Detecting and reacting to unseen long term event in demand forecasting

Abstract

A system and method are disclosed for detecting and reacting to unseen events in demand forecasting, comprising preparing, by a server, data from a supply chain domain and entity to predict a demand, selecting features in the prepared data and training a machine learning model, generating a demand prediction with residual time series corrections, using the machine learning model, monitoring the demand prediction and data from the supply chain domain and entity to detect an occurrence of an unseen event; and in response to detecting the occurrence of the unseen event, revising the demand prediction by updating the machine learning model. The system and method further comprises detecting that a greater than threshold increase has occurred in a prediction of a target variable, and revising the demand prediction further comprises performing a second residual time series corrections that incorporates time information associated with the unseen event.