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Goal-driven business process derivation

Journal Article


Abstract


  • Solutions to the problem of deriving business processes from goals

    are critical in addressing a variety of challenges facing the services and business

    process management community, and in particular, the challenge of quickly generating

    large numbers of effective process designs (often a bottleneck in industryscale

    deployment of BPM). The problem is similar to the planning problem that

    has been extensively studied in the artificial intelligence (AI) community. However,

    the direct application of AI planning techniques places an onerous burden

    on the analyst, and has proven to be difficult in practice. We propose a practical

    yet rigorous (semi-automated) algorithm for business process derivation from

    goals. Our approach relies on being able to decompose process goals to a more

    refined collection of sub-goals whose ontology is aligned with that of the effects

    of available tasks which can be used to construct the business process. Once process

    goals are refined to this level, we are able to generate a process design using

    a procedure that leverages our earlier work on semantic effect annotation of process

    designs.We illustrate our ideas throughout this paper with a real-life running

    example, and also present a proof-of-concept prototype implementation.

UOW Authors


  •   Ghose, Aditya
  •   Narendra, Nanjangud C. (external author)
  •   Ponnalagu, Karthikeyan (external author)
  •   Panda, A (external author)
  •   Gohad, Atul (external author)

Publication Date


  • 2011

Citation


  • Ghose, A. K., Narendra, N. C., Ponnalagu, K., Panda, A. & Gohad, A. (2011). Goal-driven business process derivation. Lecture Notes in Computer Science, 7084 467-476. Paphos Goal-driven business process derivation

Scopus Eid


  • 2-s2.0-82055196738

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/3789

Number Of Pages


  • 9

Start Page


  • 467

End Page


  • 476

Volume


  • 7084

Abstract


  • Solutions to the problem of deriving business processes from goals

    are critical in addressing a variety of challenges facing the services and business

    process management community, and in particular, the challenge of quickly generating

    large numbers of effective process designs (often a bottleneck in industryscale

    deployment of BPM). The problem is similar to the planning problem that

    has been extensively studied in the artificial intelligence (AI) community. However,

    the direct application of AI planning techniques places an onerous burden

    on the analyst, and has proven to be difficult in practice. We propose a practical

    yet rigorous (semi-automated) algorithm for business process derivation from

    goals. Our approach relies on being able to decompose process goals to a more

    refined collection of sub-goals whose ontology is aligned with that of the effects

    of available tasks which can be used to construct the business process. Once process

    goals are refined to this level, we are able to generate a process design using

    a procedure that leverages our earlier work on semantic effect annotation of process

    designs.We illustrate our ideas throughout this paper with a real-life running

    example, and also present a proof-of-concept prototype implementation.

UOW Authors


  •   Ghose, Aditya
  •   Narendra, Nanjangud C. (external author)
  •   Ponnalagu, Karthikeyan (external author)
  •   Panda, A (external author)
  •   Gohad, Atul (external author)

Publication Date


  • 2011

Citation


  • Ghose, A. K., Narendra, N. C., Ponnalagu, K., Panda, A. & Gohad, A. (2011). Goal-driven business process derivation. Lecture Notes in Computer Science, 7084 467-476. Paphos Goal-driven business process derivation

Scopus Eid


  • 2-s2.0-82055196738

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/3789

Number Of Pages


  • 9

Start Page


  • 467

End Page


  • 476

Volume


  • 7084