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Discovering and categorizing goal alignments from mined process variants

Journal Article


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 bottomup 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.

UOW Authors


  •   Ponnalagu, Karthikeyan (external author)
  •   Ghose, Aditya
  •   Narendra, Nanjangud C. (external author)
  •   Dam, Hoa

Publication Date


  • 2015

Citation


  • Ponnalagu, K., Ghose, A. K., Narendra, N. C. & Dam, H. K. (2015). Discovering and categorizing goal alignments from mined process variants. Lecture Notes in Computer Science, 8954 114-157.

Scopus Eid


  • 2-s2.0-84983609915

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5069

Number Of Pages


  • 43

Start Page


  • 114

End Page


  • 157

Volume


  • 8954

Place Of Publication


  • Germany

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 bottomup 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.

UOW Authors


  •   Ponnalagu, Karthikeyan (external author)
  •   Ghose, Aditya
  •   Narendra, Nanjangud C. (external author)
  •   Dam, Hoa

Publication Date


  • 2015

Citation


  • Ponnalagu, K., Ghose, A. K., Narendra, N. C. & Dam, H. K. (2015). Discovering and categorizing goal alignments from mined process variants. Lecture Notes in Computer Science, 8954 114-157.

Scopus Eid


  • 2-s2.0-84983609915

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5069

Number Of Pages


  • 43

Start Page


  • 114

End Page


  • 157

Volume


  • 8954

Place Of Publication


  • Germany