The Holistic Risk Analysis and Modelling (HoRAM) method. (February 2019)

• Record Type: Journal Article
• Authors: Colombo, Simone
• Is Part Of: Safety science. Volume 112(2019)
• Page Start: 18
• Page End: 37
• Publication Date: 2019-02
• Subjects: Industrial accidents -- Periodicals; Accident Prevention -- Periodicals; Safety -- Periodicals; Travail -- Accidents -- Périodiques; 363.11
• DOI: 10.1016/j.ssci.2018.09.018
• Languages: English
• ISSNs: 0925-7535

Abstract

Graphical abstract: Highlights: Systemic and systematic risk analysis and modelling. Logic-based Artificial Intelligence to face increasing complexity of systems. Risk Curve, Risk Spectrum (new), and Critical Functions List as practical tools. Systemic and systematic verification of the efficacy of solutions to reduce risks. Risk-based decision making as evolution of the opportunity-based approach. Abstract: Making decisions in complex systems and for complex phenomena is a challenging task to accomplish. As complexity and uncertainty increase, the use of scenarios to exploring that uncertainty becomes essential to support decision makers. Yet, the increasing complexity of and interrelatedness amongst systems/phenomena is imposing to the risk analysis world a paradigm shift from traditional, "paper and pencil" approaches toward simulation-based approaches, not least because the cognitive demand required to envisage all the possible alternatives the system/phenomenon might unfold is too high to manage for the human mind. The paper presents how the Holistic Risk Analysis and Modelling (HoRAM) method allows, on the one hand, to holistically account for the Human, the Technological and the Organisational (HTO) elements of the system/phenomenon being analysed and, on the other hand, thanks to the use of artificial logic, to create complete partitions of sizes that are unthinkable to achieve with traditional, paper and pencil methods. The paper also explains how the method allows to systemically and systematically account for the consequences scenarios might generate, thus allowing to include in the decision both the possibility of the unwanted outcomes and the associated effort needed to make them less likely or less severe. Finally, it explains how the scenarios can be managed at different level of abstraction to deriving the well-known risk curve, the newly defined risk spectrum, and the critical functions list, which are all necessary tools to better discriminating which alternative to pursue and where exactly investing the (always limited and scarse) resources to reduce the risk.