Enabling flexible task compositions, orders and granularities for knowledge-intensive business processes

Abstract

During the last decades, many approaches and tools were developed that enable a flexible enactment of repetitive business processes. By contrast, knowledge-intensive processes (KIPs) have not been effectively supported yet. This paper proposes a data-centric and goal-driven approach that enables flexible KIP enactment with dynamically evolving task structure and varying task granularity. The approach utilises artificial intelligence planning techniques in order to enable recommendations regarding the next tasks to be enacted. Furthermore, recommendations may be dynamically adapted when mismatches between the digital process and the real-world KIP emerge. Overall, the approach provides flexibility and guidance during KIP enactment.

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