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Statistical Forecasting in IFP

May 15, 2012

In IFP, statistical forecasting methods are available for the following types of analysis:

  • Fitting of mathematical trend models to a selected period of historical values  
  • Estimation of average seasonal patterns in any selected period of historical values  
  • Calculation of forecast values using projected trend values adjusted according to estimated seasonal factors

This approach to forecasting is most useful when reasonably stable patterns exist in actual values over a period of two or more years.

  • Forecasts may be created using any level of data, e.g. SKU (item code) details or brand totals
  • Forecasts created at group level are automatically split into corresponding item code details on a pro-rata basis
  • The base for these pro-rata allocations may be any set of base data, e.g. previously created forecasts or prior year actual data
  • Up to 10 years of forecasts may be created for each item
  • You may also specify the parameters of trend models using your own judgement and knowledge of market conditions

Visit our Support website for more information on Statistical Forecasting in IFP.