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Monitoring risk response actions for effective project risk management

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  • Edouard Kujawski
  • Diana Angelis

Abstract

Complex projects typically involve high‐consequence, project‐specific risks that require detailed analysis and for which risk response actions (RRAs) need to be developed and implemented. The risk picture is dynamic. The sources and consequences of risks evolve and change over the project lifecycle; thus, it is necessary to constantly monitor risk. RRAs that do not keep pace with the changing project situation are a major cause of risk management failures. This paper extends traditional cost risk analysis from a purely macroscopic perspective by evaluating and tracking project‐specific risks and RRAs at the microscopic level. The key elements of the method are (i) develop risk scenarios, (ii) model them using generalized decision trees, and (iii) quantify the risks using Monte Carlo simulation. For each risk the probability and cost values are conditional on the specific RRA and the preceding outcomes. The use of fractional factorial design provides a subset of all possible RRA combinations for efficiently determining the preferred total project RRA solution. Risk curves are generated to provide the necessary information to analyze, track, and manage the performance of the selected RRAs over time. Project managers and team leaders can use this information to dynamically manage the RRAs to keep pace with the changing project situation, thereby increasing the probability of project success in a cost‐effective manner. The approach is detailed using a realistic but simplified case of a project examined first with one and then expanded to three technical risks. © 2009 Wiley Periodicals, Inc. Syst Eng 13

Suggested Citation

  • Edouard Kujawski & Diana Angelis, 2010. "Monitoring risk response actions for effective project risk management," Systems Engineering, John Wiley & Sons, vol. 13(4), pages 353-368, December.
  • Handle: RePEc:wly:syseng:v:13:y:2010:i:4:p:353-368
    DOI: 10.1002/sys.20154
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    References listed on IDEAS

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    1. Edouard Kujawski, 2002. "Selection of technical risk responses for efficient contingencies," Systems Engineering, John Wiley & Sons, vol. 5(3), pages 194-212.
    2. 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.
    3. Michael J. Pennock & Yacov Y. Haimes, 2002. "Principles and guidelines for project risk management," Systems Engineering, John Wiley & Sons, vol. 5(2), pages 89-108.
    4. M.‐Elisabeth Paté‐Cornell & Peter J. Regan, 1998. "Dynamic Risk Management Systems: Hybrid Architecture and Offshore Platform Illustration," Risk Analysis, John Wiley & Sons, vol. 18(4), pages 485-496, August.
    5. Avner Engel & Miryam Barad, 2003. "A methodology for modeling VVT risks and costs," Systems Engineering, John Wiley & Sons, vol. 6(3), pages 135-151.
    6. Yacov Y. Haimes, 1991. "Total Risk Management," Risk Analysis, John Wiley & Sons, vol. 11(2), pages 169-171, June.
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    Cited by:

    1. Xin Guan & Tom Servranckx & Mario Vanhoucke, 2024. "Risk response budget allocation based on fault tree analysis and optimization," Annals of Operations Research, Springer, vol. 337(2), pages 523-564, June.
    2. Zhang, Yao & Zuo, Fei & Guan, Xin, 2020. "Integrating case-based analysis and fuzzy optimization for selecting project risk response actions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

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