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Risk Filtering, Ranking, and Management Framework Using Hierarchical Holographic Modeling

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  • Yacov Y. Haimes
  • Stan Kaplan
  • James H. Lambert

Abstract

This paper contributes a methodological framework to identify, prioritize, assess, and manage risk scenarios of a large‐scale system. Qualitative screening of scenarios and classes of scenarios is appropriate initially, while quantitative assessments may be applied once the set of all scenarios (hundreds) has been prioritized in several phases. The eight‐phase methodology is described in detail and is applied to operations other than war. The eight phases are as follows: Phase I, Scenario Identification—A hierarchical holographic model (HHM) is developed to describe the system's ``as planned'' or ``success'' scenario. Phase II, Scenario Filtering—The risk scenarios identified in Phase I are filtered according to the responsibilities and interests of the current system user. Phase III, Bi‐Criteria Filtering and Ranking. Phase IV, Multi‐Criteria Evaluation. Phase V, Quantitative Ranking—We continue to filter and rank scenarios based on quantitative and qualitative matrix scales of likelihood and consequence; and ordinal response to system resiliency, robustness, redundancy. Phase VI, RiskManagement is performed, involving identification of management options for dealing with the filtered scenarios, and estimating the cost, performance benefits, and risk reduction of each. Phase VII, Safeguarding Against Missing Critical Items—We examine the performance of the options selected in Phase VI against the scenarios previously filtered out during Phases II to V. Phase VIII, OperationalFeedback—We use the experience and information gained during application to refine the scenario filtering and decision processes in earlier phases. These eight phases reflect a philosophical approach rather than a mechanical methodology. In this philosophy, the filtering and ranking of discrete scenarios is viewed as a precursor to, rather than a substitute for, consideration of the totality of all risk scenarios.

Suggested Citation

  • Yacov Y. Haimes & Stan Kaplan & James H. Lambert, 2002. "Risk Filtering, Ranking, and Management Framework Using Hierarchical Holographic Modeling," Risk Analysis, John Wiley & Sons, vol. 22(2), pages 383-397, April.
  • Handle: RePEc:wly:riskan:v:22:y:2002:i:2:p:383-397
    DOI: 10.1111/0272-4332.00020
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    References listed on IDEAS

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    1. M. Granger Morgan & H. Keith Florig & Michael L. DeKay & Paul Fischbeck, 2000. "Categorizing Risks for Risk Ranking," Risk Analysis, John Wiley & Sons, vol. 20(1), pages 49-58, February.
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    4. Stan Kaplan & Yacov Y. Haimes & B. John Garrick, 2001. "Fitting Hierarchical Holographic Modeling into the Theory of Scenario Structuring and a Resulting Refinement to the Quantitative Definition of Risk," Risk Analysis, John Wiley & Sons, vol. 21(5), pages 807-807, October.
    5. Jonathan Baron & John C. Hershey & Howard Kunreuther, 2000. "Determinants of Priority for Risk Reduction: The Role of Worry," Risk Analysis, John Wiley & Sons, vol. 20(4), pages 413-428, August.
    6. Yacov Y. Haimes, 1991. "Total Risk Management," Risk Analysis, John Wiley & Sons, vol. 11(2), pages 169-171, June.
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