Narrowing the business-IT gap in process performance measurement


Van Der Aa, H., Del-Río-Ortega, A., Resinas, M., Leopold, H., Ruiz-Cortés, A., Mendling, J. & Reijers, H.A. (2016). Narrowing the business-IT gap in process performance measurement. In J. Eder, P. Soffer, S. Nurcan & M. Bajec (Eds.), Advanced Information Systems Engineering (pp. 543-557). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), No. 9694). Dordrecht: Springer. In Scopus Cited 2 times.

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To determine whether strategic goals are met, organizations must monitor how their business processes perform. Process Performance Indicators (PPIs) are used to specify relevant performance requirements. The formulation of PPIs is typically a managerial concern. Therefore, considerable effort has to be invested to relate PPIs, described by management, to the exact operational and technical characteristics of business processes. This work presents an approach to support this task, which would otherwise be a laborious and time-consuming endeavor. The presented approach can automatically establish links between PPIs, as formulated in natural language, with operational details, as described in process models. To do so, we employ machine learning and natural language processing techniques. A quantitative evaluation on the basis of a collection of 173 real-world PPIs demonstrates that the proposed approach works well.