Method and system for hierarchical forecasting

A system for generation of an automated forecast for a subject based on one or more input parameters, the subject associated with an end node of a categorical hierarchy, the system comprising at least one processing unit and a data storage, the at least one processing unit in communication with the data storage and configured to execute:

• an analysis module to receive historical data associated with the subject, and determine the sufficiency of the historical data associated with the subject based on a feasibility of building at least one subject machine learning model to generate a forecast with a predetermined level of accuracy using the historical data associated with the subject;
• and
• a forecasting module to:
• where there is sufficient historical data associated with the subject, build the at least one subject machine learning model trained using the historical data associated with the subject;
• where there is not sufficient historical data associated with the subject, build the at least one subject machine learning model trained using the historical data associated with the subject in combination with at least one of historical data and parameters of machine learning models associated with at least one ancestor node of the categorical hierarchy;
• receive the one or more input parameters;
• generate a forecast for the subject using the at least one machine learning model provided with the one or more input parameters;
• and
• output the forecast.