Predicting downstream schedule effects of user task assignments

Abstract

Techniques for managing task assignments to workers in a work environment are disclosed. A system identifies one or more workers with qualifications that match recommended qualifications to perform a task in a work environment. The system applies a trained machine learning model to task performance data associated with the worker, such as a past history of tasks performed and statistics associated with the performance of the task. The machine learning model generates a prediction of downstream effects associated with assigning the task to the user. The downstream effects include delays and performance improvements on subsequent tasks performed by the worker, as well as effects on tasks performed by other workers, at work centers in the work environment.