Forecast Bias

Updated September 2026Finance Software Glossary

Forecast bias is the tendency of a forecast to consistently overshoot or undershoot actual demand, measured as the average signed error over time. Positive bias means chronic over-forecasting, which builds excess inventory. Negative bias means under-forecasting, which causes stockouts. Unlike accuracy metrics such as MAPE, bias shows the direction of error, not just its size.

Some error is unavoidable in any forecast. Bias is different: it's systematic error in one direction, and it usually has an organizational cause. Sales teams under-forecast to beat their commitments, supply planners over-forecast to avoid stockouts and finance adjusts numbers to fit the budget.

Bias is measured as mean error or as a tracking signal over a rolling window. Because positive and negative errors cancel out, a forecast can show a reasonable MAPE while carrying heavy bias, so the two metrics are read together.

In software: planning tools such as Netstock, o9 and GMDH Streamline flag persistent bias by item and by forecast contributor, which helps teams find where human overrides consistently push the number in one direction.