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Fixing the cracks in the crystal ball: A maturity model for quantitative risk assessment

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  • Rae, Andrew
  • Alexander, Rob
  • McDermid, John

Abstract

Quantitative risk assessment (QRA) is widely practiced in system safety, but there is insufficient evidence that QRA in general is fit for purpose. Defenders of QRA draw a distinction between poor or misused QRA and correct, appropriately used QRA, but this distinction is only useful if we have robust ways to identify the flaws in an individual QRA. In this paper we present a comprehensive maturity model for QRA which covers all the potential flaws discussed in the risk assessment literature and in a collection of risk assessment peer reviews. We provide initial validation of the completeness and realism of the model.

Suggested Citation

  • Rae, Andrew & Alexander, Rob & McDermid, John, 2014. "Fixing the cracks in the crystal ball: A maturity model for quantitative risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 67-81.
    • Handle: RePEc:eee:reensy:v:125:y:2014:i:c:p:67-81
    DOI: 10.1016/j.ress.2013.09.008
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    1. Nguyen, Son & Chen, Peggy Shu-Ling & Du, Yuquan & Thai, Vinh V., 2021. "An Operational Risk Analysis Model for Container Shipping Systems considering Uncertainty Quantification," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Shenae Lee & Gabriele Landucci & Genserik Reniers & Nicola Paltrinieri, 2019. "Validation of Dynamic Risk Analysis Supporting Integrated Operations Across Systems," Sustainability, MDPI, vol. 11(23), pages 1-25, November.
    3. Sujan, Mark A. & Habli, Ibrahim & Kelly, Tim P. & Gühnemann, Astrid & Pozzi, Simone & Johnson, Christopher W., 2017. "How can health care organisations make and justify decisions about risk reduction? Lessons from a cross-industry review and a health care stakeholder consensus development process," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 1-11.
    4. Amundrud, Øystein & Aven, Terje, 2015. "On how to understand and acknowledge risk," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 42-47.
    5. Stephen Thomas & Katrina M Groth, 2023. "Toward a hybrid causal framework for autonomous vehicle safety analysis," Journal of Risk and Reliability, , vol. 237(2), pages 367-388, April.
    6. Alceu Souza & Ariane Maria Machado de Oliveira & Dayla Karolina Fossile & Emmanuel Óguchi Ogu & Luciano Luiz Dalazen & Claudimar Pereira da Veiga, 2020. "Business Plan Analysis Using Multi-Index Methodology: Expectations of Return and Perceived Risks," SAGE Open, , vol. 10(1), pages 21582440199, January.
    7. Aven, Terje, 2018. "How the integration of System 1-System 2 thinking and recent risk perspectives can improve risk assessment and management," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 237-244.
    8. Christian C. Blanco & Felipe Caro & Charles J. Corbett, 2019. "Managing Safety‐Related Disruptions: Evidence from the U.S. Nuclear Power Industry," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2197-2213, October.
    9. Nguyen, Son & Chen, Peggy Shu-Ling & Du, Yuquan & Shi, Wenming, 2019. "A quantitative risk analysis model with integrated deliberative Delphi platform for container shipping operational risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 203-227.
    10. Denney, Ewen & Pai, Ganesh & Whiteside, Iain, 2019. "The role of safety architectures in aviation safety cases," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    11. Marie Røyksund & Roger Flage, 2019. "When Is a Risk Assessment Deficient According to an Uncertainty‐Based Risk Perspective?," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 761-776, April.
    12. Lewis, Austin D. & Groth, Katrina M., 2022. "Metrics for evaluating the performance of complex engineering system health monitoring models," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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