Example 1:

## Exponential Smoothing Forecasting — Example

Let’s consider **α=0.2** for the above-given data values so enter the value **0.8** in the Damping Factor box and again repeat the Exponential

The result is shown below:

## Exponential Smoothing Forecasting — Example #2

Let’s consider **α=0.8** for the above-given data values so enter the value **0.2** in the Damping Factor box and again repeat the Exponential Smoothing method.

The result is shown below:

Now, if we compare the results of all the above 3 Excel Exponential Smoothing examples, then we can come up with the below conclusion:

- The Alpha α value is smaller; the damping factor is higher. Resultant the more the peaks and valleys are smoothed out.
- The Alpha α value is higher; the damping factor is smaller. Resultant the smoothed values are closer to the actual data points.

**Things to** Remember

- The more value of the dumping factor smooths out the peak and valleys in the dataset.
- Excel Exponential Smoothing is a very flexible method to use and easy in the calculation.