Sometimes making changes to near-term forecasts can be an expensive proposition. Last minute changes often significantly increase production and procurement costs, decrease profitability, and negatively impact other aspects of the business. To protect against these effects, many companies establish “time fences” to prohibit changes to the forecast over a defined short-term horizon. This edition of Tips & Tricks details how to set time fences in Forecast Pro TRAC to prevent new statistical forecasts from being generated and/or new forecast overrides from being applied within the fenced horizon.
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.
In Forecast Pro TRAC, you have the ability to import externally-generated forecasts into the override grid view. We can choose which of these forecasts we want to use as our “baseline” forecast. This can be done either on an item-by-item basis or for groups of items. If we have specified a baseline forecast that is different than the statistical forecast, we can also use the tracking reports in Forecast Pro to track accuracy for our baseline forecasts separately from our statistical and/or our adjusted forecasts.
It is easy to understand why most Forecast Pro users rely heavily on the software’s expert selection mode to generate their forecasts–expert selection automatically analyzes their data, selects the appropriate forecasting techniques and generates the forecasts. This article discusses how the length of a data set can influence your decision to choose expert selection or an alternative approach for forecasting your data.
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.
In Forecast Pro TRAC’s Override View, users have the ability to display five types of information: historical data; forecasts; overrides; external data & calculated rows. At times, when working with your forecasts, visibility to other information such as alternative forecasts generated outside of Forecast Pro or non-forecast data such as current orders or inventory levels can greatly aid the forecasting process.
Forecast Pro TRAC users have the ability to import external data and alternative forecasts into the Forecast Override View and to create customized, calculated rows. This installment of Tips and Tricks includes several examples of how to use this functionality and illustrates the value that this new capability brings to the forecasting process.
If you are forecasting a time series that contains an outlier, there is a danger that the outlier could have a significant impact on the forecast. One solution to this problem is to screen the historical data for outliers and replace them with more typical values prior to generating the forecasts. This process is referred to as outlier detection and correction.
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.
Over the past couple of decades, business forecasters have come to recognize the importance of collaboration for creating more accurate forecasts; however, in business forecasting, the term “collaboration” doesn’t necessarily have only one definition.
Many forecasting processes can be described as “collaborative.” Some organizations utilize highly-formalized processes (e.g., S&OP, IBP) which involve defined roles, specific data elements, and/or structured meeting schedules. Others deploy less-formalized and more loosely-defined processes which involve creating an initial forecast and allowing various stakeholders to review and even modify (e.g., adjust) the initial forecast.
Forecast Pro TRAC provides a wide array of exception reports, including reports which monitor your archived forecasts (i.e., previously created and saved forecasts) and reports which monitor your current forecasts (i.e., the forecasts you are working on but haven’t yet finalized). Exception reports enable you to quickly find cases where your forecast error or some other performance metric has fallen outside of an acceptable range. In this article we explain in detail how to create the Waterfall Exception Report to monitor forecast accuracy.