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An Effort Prediction Model Based on BPM Measures for Process Automation

  • Conference paper
Enterprise, Business-Process and Information Systems Modeling (BPMDS 2013, EMMSAD 2013)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 147))

Abstract

BPM software automation projects require different approaches for effort estimation for they are developed based on business process models rather than traditional requirements analysis outputs. In this empirical research we examine the effect of various measures for BPMN compliant business process models on the effort spent to automate those models. Although different measures are suggested in the literature, only a few studies exist that relate these measures to effort estimation. We propose that different perspectives of business process models need to be considered such as behavioral, organizational, functional and informational to determine the automation effort effectively. The proposed measures include number of activities, number of participating roles, number of outputs from the process and control flow complexity. We examine the effect of these measures on the automation effort and propose a prediction model developed by multiple linear regression analysis. The data were collected from a large IS integration project which cost 300 person-months along a three-year time frame. The results indicate that some of the measures collected have significant effect on the effort spent to develop the BPM automation software. We envision that prediction models developed by using the suggested approach will be useful to make accurate estimates of project effort for BPM intensive software development projects.

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Authors and Affiliations

  1. Informatics Institute, Middle East Technical University, Ankara, Turkey

    Banu Aysolmaz & Onur Demirörs

  2. Computer Center, Middle East Technical University, Ankara, Turkey

    Deniz İren

Authors
  1. Banu Aysolmaz
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  2. Deniz İren
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  3. Onur Demirörs
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Editor information

Editors and Affiliations

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

    Selmin Nurcan

  2. Public Research Centre - Henri Tudor, Luxembourg-Kirchberg, Luxembourg

    Henderik A. Proper

  3. Information Systems, University of Haifa, Haifa, Israel

    Pnina Soffer

  4. Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway

    John Krogstie

  5. Aalen University, Beethovenstraße 1, 73430, Aalen, Germany

    Rainer Schmidt

  6. INTI International University, Kuala Lumpur, Malaysia

    Terry Halpin

  7. Stockholm University/IbisSoft, Stockholm, Sweden

    Ilia Bider

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Aysolmaz, B., İren, D., Demirörs, O. (2013). An Effort Prediction Model Based on BPM Measures for Process Automation. In: Nurcan, S., et al. Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2013 2013. Lecture Notes in Business Information Processing, vol 147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38484-4_12

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  • DOI: https://doi.org/10.1007/978-3-642-38484-4_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38483-7

  • Online ISBN: 978-3-642-38484-4

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