A business scenario that uses a machine learning-based application to consider different attributes, such as part, location, and demand attributes, to learn about historical forecast tracking signals. Using the gathered information, the application can predict the future tracking signal and provide the computer-based intelligence recommendations on the combination of attributes that cause SKUs to over forecast or under forecast.