Risk–Response Budgeting: A Financial Optimization Approach to Project Risk Management

Projects are exposed to risks that may hinder their success regarding cost, schedule, and quality/content. After identifying these risks, the project manager must select a subset for mitigation, constrained by a limited risk response budget. The problem lies in the uncertainties surrounding risk realization, their impact on the project’s parameters, and the outcomes of the risk response plan. This paper proposes a method for allocating the risk–response budget to mitigate project risks. The method begins with a Monte Carlo simulation to assess each risk’s impact and residual impact post-mitigation. These simulation results are the input for mathematical programming calculations, determining the optimal budget allocation among the risks based on various objective functions (e.g., maximizing expected net savings or minimizing variance). Each objective function can yield a different optimal budget allocation, so the final step involves weighing all results to make a conclusive decision. A case study illustrates the proposed method.

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Publication Details

Journal
Journal of risk and financial management
Published
2025-03-18
DOI
https://doi.org/10.3390/jrfm18030160
Citations
2
Primary Topic
Construction Project Management and Performance
Type
article
Field-Weighted Citation Impact
4.21
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article

Risk–Response Budgeting: A Financial Optimization Approach to Project Risk Management

Baruch Keren, Yossi Hadad
2 citations
Journal of risk and financial management
Construction Project Management and Performance
4.21
article

Risk–Response Budgeting: A Financial Optimization Approach to Project Risk Management

Baruch Keren, Yossi Hadad
article en
2 citations

Abstract

Projects are exposed to risks that may hinder their success regarding cost, schedule, and quality/content. After identifying these risks, the project manager must select a subset for mitigation, constrained by a limited risk response budget. The problem lies in the uncertainties surrounding risk realization, their impact on the project’s parameters, and the outcomes of the risk response plan. This paper proposes a method for allocating the risk–response budget to mitigate project risks. The method begins with a Monte Carlo simulation to assess each risk’s impact and residual impact post-mitigation. These simulation results are the input for mathematical programming calculations, determining the optimal budget allocation among the risks based on various objective functions (e.g., maximizing expected net savings or minimizing variance). Each objective function can yield a different optimal budget allocation, so the final step involves weighing all results to make a conclusive decision. A case study illustrates the proposed method.

Journal of risk and financial managementVol. 18(3)
Sami Shamoon College of Engineering (IL)
Openalex Percentile: Top 7%
Construction Project Management and Performance
4.21
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