Project risk management processes: improving coordination using a clustering approach

Abstract

Projects are dealing with bigger stakes and facing an ever-growing complexity. In the first place, project risks have increased in number and criticality. Lists of identified project risks thus need to be broken down into more manageable clusters. Existing techniques for this are generally based on a well-known parameter such as the nature of the risk or its ownership. The limits of this approach are that project risk interactions are not properly considered.Project interdependent risks are thus often analysed and managed as if they were independent. The consequence is that there may be a lack of consideration of potential propagation through this risk network. A change may have dramatic consequences if the propagation chain is not clearly identified and/or not managed. Our objective in this paper is to propose a methodology for grouping risks so that the project risk interaction rate is maximal inside clusters and minimal outside. What we hope to achieve is a method which facilitates the coordination of complex projects which have many interrelated risks with many different risk owners. We contend that the capacity of risk owners to communicate and make coordinated decisions will be improved if they are grouped in such a way. This proposed reconfiguration of organisation is complementary to existing configurations. To do this, we first model project risk interactions through matrix representations. Then, the mathematical formulation of the problem is presented and two heuristics are introduced. A case study in the civil engineering industry (a large infrastructure public-private partnership project) is presented, which enables us to propose global recommendations, conclusions and perspectives.

Analysis of interactions among barriers in project risk management

“…All project lifecycles consist of a sequence of stages and activities, from origin to completion and there is always a degree of risk associated with each stage (Stewart and Fortune 1995). The organizational and technological complexity of projects can generate enormous risks (Marle and Vidal 2011;Aloini et al 2012;Zou et al 2007;Carr and Tah 2001). Managing risks in every phase is very important to improve project success rates (Bush et al 2005;Keizer et al 2002;Smith and Merritt 2002).…”

Improving Collaborative Decision Making in New Product Development Projects Using Clustering Algorithms

“…The Risk-Risk Matrix (RR) had been modeled to capture risk interactions. Then, a risk clustering approach had been applied in order to enhance efficiency in risk management by capturing possible risk propagation paths [21]- [23].…”

Integration of system design and production processes in robust mechatronic product architectures development - extended M-FBFP framework

“…Process modelling phase -with several intermediate steps: a) Modelling of risk interactions in processes -Identification of risk interactions in processes -Risk Structure Matrix (RSM) Using identification, we are able detect and establish cause-effect relationships between risks. For this purpose, we defined the Risk Structure Matrix (RSM) [10][11][12], a binary and square matrix where the value RSM ij = 1 if there is an interaction between the two risks R i and R j .…”

“…-An evaluation of risk interactions is provided using the Risk Numerical Matrix (RNM) [10][11][12] based on AHP-based principles [41]. The numerical values in the matrix were obtained from a Saaty scale for both the causes (inputs) and effects (outputs) to provide a risk pair wise comparison [41,42].…”

“…In product modelling, it focuses on the relationship between functions using the function based failure propagation method [7] and extends their impact on the Quality Function Deployment (QFD) method [8] and other domains (requirements, technical processes and components) in a Multiple-Domain Matrix (MDM) [9]. In regards to process modelling, on the other hand, it deals with modelling of risk interactions based on their identification and evaluation and risk propagation and re-evaluation [10][11][12]. Based on the result derived from process modelling, improvements are made to the QFD and technical process domain in the MDM matrix.…”