BUP - Trend of Historic Averages Forecast Method

This forecast method creates bottom-up projections as part of the Budget Creation module. This 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: this method calculates forecasts for each day in chronological order so that the method can use forecasted data from one day to calculate forecasted data for a later day. The method uses this data:

Data Description
driver forecasts, which usually include sales forecasts Actuals, which can be based on any point-of-sale data daily data in the SO_RESULTS_SUMMARY table from LFSO.
AHR forecasts AHR historical weekly data in SO_RESULTS_SUMMARY table from LFSO.
staffing requirement hours LFSO workload generation data (staffing requirements, forecast, and driver distributions).
non-productive hours Estimated primarily from data in FCST_NONPROD_SMRY table, which originates in the Timesheet.
events LFSO event data for mandatory events.
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 projected 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.

This method stores the projected daily values for drivers in the FCST_DRIVER table and aggregates them in the FCST_ITEM table. The method stores the projected values for AHR (Average Hourly Rate) in the FCST_ITEM table.