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Discovering and Categorizing Goal Alignments from Mined Process Variants

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Service-Oriented Computing - ICSOC 2014 Workshops

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8954))

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Abstract

With the emergence of contextual enterprise, organizations increasingly tend to analyze the adherence of the day to day execution of internal business processes with their stated goals. This is needed so that they can continuously evaluate and readjust their operating models and corresponding business strategies. However organizations often find it very difficult to discover and categorize the process variants in terms of their stated goal adherence from process execution logs. This is due to the challenges in resolving the extent of goal compliance as it necessitates the classification of process variants first in terms of the contextual factors associated with the process execution. In this paper, we propose our approach for discovering goal adherence of process variant instances mined from event logs. We first generate goal-service alignment models to establish correlation of process fragments with specific sub-goals of the organization’s goal model. Subsequently we discover the extent of goal adherence of individual process instances by the composition of correlated sub-goals. We also associate the contextual factors with each process instance that are goal preserving in nature. Leveraging the difference in correlation and association of contextual factors we classify the instances as goal preserving executed process variants. This bottom-up approach enables the organizations to study the depth and breadth of goal adherence in their organizations. Also the impact of any specific change in the goal decomposition models and the associated contextual factors can be studied with our approach. We evaluate our approach using a real industrial case study in IT Incident Management using a event log of 25000 records.

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Notes

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Authors and Affiliations

  1. IBM Research India, Bangalore, India

    Karthikeyan Ponnalagu

  2. Cognizant Technology Solutions, Bangalore, India

    Nanjangud C. Narendra

  3. University of Wollongong, Wollongong, Australia

    Karthikeyan Ponnalagu, Aditya Ghose & Hoa Khanh Dam

Authors
  1. Karthikeyan Ponnalagu
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  2. Aditya Ghose
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  3. Nanjangud C. Narendra
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  4. Hoa Khanh Dam
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Corresponding author

Correspondence to Karthikeyan Ponnalagu .

Editor information

Editors and Affiliations

  1. Blaise Pascal University, Aubiere, France

    Farouk Toumani

  2. Politecnico di Milano, Milano, Italy

    Barbara Pernici

  3. Université Paris Dauphine, Paris, France

    Daniela Grigori

  4. Université Claude Bernard Lyon 1, Villeurbanne, France

    Djamal Benslimane

  5. Vienna University of Economics, Vienna, Austria

    Jan Mendling

  6. National Engineering School of Tunis, Tunis, Tunisia

    Nejib Ben Hadj-Alouane

  7. University of Miami, Coral Gables, Florida, USA

    Brian Blake

  8. University Lorraine, Nancy, France

    Olivier Perrin

  9. University of Miami, Coral Gables, Florida, USA

    Iman Saleh Moustafa

  10. Telecom SudParis, Evry, France

    Sami Bhiri

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© 2015 Springer International Publishing Switzerland

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Ponnalagu, K., Ghose, A., Narendra, N.C., Dam, H.K. (2015). Discovering and Categorizing Goal Alignments from Mined Process Variants. In: Toumani, F., et al. Service-Oriented Computing - ICSOC 2014 Workshops. Lecture Notes in Computer Science(), vol 8954. Springer, Cham. https://doi.org/10.1007/978-3-319-22885-3_13

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  • DOI: https://doi.org/10.1007/978-3-319-22885-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22884-6

  • Online ISBN: 978-3-319-22885-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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