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Enabling Probabilistic Process Monitoring in Non-automated Environments

  • Conference paper
Enterprise, Business-Process and Information Systems Modeling (BPMDS 2012, EMMSAD 2012)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 113))

Abstract

Business processes are crucial for every organisation as they represent the core value generating processes. Managing business processes is important to be efficient and to compete with a globalized market. Business process monitoring is an essential means to understand and to improve working procedures. It helps detecting deviations from planned procedures and brings transparency into the state and progress of running process instances. However, without automated execution of business processes via a workflow engine, the absence of execution information hampers monitoring. Often, the automated execution of business processes is neither feasible nor desirable. However, a few monitoring points can be used, when process participants interact with IT-systems.

In this paper, we propose a novel approach to business process monitoring using probabilistic estimations to fill information for missing monitoring points. The applicability of the approach is evaluated with a case study in a German university hospital.

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Author information

Authors and Affiliations

  1. Business Process Technology Group, Hasso Plattner Institute, University of Potsdam, Germany

    Andreas Rogge-Solti & Mathias Weske

Authors
  1. Andreas Rogge-Solti
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  2. Mathias Weske
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Editor information

Editors and Affiliations

  1. IbisSoft AB, Stockholm, Box 19567, SE-10432, Stockholm, Sweden

    Ilia Bider

  2. LogicBlox, Australia, and INTI International University, Malaysia

    Terry Halpin

  3. Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), Sem Sælands Vei 7-9, 7491, Trondheim, Norway

    John Krogstie

  4. University Paris 1 Pantheon-Sorbonne, Paris, France

    Selmin Nurcan

  5. Erik Proper, PRC Henri Tudor, Luxembourg-Kirchberg, Luxembourg

    Erik Proper

  6. Aalen University, Aalen, Germany

    Rainer Schmidt

  7. University of Haifa, Carmel Mountain, 31905, Haifa, Israel

    Pnina Soffer

  8. Department of Business Informatics, University of Gdansk, ul. Piaskowa 9, 81-864, Sopot, Poland

    Stanisław Wrycza

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Rogge-Solti, A., Weske, M. (2012). Enabling Probabilistic Process Monitoring in Non-automated Environments. In: Bider, I., et al. Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2012 2012. Lecture Notes in Business Information Processing, vol 113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31072-0_16

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  • DOI: https://doi.org/10.1007/978-3-642-31072-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31071-3

  • Online ISBN: 978-3-642-31072-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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