Explanatory variable files are used to import explanatory variables (i.e., independent variables) that you wish to include in a dynamic regression model.
Forecast Pro allows you to specify two types of explanatory variables—global and item-specific. A global explanatory variable consists of a single time series (set of values) which can be included in a dynamic regression model for any item on the Navigator. An item-specific explanatory variable consists of a set of time series each of which is associated to a specific item on the Navigator.
To illustrate the difference, consider a variable like holidays which will likely be the same for all items within a hierarchy and therefore should be defined as a global variable. Contrast holidays with a variable like price, which will likely take on different values for different items and therefore should be defined as an item-specific variable. In this context “items” is being used to include both end items and aggregate levels in the hierarchy.
Explanatory variables must include values for the historic period. Ideally, you would also include forecast values for your explanatory variable, but you are not required to do so. If an explanatory variable does not have values provided for the complete forecast period, you can use the “automatically extend” option to instruct Forecast Pro to forecast explanatory variables (using expert selection) where necessary.