April 13, 2015: Invited Speaker Seminar: Development of a Risk Assessment-to-Management Matching Matrix for IT Projects Using the Analytic Hierarchy Process and Fuzzy Memberships

Dr. Fereshteh Mafakheri
 

Wednesday, April 13,2015, 10:45 a.m.
Room EV003.309

Abstract

A project risk assessment process aims at analyzing the impact of potential risk events associated with a given project. Fulfilling such a process is the first requirement in developing risk response/ management strategies. Studies have shown that in reality, however, many projects suffer from a mismatch between the assessment and management of risks which could result in failure to meet time, budget and quality goals of projects. In particular, when it comes to risk assessment in the context of IT projects (with an ever changing customers’ demand and needs), risk management capabilities are less understood and sometimes not well incorporated into the project life cycle decisions. The argument is that if a project organization has sufficient capabilities to manage the identified project risks, then the impact of risk events will be mediated. On the other hand, with little or no management capability in place, even moderate risks with moderate likelihood and/or impact could jeopardize the success of projects.

In this research, a decision support tool for integrated risk assessment of IT projects is developed using an analytic hierarchy process. It links and compares the assessed risks of projects to the risk management capability of project organizations. The analytical hierarchy process is one of the most cited multiple criteria decision analysis approaches, capable of dealing with both qualitative and quantitative information, and in particular, with subjectivities involved in the risk evaluation process. We have identified 6 criteria and 28 sub-criteria to interpret the risks associated with IT projects. From there, we constructed a risk assessment-to-management matching matrix, leading to calculation of two sets of risk acceptance and rejection scores. In doing so, we have adopted the concept of fuzzy memberships in order to calculate the memberships of a project in the risk acceptance and rejection areas of the matrix. A higher membership in the risk acceptance area corresponds to projects with under-control and manageable risk profiles. 

The proposed matrix could be helpful for IT project managers by providing a risk-based ranking of projects. It could also assist in project delivery decisions to effectively allocate the resources according to identified gaps between assessed risks and the corresponding risk management capabilities. Using this multi-dimensional approach, for instance, a project with a moderate dimension of risk could also be subject to rejection because the project organization/team is not equipped with the necessary capabilities to address the specific risks associated with the project. This study was addressing the lack of a risk knowledge management framework for IT projects capable of integrating both project and organizational risk factors and their likelihoods and foreseen impacts.

Biography

Dr. Fereshteh Mafakheri received her PhD in Quantitative Methods from HEC (University of Montreal) in 2011. She is currently a part-time faculty member at the Faculty of Engineering and Computer Science (ENCS) at Concordia University. Prior to moving to Concordia, Fereshteh worked as a full-time faculty at Department of Systems Management at the University of Greenwich, London, UK, for about four years. Dr. Mafakheri has worked as a research assistant in systems modelling and analysis at Yale University and the University of Calgary.                                                                  

Dr. Mafakheri’s research interests evolve around the applications of operational research approaches in IT Project Risk Assessment & Analysis, IT Project Knowledge Management, Supply Chain Management and Sustainability. Fereshteh’s work has been published and cited in several top-tier journals. She has been active in organizing seminars and presenting her work at various international conferences. Dr. Mafakeri holds MSc and BSc degrees in Industrial Systems Engineering, a Postgraduate Certificate (PGCert) in Higher Education Teaching and Learning and is a fellow of UK Higher Education Academy.