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Interactions-Based Clustering to Assist Project Risk Management
Vidal, Ludovic-Alexandre; Marle, Franck; Bocquet, Jean-Claude
Type:
Year:
2009
Editor:
Norell Bergendahl, M.; Grimheden, M.; Leifer, L.; Skogstad, P.; Lindemann, U.
Author:
Series:
ICED
Section:
Design Organization and Management
Page(s):
145-156
Abstract:
Projects are dealing with bigger stakes and facing an ever-growing complexity. Project risks have then increased in number and criticality. Lists of identified project risks thus need to be decomposed, for smaller clusters are more manageable. Existing techniques are mainly mono-criteria, based on a parameter such as nature or criticality. Limits have appeared since project risk interactions are not properly considered. Project interdependent risks are indeed often managed as if they were independent. We thus propose an interactions-based clustering method with associated tools and algorithms. Our objective is to group risks, so that the interaction rate is maximal inside clusters and minimal outside. The final objective is to facilitate the coordination of complex projects by reducing interfaces when dealing with risks. We first model project risk interactions through matrix representation. A linear programming algorithm, two approximate iterative ones and possible refinement are then presented. A case study in the entertainment industry is finally presented, providing us information and points of comparison for global recommendations, conclusions and perspectives.
Keywords:
