Improving risk matrices using the MACBETH approach for multicriteria value measurement

Abstract

Risk matrices (RMs) have been recommended by many organizations to evaluate and mitigate risks. This study aims at improving the design and the deployment of RMs, avoiding theoretical problems of traditional RMs and inconsistent risk ratings, following Multicriteria and Portfolio Decision Analysis. In particular, the MACBETH approach is used to build quantitative evaluation models from qualitative value judgments. A new RMs’ modeling framework is proposed, which includes: (1) the construction of a multicriteria additive value model applying MACBETH to assess risk impacts; (2) the innovative use of MACBETH to derive subjective probabilities; (3) the transformation of a RM into a Value Risk Matrix (VRM); (4) the definition of multicriteria assignment procedures, applied to classify risks from the VRM by severity; (5) and the use of MACBETH’s resource allocation to prioritize risk mitigation actions and analyze portfolios that offer the best value for money for different budgeting and contextual constraints.