Impact of Data Aggregation on the Significance of Process Mining Results: An Experimental Evaluation
Kerstin Gerke
Abstract
Kerstin Gerke
Abstract
Today, many enterprises seek for efficient business process coordination and control to raise business process quality. Process mining technologies promise significant potentials in making business process knowledge explicit. However, it appears to be important to distinguish homogeneous process structures within a business process model to manage them accordingly. In this paper we present an experimental result of the classification of business processes according to their complexity. Furthermore, we evaluate if the homogeneity of the business processes correspond to the business process models derived with process mining.
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Today, many enterprises seek for efficient business process coordination and control to raise business process quality. Process mining technologies promise significant potentials in making business process knowledge explicit. However, it appears to be important to distinguish homogeneous process structures within a business process model to manage them accordingly. In this paper we present an experimental result of the classification of business processes according to their complexity. Furthermore, we evaluate if the homogeneity of the business processes correspond to the business process models derived with process mining.
Key concepts: Business process discovery, Process mining, Business process modeling, Artifact-centric business process model, Business process, Process modeling, Process (computing), Business process management