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

Felipe Sanchez Garzon, Eric Bonjour (), Jean-Pierre Micaëlli () and Davy Monticolo ()
Additional contact information
Felipe Sanchez Garzon: Sopra Steria (FRANCE)
Eric Bonjour: ERPI - Equipe de Recherche sur les Processus Innovatifs - UL - Université de Lorraine
Jean-Pierre Micaëlli: MAGELLAN - 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

Post-Print from HAL

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.

Keywords: Bayesian Networks; Cost Overrun; Knowledge Modeling; Maturity Model; Project Management (search for similar items in EconPapers)
Date: 2020-08-01
References: Add references at CitEc
Citations:

Published in Computers in Industry, 2020, 119 (2020), pp.103227. ⟨10.1016/j.compind.2020.103227⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04460061

DOI: 10.1016/j.compind.2020.103227

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().