Identifying and Addressing Inefficiencies in Customer Complaints: A Process Mining Study with Generative AI

This research presents an analysis of the customer complaint management process at UWV using Process Mining techniques combined with Generative AI to identify and examine issues within the process. The data used is derived from event logs, which include Case ID, Activity, Timestamp, and Resource. This data is imported and analyzed using Disco software to create a Process Map that illustrates the sequence of activities and highlights issues such as irregular payments and inaccurate information. The incorporation of Generative AI enhances the analysis, making it faster and more accurate, uncovering complex relationships within the data, and providing recommendations for process improvements. The study suggests optimizing slow and complex steps by integrating automated tools for document verification and other processes to enhance efficiency and reduce processing time. (Abstract)