Forecasting Methods

JD Edwards EnterpriseOne Forecast Management uses 12 methods for quantitative forecasting and indicates which method provides the best fit for the forecasting situation.

This section discusses:

• Method 1: Percent Over Last Year.

• Method 2: Calculated Percent Over Last Year.

• Method 3: Last Year to This Year.

• Method 4: Moving Average.

• Method 5: Linear Approximation.

• Method 6: Least Squares Regression.

• Method 7: Second Degree Approximation.

• Method 8: Flexible Method.

• Method 9: Weighted Moving Average.

• Method 10: Linear Smoothing.

• Method 11: Exponential Smoothing.

• Method 12: Exponential Smoothing with Trend and Seasonality.

Specify the method that you want to use in the processing options for the Forecast Generation program (R34650). Most of these methods provide limited control. For example, the weight placed on recent historical data or the date range of historical data that is used in the calculations can be specified by you.

Note: The examples in the guide indicate the calculation procedure for each of the available forecasting methods, given an identical set of historical data.

The method examples in the guide use part or all of these data sets, which is historical data from the past two years. The forecast projection goes into next year.

Past Year	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
1 (one year ago)	128	117	115	125	122	137	140	129	131	114	119	137
2 (two years ago)	125	123	115	137	122	130	141	128	118	123	139	133

This sales history data is stable with small seasonal increases in July and December. This pattern is characteristic of a mature product that might be approaching obsolescence.