Exponential Smoothing in Excel


Exponential Smoothing is used to forecast the business volume for taking appropriate decisions. This is a way of “Smoothing” out the data by eliminating much of random effects. The idea behind Exponential Smoothing is just to get a more realistic picture of the business by using the Microsoft Excel 2010 and 2013.

To access this tool, click on Data Tab, click on Data Analysis in the Analysis group. If the Data Analysis command is not available then you need to load the Analysis Toolpak.

To load and activate the Analysis Toolpak follow below mentioned steps:-

  • Click the File Tab, Click options and click on Add INS Category.


  • In the Manage box, select the Analysis Toolpak and then click on the Go button.


  • In the Add Ins dialog box, select the Analysis Toolpak check box and then click Ok.
  • If Analysis Toolpak is not listed in the Add Ins available box, click Browse to locate it.

Let’s come back to the topic, to prepare the forecasting of data.

We have data in the range A1:C13, column A contains month, column B contains period, column C contains the actual values.

This example teaches you how to apply exponential smoothing to a time series in excel.

To use the Exponential Smoothing, follow the below given steps:-

  • Go to Data Tab.
  • Click on Data Analysis in the Analyses group.


  • Data Analysis dialog box will appear.


  • From the Analysis tool drop down menu, Exponential Smoothing and click on ok.
  • An Exponential Smoothing dialog box will appear.
  • Click on Input range, select the range C1:C13.
  • Write 0.9 in Damping Factor.
  • Select the output range where you want to put the data.
  • If you have require the chart, then tick on Chart Output.



Explanation: because we set alpha to 0.1, the previous data point is given a relatively small weight while the previous smoothed value is given a large weight (i.e. 0.9).

The graph shows an increasing trend. Excel cannot calculate the smoothed value for the first data point because there is no previous data point. The smoothed value of the second data point equals the previous data point.


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