Exponential Smoothing Forecasting – Examples

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.