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What is forecast value added and how do I measure it?
Forecast value added (FVA) measures whether each step in a forecasting process improves accuracy compared with the previous step or a naive benchmark. You compare the error of, for example, the statistical forecast, the manager-adjusted forecast and the naive forecast. If a step makes things worse, it adds no value.
The idea exposes wasted effort. Manual overrides sometimes improve forecasts when they include real market knowledge, but often add bias, for example through optimism.
To measure it:
- Save forecasts at each stage before actuals are known.
- Calculate the same error metric for each stage.
- Compare across enough periods to be meaningful.
Use the results to decide where human input is worth it, such as promotions and new launches, and where to leave the numbers alone.
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