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MFG/PRO 9.0 User Guide Volume 3: Manufacturing - QAD.com

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Forecast Methods<br />

FORECASTING/MASTER SCHEDULE PLANNING 211<br />

Forecast methods are identified by two-digit method numbers. Table 11.2<br />

lists the forecast method numbers available in <strong>MFG</strong>/<strong>PRO</strong>.<br />

Method Number Usage<br />

00 Indicates that a forecast detail record was not<br />

generated by the system, but was created manually<br />

using the copy programs or using CIM interface.<br />

01–06 <strong>MFG</strong>/<strong>PRO</strong> predefined forecast methods.<br />

07–50 Reserved for <strong>QAD</strong> usage.<br />

51–99 Use these numbers to identify your own<br />

forecasting methods.<br />

There are six predefined forecast methods, described in Table 11.3. You<br />

can create additional methods using <strong>User</strong> Forecast Method Maintenance<br />

(22.7.17).<br />

Method # Type Description<br />

01 Best Fit Uses all predefined methods—02 through 06—<br />

and selects the results with the least mean<br />

absolute deviation. This is the default forecast<br />

method.<br />

02 Double Moving<br />

Average<br />

03 Double<br />

Exponential<br />

Smoothing<br />

04 Winter’s Linear<br />

Exponential<br />

Smoothing<br />

The simplest of the forecasting techniques. It uses a<br />

set of simple moving averages based on historical<br />

data and then <strong>com</strong>putes another set of moving<br />

averages based on the first set. The moving averages<br />

are based on four months of data. This method<br />

produces a forecast that lags behind trend effects.<br />

The most popular of the forecast techniques. It is<br />

similar to Double Moving Average, except that it<br />

uses the alpha factor to weigh the most recent sales<br />

data more heavily than the older sales data. This<br />

method produces a forecast that lags behind trends<br />

effects.<br />

Produces results similar to Double Exponential<br />

Smoothing, but incorporates a seasonal/trend<br />

adjustment factor. This method can be used to<br />

forecast based on sales history containing both trends<br />

and seasonal patterns. Uses the trend and alpha<br />

factors. Requires two years of history.<br />

Table 11.2<br />

Method Numbers<br />

Ï See page 213.<br />

Table 11.3<br />

Predefined Forecast<br />

Methods

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