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Moving Average Forecast Method
This forecast method uses a weighted average of the last n slices, where n represents the number of slices .
For example, if n = 3 and H1, H2, and H3 are the historical values for the last slice, two slices back, and three slices back respectively, then the forecast is (H1 × 3 + H2 × 2 + H3 × 1) ÷ (1 + 2 + 3). Moving average forecast is useful when you need to consider recent events. For example, averaging the last three month's services or averaging the cost of the last ten services. The Moving Average forecast method requires a minimum of one month of demand history.
The moving average forecast method is a hybrid of the Average forecast method and the Weighted Average forecast method. What differentiates the Moving Average forecast method form the others is the introduction of a weight factor applied to the moving average. If the weight factor is 0, then the Moving Average forecast method functions exactly like the Average forecast method. If the weight factor is 1, then the Moving Average forecast method functions exactly like the Weighted Average forecast method.
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Each forecast method has constraints, called best fit rules that may make it ineligible for forecasting.
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