Forecast Bias Calculator
Aggregate forecast bias shows the direction and percentage size of total forecast error compared with actual outcomes. Positive bias here means over-forecasting.
How to use this calculator
- Enter summed actuals and forecasts for the same items and interval.
- Check that all inputs use the same units, period and population scope.
- Change one assumption at a time when comparing scenarios.
Formula used by forecast bias percent calculator
Bias % = (total forecast − total actual) ÷ total actual × 100%.
- Bias % = (total forecast − total actual) ÷ total actual × 100%.
- Aggregate totals can hide offsetting errors between items or periods; examine segment-level bias and absolute error too.
- The tool validates inputs and rounds displayed figures for readability; it does not validate assumptions against external records.
Worked examples
Worked example
Forecast demand is 10,800 while actual demand is 10,000.
(10,800 − 10,000) ÷ 10,000 × 100 = 8%.
The forecast overstates actuals by 8%.
Understanding the result
Aggregate forecast bias shows the direction and percentage size of total forecast error compared with actual outcomes. Positive bias here means over-forecasting.
Aggregate totals can hide offsetting errors between items or periods; examine segment-level bias and absolute error too.
Important notes
Aggregate totals can hide offsetting errors between items or periods; examine segment-level bias and absolute error too.
Treat the result as an estimate from the entered assumptions. For commercial, statistical, engineering or health-related decisions, verify relevant specifications and professional guidance.
Frequently asked questions
Is positive bias good?
It means forecasts were above actuals using this sign convention; whether that is desirable depends on the costs of over- and under-forecasting.
Is bias the same as MAPE?
No. Bias keeps direction, while MAPE measures average absolute percentage error.
How should I interpret this result?
Aggregate totals can hide offsetting errors between items or periods; examine segment-level bias and absolute error too.
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Related explanations
Learn the method behind the number or compare the terminology before using the calculator.
- How to Calculate Percent Error — Learn the percent error formula and how to compare an experimental value with a reference or accepted value.
- Percentage Change vs Percentage Difference — Understand the difference between percentage change and percentage difference, including when each formula is appropriate.
- Percent Difference — Understand percent difference, when it is appropriate, and how it differs from percentage change and percent error.
This page provides a calculation tool plus explanatory information so you can understand what the result means and when the underlying method may not fit your situation.