van der Aa, Han, Adela del-Río-Ortega, Manuel Resinas, Henrik Leopold, Antonio Ruiz-Cortés, Jan Mendling and Hajo A. Reijers (2016)

Narrowing the business-IT gap in process performance measurement

in: Nurcan, Selmin, Pnina Soffer, Marko Bajec and Johann Eder (ed.): Proceedings of the 28th International Conference on Advanced Information Systems Engineering (CAiSE): 9694, Springer, (2016), 543-557.

Copy reference link   DOI: 10.1007/978-3-319-39696-5_33

Abstract: 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.

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