Clustering Project Risks According to Their Interactions

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 based on a well-known parameter such as the nature of the risk or its criticality. But some limits have appeared since project risk interactions are not properly considered. Project interdependent risks are indeed often considered and managed just as if they were independent. We thus propose an interactions-based clustering method with its associated algorithms and heuristics. Our objective is to group risks, so that the project risk interaction rate is maximal inside clusters and minimal outside. The final objective of this study is to facilitate the coordination of complex projects by reducing interfaces when dealing with risks. We first model project risk interactions through a matrix representation. Then, the overall mathematical formulation of the problem is presented. A case study in the construction industry is finally presented and permits us to propose global recommendations, conclusions and perspectives.