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Proactive Management of Business Change

  • Mamadou Camara
  • Lyes Kermad
  • Abderrahman El Mhamedi
Part of the IFIP – The International Federation for Information Processing book series (IFIPAICT, volume 283)

This paper addresses enterprise performance problems that can occur after Business Process Reengineering (BPR) project as consequence of business change. The general idea is to lean a Bayesian network from past BPR projects and use this model for prediction in future restructured processes. The role of Bayesian network will be to measure influence of business process structural changes, quantified by structural change metrics, and the increasing or decreasing of process performance, quantified by operational variation metrics. The paper’s focus is interoperable structural change metrics definition using process ontology, and operational variation metrics definition. Bayesian prediction model learning, application and result interpretation are discussed in (CAMRA, et al., 2007). The method we propose is for use for the validation of enterprise restructuration, more precisely in the validation of business processes restructuration’s.

Keywords

Business Process Bayesian Network Control Chart Business Process Model Proactive Management 
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.

Copyright information

© International Federation for Information Processing 2008

Authors and Affiliations

  • Mamadou Camara
    • 1
  • Lyes Kermad
    • 1
  • Abderrahman El Mhamedi
    • 1
  1. 1.IUT de Montreuil- Université de Paris 8Montreuil CedexFrance

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