What Automated Planning can do for Business Process Management
This work proposes a novel integration of automated planning into BPM to enhance flexibility and reactivity, potentially benefiting organizations in dynamic domains, though it appears incremental as it applies existing AI methods to a new context.
The paper addresses the challenge of increasing automation in Business Process Management (BPM) to handle dynamic conditions like changing requirements and unpredictable environments, by leveraging automated planning techniques from AI to enable new levels of support across the BPM life cycle, with concrete examples of successful application.
Business Process Management (BPM) is a central element of today organizations. Despite over the years its main focus has been the support of processes in highly controlled domains, nowadays many domains of interest to the BPM community are characterized by ever-changing requirements, unpredictable environments and increasing amounts of data that influence the execution of process instances. Under such dynamic conditions, BPM systems must increase their level of automation to provide the reactivity and flexibility necessary for process management. On the other hand, the Artificial Intelligence (AI) community has concentrated its efforts on investigating dynamic domains that involve active control of computational entities and physical devices (e.g., robots, software agents, etc.). In this context, Automated Planning, which is one of the oldest areas in AI, is conceived as a model-based approach to synthesize autonomous behaviours in automated way from a model. In this paper, we discuss how automated planning techniques can be leveraged to enable new levels of automation and support for business processing, and we show some concrete examples of their successful application to the different stages of the BPM life cycle.