Stefanie Rinderle-Ma

Nataliia Klievtsova, Juergen Mangler, Stefanie Rinderle-Ma

The artefact at the intersection of knowledge and process management is the process, which describes how enterprises are generating value. In knowledge management literature the relation of knowledge and processes is discussed, often leading to the definition of knowledge intensive processes, which entail a high level of human involvement. The process management community on the other hand focuses on the formalization of processes as models that can be executed, monitored, and improved. In this paper we explore the relationship of process resources such as data, objects, artefacts and humans, in order to come to more universal definition of knowledge intensive processes. For this purpose, we analyze different patterns that frequently occur in knowledge management processes, how they are represented in process models, and which types of knowledge are represented by them. The results comprise a categorization of process models into 6 categories that allow to easily see the knowledge intensity as well as a collection of common knowledge process patterns. The patterns were derived from a real-world knowledge gathering process, which includes a wide array of patterns and concepts detailed in this paper. We think that a holistic view on knowledge intensive processes, how to model, execute, monitor, and asses their impact, will speed up and improve the quality of digital transformation projects.

Stefanie Rinderle-Ma, Juergen Mangler, Johannes Loebbecke et al.

Agentic Business Process Management has gained momentum recently. The prospect is that the autonomy of AI agents, i.e., predominantly LLM-based agents, can be balanced with a certain level of robustness, tractability, and traceability through a combination with process technology. In this paper, we provide a classification framework for agentic orchestration options along properties such as task specificity, traceability and tractability, autonomy and reactivity, and correctness assurance and present qualitative decision criteria for realizations of different scenarios. We also provide metrics for the quantitative assessment of realization properties and show them through different agentic implementations of a predictive light sensing scenario. Altogether, this work aims at providing properties, criteria, and metrics for the design and implementation of agentic orchestrations and orchestration of agents.