Driving Efficient Warehouse Optimization Through Structured Processes and User Adoption

Author

Angeline C. Harris, Kennesaw State UniversityFollow
Gaby R. Benisek, Kennesaw State UniversityFollow
Liz Tingley, Kennesaw State UniversityFollow
Lia Urena, Kennesaw State UniversityFollow

Date of Submission

Fall 12-8-2025

Project Type

Senior Design

Major

Industrial and Systems Engineering

Degree Name

Bachelor of Science in Industrial and Systems Engineering

Department

Department of Industrial and Systems Engineering

Committee Chair/First Advisor

Dr. Luisa Valentina Nino de Valladares

Abstract

AutoScheduler, the company that designs unique warehousing solutions for its clients through its optimization software, was struggling to make its software user friendly to fulfill warehousing tasks. With minimal training documentation in place for teaching clients functions in the software, the clients were often left unmotivated to use the software in the way that was intended. This was creating conflict between AutoScheduler and the clients, as there was often confusion for the clients regarding why they were not acquiring the profits they were promised. To reduce this client reluctance to use the optimization software, the objective of this project was to develop reference documents to explain how to use certain functions in the software quickly and to develop a sounder training program for AutoScheduler employees to communicate the most important software features to clients in a more structured way. Another objective was to develop a better-defined software implementation phased approach that the AutoScheduler employees could use to guide the clients from the data collection phase to the software setup and usage phase. This would assist in communicating better to the clients the overall purpose of the software and help them understand how their warehousing data is being used to develop a plan. Finally, there was an objective to establish a defense for AutoScheduler for observing client usage of the software, which would be models that reveal how often clients are navigating the software and their degree of adherence to the plans generated for them.