Process Improvement Copilot: bridging the gap between process inefficiencies and process improvement ideas

Business process improvement (BPI) is a crucial value-adding stage of business process management, as it introduces process changes to eliminate flaws and enhance performance. However, the inherent demands of BPI on domain knowledge, process expertise, time, and creativity in conjunction with a scarcity of adequate computational support, hinder organizations from fully leveraging BPI. Recognizing this gap, recent research calls for all types of contributions to process improvement and innovation systems (PIISs), from design knowledge to software artifacts. Leveraging the latest developments in generative artificial intelligence, increased availability of process execution data, and extensive collections of BPI knowledge, we propose a new technical approach to supporting the generation of process improvement ideas in BPI initiatives. To this end, we develop the Process Improvement Copilot – a retrieval-augmented generation (RAG)-enhanced PIIS that generates context-specific process improvement ideas and provides related justification, thereby facilitating their further evaluation and implementation. This research contributes a novel technical approach to automated BPI by exploring a RAG-based use case, designing a corresponding system architecture, developing a software prototype to demonstrate its technical feasibility, and evaluating the Process Improvement Copilot’s usefulness in a naturalistic workshop setting.