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

where:

**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**%.