Forecast Engine Best Fit: Seasonal model selection

The model selection of the Best Fit forecasting process is altered to use the BATS algorithm’s significance test for seasonal model. The BATS significance test removes seasonal harmonics that are deemed not significant. If any harmonics remain, we can conclude that the seasonal model is present and now returns the best seasonal model.

The change to the best fit selection process is now applied to the execution of any forecast engine configuration with Default Algorithm = Best, including the default Demand Planning engine (Best ML Combination Months). The general result is anticipated that more seasonal models to be returned by these forecast engines. Several forecast results are now produced by these forecast engines than in the previous version and this is considered as a disruptive change.

Executing forecast engines where the Default Algorithm is a value other than Best Fit, remain unaffected by this change.

Note: By default, Forecast Engine configuration with Default Algorithm = Best is automatically applied the updated logic and no additional role or privilege is required to access this feature.