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Risk matrix input data biases

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  • Eric D. Smith
  • William T. Siefert
  • David Drain

Abstract

Risk matrices used in industry characterize particular risks in terms of the likelihood of occurreRisk matrix input data biaseshe actualized risk. Human cognitive bias research led by Daniel Kahneman and Amos Tversky exposed systematic translations of objective probability and value as judged by human subjects. Applying these translations to the risk matrix allows the formation of statistical hypotheses of risk point placement biases. Industry‐generated risk matrix data reveals evidence of biases in the judgment of likelihood and consequence—principally, likelihood centering, a systematic increase in consequence, and a diagonal bias. Statistical analyses are conducted with linear regression, normal distribution fitting, and Bayesian analysis. Evidence presented could improve risk matrix based risk analysis prevalent in industry. © 2008 Wiley Periodicals, Inc. Syst Eng

Suggested Citation

  • Eric D. Smith & William T. Siefert & David Drain, 2009. "Risk matrix input data biases," Systems Engineering, John Wiley & Sons, vol. 12(4), pages 344-360, December.
    • Handle: RePEc:wly:syseng:v:12:y:2009:i:4:p:344-360
    DOI: 10.1002/sys.20126
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    References listed on IDEAS

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    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
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    3. Jianping Li & Chunbing Bao & Dengsheng Wu, 2018. "How to Design Rating Schemes of Risk Matrices: A Sequential Updating Approach," Risk Analysis, John Wiley & Sons, vol. 38(1), pages 99-117, January.
    4. Bill A. Olson & Thomas A. Mazzuchi & Shahram Sarkani & Kevin Forsberg, 2012. "Problem management process, filling the gap in the systems engineering processes between the risk and opportunity processes," Systems Engineering, John Wiley & Sons, vol. 15(3), pages 275-286, September.
    5. Genserik L. L. Reniers & Kenneth Sörensen, 2013. "An Approach for Optimal Allocation of Safety Resources: Using the Knapsack Problem to Take Aggregated Cost‐Efficient Preventive Measures," Risk Analysis, John Wiley & Sons, vol. 33(11), pages 2056-2067, November.
    6. Gema Sakti Raspati & Stian Bruaset & Camillo Bosco & Lars Mushom & Birgitte Johannessen & Rita Ugarelli, 2022. "A Risk-Based Approach in Rehabilitation of Water Distribution Networks," IJERPH, MDPI, vol. 19(3), pages 1-24, January.
    7. Andrea Chaves & A. Terry Bahill, 2014. "Comparison of Risk Analysis Approaches and a Case Study of the Risk of Incorporating Solar Photovoltaic Systems into a Commercial Electric Power Grid," Systems Engineering, John Wiley & Sons, vol. 17(1), pages 89-111, March.

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