Workflow simulation for operational decision support

  • Authors:

  • A. Rozinat;M. T. Wynn;W. M. P. van der Aalst;A. H. M. ter Hofstede;C. J. Fidge

  • Affiliations:

  • Information Systems Group, Eindhoven University of Technology, P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands;Business Process Management Group, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia;Information Systems Group, Eindhoven University of Technology, P.O. Box 513, NL-5600 MB, Eindhoven, The Netherlands and Business Process Management Group, Queensland University of Technology, GPO ...;Business Process Management Group, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia;Business Process Management Group, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2009

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Abstract

Simulation is widely used as a tool for analyzing business processes but is mostly focused on examining abstract steady-state situations. Such analyses are helpful for the initial design of a business process but are less suitable for operational decision making and continuous improvement. Here we describe a simulation system for operational decision support in the context of workflow management. To do this we exploit not only the workflow's design, but also use logged data describing the system's observed historic behavior, and incorporate information extracted about the current state of the workflow. Making use of actual data capturing the current state and historic information allows our simulations to accurately predict potential near-future behaviors for different scenarios. The approach is supported by a practical toolset which combines and extends the workflow management system YAWL and the process mining framework ProM.