Dean School of Computer Science,
University of St. Gallen
Business processes are at the core of digital transformation and range from highly repeatable and predictable to highly variable and little predictable. While classical Business Process Management technologies target repeatable and predictable business processes, Case Management Systems (with declarative process models at their core) are more tailored towards knowledge-intensive business processes that are more variable and often less predictable. While declarative process models offer a high degree of flexibility to their users during run-time, the choice of how to execute a declarative model can be challenging for its users. This complexity further increases for business processes that comprise temporal or cross-instance constraints, require an efficient management of shared resources, and need to optimize objective functions in an uncertain evolving environment. This might result into sub-optimal enactment plans and thus requires advanced operational support. Automatically generated optimized enactment plans can be used to guide users during run-time. To deal with uncertainty plans can be adapted during run-time if required taking run-time information into account.