Beyond Roles: Prediction Model-Based Process Resource Management

  • Florian Niedermann
  • Alexandru Pavel
  • Bernhard Mitschang
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 97)

Abstract

The outcome of a business process (e.g., duration, cost, success rate) depends significantly on how well the assigned resources perform at their respective tasks. Currently, this assignment is typically based on a static resource query that specifies the minimum requirements (e.g., role) a resource has to meet. This approach has the major downside that any resource whatsoever that meets the requirements can be retrieved, possibly selecting resources that do not perform well on the task. To address this challenge, we present and evaluate in this paper a model-based approach that uses data integration and mining techniques for selecting resources based on their likely performance for the task or sub-process at hand.

Keywords

Business Process Resource Dependency Resource Model Work Item Resource Assignment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Florian Niedermann
    • 1
  • Alexandru Pavel
    • 1
  • Bernhard Mitschang
    • 1
  1. 1.Institute of Parallel and Distributed SystemsUniversität StuttgartStuttgartGermany

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