Trend of Historic Averages Forecast Method

This forecast method creates top-down forecasts as part of the Budget Management module. The forecast method compares the trend of this year’s actuals against the trend of last year’s actuals. A forecast is created for each day in the time period for which you are generating the forecast. These daily forecasted values are then aggregated into weekly values that are displayed on the Worksheet. Note: the method calculates forecasts for each day in chronological order. The forecasted data from one day is used to calculate the forecasted data for a later day.

This forecast method uses this data:

Data Origin
sales forecasts Point-of-sale data daily data in the SO_RESULTS_SUMMARY table from LFSO.
AHR forecasts AHR historical weekly data in SO_RESULTS_SUMMARY that is automatically averaged to weekly values.
budget values Optional. An imported reference budget stored in the FCST_ITEM table.

This forecast method uses the Trend of Historic Averages algorithm to calculate the forecasted values. The algorithm:

  1. Calculates an average of last year’s similar days.
  2. Calculates an average of this year’s actual or forecasted similar days.
  3. Calculates the ratio of last year’s actual data to this year’s actual or forecasted data.
  4. Applies the ratio to the actuals of last year’s matching day.
  5. Aggregates daily values into the weekly values that are displayed on the Worksheet.

See Trend of Historic Averages Algorithm.

The application stores the forecasted values in the FCST_ITEM table in the database.