed bias shows whether forecasts tend to run high or low.

Starter formula: MAE = mean(|forecast − actual|) · WAPE = sum(|forecast − actual|) ÷ sum(actual) · signed bias = mean(forecast − actual)

Worked example

Actual: 100, 110, 90. Forecast: 95, 108, 100. Errors are −5, −2, +10. MAE = 17 ÷ 3 ≈ 5.7 units. Bias = +1 unit per period, indicating a slight average over-forecast.

Limits to keep in view

These calculations are deliberately small and transparent. They do not include every product rule, location, calendar, lead-time distribution, lot-sizing policy, resource, service target or commercial constraint. Use the result as a learning prompt, then validate it with the relevant data and planning process.

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