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Extending BPM Environments of Your Choice with Performance Related Decision Support

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5701))

Abstract

What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools, process optimizations or a combination of such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.

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© 2009 Springer-Verlag Berlin Heidelberg

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Fritzsche, M., Picht, M., Gilani, W., Spence, I., Brown, J., Kilpatrick, P. (2009). Extending BPM Environments of Your Choice with Performance Related Decision Support. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds) Business Process Management. BPM 2009. Lecture Notes in Computer Science, vol 5701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03848-8_8

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  • DOI: https://doi.org/10.1007/978-3-642-03848-8_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03847-1

  • Online ISBN: 978-3-642-03848-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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