Does Your ML Forecast Actually Add Value? Run an FVA Analysis
by the U2xAI Team | 4 min read | May 25, 2026
ML forecasting pilots love to report accuracy. The better question is: accuracy compared to what? A naive statistical baseline is free; your ML pipeline is not.
Forecast Value Added (FVA) analysis compares every step of your forecasting process — statistical baseline, ML model, planner overrides, consensus meetings — against the naive forecast. Each step must earn its keep. In many organizations, the uncomfortable finding is that human overrides subtract value.
Run FVA before and after your ML pilot. If the model beats the baseline and the overrides don't, you have two findings — and the second one is worth more.
The AI for Supply Chain Toolkit includes FVA templates, ML forecasting approach comparisons and S&OP integration guides.