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.
Users can take advantage of the enhancements available in Forecast Pro TRAC Version 4.1. This new release includes further improvements to the grid view, and substantial improvements to the “hierarchy shuffling” functionality.
Forecast Pro TRAC allows you to view and work with your forecasts in different units of measure. When you set up your data for Forecast Pro TRAC, the units of measure for the input data are referred to as the default units. Unlike Forecast Pro Unlimited, which limits you to a single unit of measure, Forecast Pro TRAC lets you change the units you are working in.
Changing units isn’t just designed for reporting purposes. In Forecast Pro TRAC, as you change the working units you can continue to make adjustments and overrides to the forecast. As a result, the members of your team can view and work with the forecast in the units of measure that matches the way that they think about the business.
ABC classification, also known as Pareto analysis, is a useful method for classifying forecast items based on their relative importance to the organization. Many companies adopt different procedures for creating, reviewing and monitoring forecasts based upon an item’s classification. This enables the forecasting team to focus its efforts on those items which have the greatest impact to the organization.
Items are typically categorized as follows:
- A: important high volume items
- B: medium volume items
- C: slow moving items
Users can now enjoy the variety of improvements available in Forecast Pro Version 9. The features found in the new release–including an enhanced user interface, methodology improvements and the new Custom Component Model–make the software more powerful and easier to use.
Here’s an overview of what’s new in Forecast Pro Unlimited v9:
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.
Forecasters dealing with large, complex hierarchies face the challenge of managing thousands, or even tens of thousands, of forecasted items. In order to streamline navigation and to provide flexibility in reporting, Forecast Pro offers the “Hot List.” The Hot List is an easy-to-use utility for creating subsets of your data for viewing, applying modifiers and reporting. Taking advantage of the Hot List can save you time and effort.
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.
To meet its customers’ needs, Enesco Limited—a worldwide distributor of gifts, home décor and collectables—has the challenging task of creating accurate forecasts for a large number of SKUs. In this case study, you will learn how the UK-based company shortened its lead time for existing products, cut inventory and reduced product shortages by implementing Forecast Pro.