The symmetric mean absolute percentage error (SMAPE) is used to measure the predictive accuracy of models. It is calculated as:
SMAPE = (1/n) * Σ(|forecast – actual| / ((|actual| + |forecast|)/2) * 100
- Σ – a symbol that means “sum”
- n – sample size
- actual – the actual data value
- forecast – the forecasted data value
The smaller the value for SMAPE, the better the predictive accuracy of a given model.
The following step-by-step example explains how to calculate SMAPE in Excel.
Step 1: Enter the Data
First, we’ll enter some fake data for the actual sales and the forecasted sales during 12 consecutive sales periods for some company:
Step 2: Calculate the SMAPE Differences
Next, we’ll calculate the SMAPE difference for each sales period using the following formula:
Step 3: Calculate SMAPE
Lastly, we’ll use the following formula to calculate SMAPE:
The SMAPE for this particular model turns out to be 9.89%.
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