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Narrowing the Business-IT Gap in Process Performance Measurement

  • Han van der AaEmail author
  • Adela del-Río-Ortega
  • Manuel Resinas
  • Henrik Leopold
  • Antonio Ruiz-Cortés
  • Jan Mendling
  • Hajo A. Reijers
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9694)

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.

Keywords

Performance measurement Process performance indicators Model alignment Natural language processing 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Han van der Aa
    • 1
    Email author
  • Adela del-Río-Ortega
    • 2
  • Manuel Resinas
    • 2
  • Henrik Leopold
    • 1
  • Antonio Ruiz-Cortés
    • 2
  • Jan Mendling
    • 3
  • Hajo A. Reijers
    • 1
    • 4
  1. 1.Department of Computer SciencesVU University AmsterdamAmsterdamThe Netherlands
  2. 2.Dpto. de Lenguajes y Sistemas InformticosUniversity of SevilleSevilleSpain
  3. 3.Institute for Information BusinessWUViennaAustria
  4. 4.Department of Mathematics and Computer ScienceEindhoven University of TechnologyEindhovenThe Netherlands

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