Recent Advances in Data-Driven Business Process Management

June 03, 2024 · The Cartographer · 🏛 arXiv.org

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"Title-pattern auto-detect: Recent Advances in Data-Driven Business Process Management"

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Authors Lars Ackermann, Martin Käppel, Laura Marcus, Linda Moder, Sebastian Dunzer, Markus Hornsteiner, Annina Liessmann, Yorck Zisgen, Philip Empl, Lukas-Valentin Herm, Nicolas Neis, Julian Neuberger, Leo Poss, Myriam Schaschek, Sven Weinzierl, Niklas Wördehoff, Stefan Jablonski, Agnes Koschmider, Wolfgang Kratsch, Martin Matzner, Stefanie Rinderle-Ma, Maximilian Röglinger, Stefan Schönig, Axel Winkelmann arXiv ID 2406.01786 Category cs.DB: Databases Cross-listed cs.AI Citations 5 Venue arXiv.org Last Checked 11 days ago

Abstract

The rapid development of cutting-edge technologies, the increasing volume of data and also the availability and processability of new types of data sources has led to a paradigm shift in data-based management and decision-making. Since business processes are at the core of organizational work, these developments heavily impact BPM as a crucial success factor for organizations. In view of this emerging potential, data-driven business process management has become a relevant and vibrant research area. Given the complexity and interdisciplinarity of the research field, this position paper therefore presents research insights regarding data-driven BPM.