Citation

Komljenovic D, Gaha M, Abdul-Nour G, Langheit C, Bourgeois M. Safety Sci. 2016; 88: 129-145.

Copyright

(Copyright © 2016, Elsevier Publishing)

DOI

10.1016/j.ssci.2016.05.004

PMID

unavailable

Abstract

Modern companies operate in a complex business and operational environment, which generates new types of risks that were relatively unknown just a few decades ago (e.g. cyber security), and creates favorable conditions for the emerging of extreme and rare events that may seriously perturb the current and long-term performance of enterprises. Current practices generally neglect taking into account those risks. Analyzing and managing them through traditional methods has recently shown to be less efficient. Advice and input from technical experts, strategic planners or knowledgeable managers may be insufficient or too narrowly focused to adequately manage the complexity of the systems and structures in a constantly changing and barely predictable environment. It is generally due to a lack of knowledge regarding the type and range of uncertainties, the nature of interconnections, the level of complexity, as well as our low ability to predict future events. Consequently, enterprises need alternative and enhanced methods and tools in order to better understand and model the complex business and operational environment and the associated risks.

This paper proposes a high level Risk-Informed Decision-Making framework in Asset Management that integrates risks extreme and rare events as part of an overall risk assessment and management activity. The research focuses on the methodology aimed at identifying, assessing and managing those risks in Asset Management. We believe that this approach may support organizations in becoming companies more resilient and robust in a changing and complex environment. We expose two case studies that demonstrate the applicability of the proposed model.

Language: en