Forecast Error Calculator

Measure forecast accuracy using absolute, squared and percentage error metrics.

About Forecast Error Calculator

MAE and RMSE both measure magnitude but RMSE punishes large misses harder. Bias is the signed average and is the only one of the three that detects systematic error. A forecast can have low MAE and severe bias, which matters enormously for inventory where persistent under-forecasting causes stockouts.

Formula

Forecast Error

MAE averages absolute errors; RMSE averages squared errors; bias averages signed errors

RMSE: Penalises large errors more heavily than MAE
bias: Signed average, which reveals systematic over or under-forecasting

Worked example

With the default values below, Forecast Error Calculator returns Mean Absolute Error of 8.33333. Change any input above and every figure here is recalculated in your browser.

Inputs used

Actual period 1: 100
Forecast period 1: 110
Actual period 2: 120
Forecast period 2: 115
Actual period 3: 90
Forecast period 3: 100

Results

Mean Absolute Error: 8.33333
Root Mean Squared Error: 8.66025
Mean Absolute Percentage Error: 8.4259%
Forecast Bias: -5.00000
Bias Direction: Forecasts are consistently too high

Step by step

1Values used
2Forecast Error
3Mean Absolute Error= 8.33333
4Root Mean Squared Error= 8.66025
5Mean Absolute Percentage Error= 8.4259
6Forecast Bias= -5.00000
7Bias Direction= Forecasts are consistently too high

Assumptions and limits

The result is derived only from the 6 inputs listed above. Anything not among them is not part of the calculation.
In particular, this calculator does not take inflation, tax or fees or charges into account.
Figures are rounded for display to 5 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

How is Forecast Error calculated?

MAE averages absolute errors; RMSE averages squared errors; bias averages signed errors MAE and RMSE both measure magnitude but RMSE punishes large misses harder. Bias is the signed average and is the only one of the three that detects systematic error.

Why does Forecast Error matter?

A forecast can have low MAE and severe bias, which matters enormously for inventory where persistent under-forecasting causes stockouts.

What values do I need to enter?

This calculator takes 6 inputs: Actual period 1, Forecast period 1, Actual period 2, Forecast period 2, Actual period 3, Forecast period 3. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.