TUM and ATOSS Students Conduct Research: AI Deployment in Workforce Management
The TUM.ai student initiative of the Technical University of Munich (TUM), a group of students specializing in the development of AI solutions and the promotion of AI technologies, and Atoss Software conducted a joint project on AI-based workforce demand forecasting in retail as part of the Industry Project Phase (4.0). The goal of the collaboration was to engage students in the practical use of AI technologies while exploring the use of artificial intelligence (AI) in workforce management.
Senior Director Research, ATOSS, TUM alumnus and leader of the joint project.
Answers were sought to the following question: how can retailers deploy the optimal number of associates on the sales floor at all times? The focus of the research project was to use AI to develop a sales associate schedule that ensures the highest quality of service while optimizing labor costs: customers should feel that they are receiving the best possible service. Employees should be deployed as efficiently and productively as possible, with more personal responsibility and more flexible working hours.
The students' task was to create an AI-based forecast for staffing the stores of a sample retail customer. Based on customer volume data provided by Atoss, the students' AI model, with support from the Atoss development team, calculated the most accurate staffing demand forecast and staffing plan for the near future. Together with the student initiative, Atoss wanted to further improve this application of machine learning.
