Adaptive Exponential Smoothing

Adaptive Exponential Smoothing is similar to basic exponential smoothing where the latest base demand value is weighted with a smoothing constant. In adaptive exponential smoothing, the smoothing constant is calculated every time a new forecast is made.

The smoothing constant is recalculated using this equation:

In order to control and follow up forecast precision, two types of measurements are used, Mean Absolute Deviation (MAD) and Mean Error (Forecast error, AVER). These measure the deviation between forecast and actual demand. You can calculate the Mean Error and MAD in three ways:

Method 3: Mean Demand deviation

Factor	Description
	Mean absolute deviation for period (i)
α	Smoothing constant for exponential smoothing in period (i)
	The absolute amount of a difference (without minus sign)
	Base demand during period (i)
	Base forecast for period (i)
	Average demand for (n) periods
i	Period number
n	Number of periods included in calculating the mean

Note: Alpha is adaptive and calculated automatically from the deviation (CDev).