Andrea Burattin
Associate Professor
Technical University of Denmark
What is the Problem? Process Mining with a Control Theory Perspective
A. Burattin, E. Kindler
Abstract
Process mining aims to discover and monitor business processes from event data, traditionally evaluated using criteria such as simplicity, generalization, fitness, and precision. But, these criteria mostly assess how well the discovered model reflects the observed event data; they do not assess how well the discovered model serves its purpose. Looking at business process management and process mining from a control theory point of view, led us to including business goals and key performance indicators into the feedback loop; which gives feedback on how well a discovered process model serves its purpose. In this paper, we propose a framework for process mining and business process management with a control theory perspective. This framework helps us identifying additional quality dimensions on the level of business goals, such as stability, robustness and responsiveness. In addition, this framework identifies the sources of disturbances on a more detailed level than the traditional notions of noise and incompleteness in process mining. This perspective not only enriches process mining evaluation but also offers a deeper understanding of the discipline.
Paper Information and Files
In Mendling, J., Leemans, S., van Dongen, B.F., Reijers, H. (eds) Mining a Scientist's Process. LNCS, vol 16480.
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