The educational Webinar How to Leverage Forecasting and a Demand Control Process to Improve Customer Service presented by Business Forecast Systems and Oliver Wight is now available to view on demand.
In this installment of Tips & Tricks we detail one of the many reports available in Forecast Pro TRAC–the Actual vs. Archive report. This important report allows you to track your forecasts’ accuracy by comparing them to what actually occurred. Tracking accuracy provides several benefits such as: information that enables you to improve forecast performance; insight into expected performance; and the ability to spot problems early on.
Many Forecast Pro users rely on the software’s expert selection capability to choose the appropriate forecasting techniques and generate the forecasts, and then “tweak” the forecasts as needed. One way to adjust a forecast is to change the forecasting method used; when you do this, a “forecast modifier” appears next to the item in the Navigator to record and maintain your selection. A second option for adjusting the statistical forecast is to apply overrides.
In this edition of Tips and Tricks, we explain how to import overrides and modifiers into Forecast Pro directly from Excel which can save substantial time if you work with large data sets.
Generating the most accurate forecast often involves creating a statistical forecast and then judgmentally changing the statistical forecast to account for market conditions which aren’t fully reflected in the historical data. Some common examples include: promotions; pipeline fills; large one-time orders; and product introductions or phase outs.
Forecast Pro TRAC accommodates judgmental changes to the statistical forecasts it generates via the Override Forecasts screen. This spreadsheet-style display, as shown in the screenshot below, contains five rows labeled Statistical, Override 1, Override 2, Override 3 and Forecast.
The majority of Forecast Pro users rely on Expert Selection, the software’s built-in system which automatically creates forecasts. This approach works quite well in most cases; however, you must keep in mind that Expert Selection views your data as a series of numbers and takes a purely statistical approach to generating the forecasts. At times your knowledge of your products and future events may lead you to either adjust the Expert Selection forecast judgmentally or reject it completely and use an alternative forecasting method. Let’s examine several cases where overriding the Expert Selection forecast should be considered.