Consider the following situation. We work for the 123 Bakery. We have defined an extremely simple forecasting process where the forecasts are generated and adjusted by one individual. All adjustments are made to the SKU-level data in base units and in the base hierarchy. The projects are saved with the statistical forecast unlocked (i.e., we never change states).
It is June 2023, and we have monthly historic demand data that starts in 1/2018 and ends in 5/2023. Our first forecast period will be June 2023. We use Forecast Pro to create our forecasts and then we save a project named Tutorial – Updating – June 2023.
Now imagine that a month passes by. We now have our June sales figures, and we update our historic data files.
This is accomplished externally to Forecast Pro. It may entail running a data extraction routine to generate the new files, updating your spreadsheets by hand, or some other process to update the historical data files.