Data-Centric Support for Dynamic Processes

Manfred Reichert, Shazia Sadiq, Barbara Weber

Abstract: From its roots in business process re-engineering, to current disruptions resulting from changes in processes and practices due to increasing adoption of Artificial Intelligence tools and systems, research on change management has been consistently prominent in the field of Business Process Management. In this paper, we summarize the foundational contributions made on the support of dynamic processes, covering ad-hoc changes, schema-level changes & instance migration, and approaches to achieve flexibility by design through loosely specified process schemes. Traditional activity-centric approaches, while effective for structured workflows, fall short in addressing the complexities of knowledge-intensive and increasingly automatized business environments. We outline the need for a paradigm shift to data- and object-centric process models, where business objects and their lifecycles drive process execution and coordination. We illustrate that this shift becomes necessary to tackle the challenges emerging from the convergence of AI and automation, and we highlight that effective change management must integrate data skills and human-in-the-loop support to ensure adaptability, safety, and continuous improvement. This paper positions data-centric BPM as essential for resilient and intelligent process management in dynamic organizational contexts.

External IDs:doi:10.1007/978-3-032-17618-9_10