Single Exponential Smoothing Forecast Method
This forecast method smooths the old average and the new average together rather than simply replacing the old average with the new average. It is the more appropriate forecast method when trend and seasonality are not significant factors. This forecast method still produces a flat-line forecast, but it shifts less erratically from month-to-month.
Single Exponential Smoothing requires at least one month of demand history.
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Each forecast method has constraints, called best fit rules that may make it ineligible for forecasting.
Refer to the EXP_SMOOTHING_HIST_AVG_BASE global setting for details on how to specify the initialization of the base forecast.
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