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An Approach Based on Bayesian Network for Improving Project Management Maturity: An Application to Reduce Cost Overrun Risks in Engineering Projects

Author

Listed:
  • Felipe Sanchez Garzon

    (Sopra Steria (FRANCE))

  • Eric Bonjour

    (ERPI - Equipe de Recherche sur les Processus Innovatifs - UL - Université de Lorraine)

  • Jean-Pierre Micaëlli

    (Laboratoire de Recherche Magellan - UJML - Université Jean Moulin - Lyon 3 - Université de Lyon - Institut d'Administration des Entreprises (IAE) - Lyon)

  • Davy Monticolo

    (ERPI - Equipe de Recherche sur les Processus Innovatifs - UL - Université de Lorraine)

Abstract

The project management field has the imperative to increase the success probability of projects. Experts have developed several Project Management Maturity (PMM) models to assess project management practices and improve the project outcome. However, the current literature lacks models that allow experts to correlate the measured maturity with the expected probability of success. The present paper develops a general framework and a method to estimate the impact of PMM on project performance. It uses Bayesian networks to formalize project management experts' knowledge and to extract knowledge from a database of past projects. An industrial case concerning large projects in the oil and gas industry is used to illustrate the application of the method to reduce the risk of project cost (or budget) overruns.

Suggested Citation

  • Felipe Sanchez Garzon & Eric Bonjour & Jean-Pierre Micaëlli & Davy Monticolo, 2020. "An Approach Based on Bayesian Network for Improving Project Management Maturity: An Application to Reduce Cost Overrun Risks in Engineering Projects," Post-Print hal-04460061, HAL.
    • Handle: RePEc:hal:journl:hal-04460061
    DOI: 10.1016/j.compind.2020.103227
    as

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