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Linear Monte Carlo Methodology

In: Risk-Based Project Decisions in Situations of High Complexity and Deep Uncertainty

Author

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  • Yuri G. Raydugin

    (Risk Services & Solutions Inc.)

Abstract

This chapter overviews the well-known basics of the traditional Monte Carlo methodology to define project schedule and cost contingencies. Three components of the Monte Carlo PRM system—framework, process and tools—are looked through. Contribution of the traditional scoring PRM in providing valuable inputs is accentuated. Integrated schedule and cost risk analysis (SCRA) is utilized as a standard realization of the Monte Carlo methodology in capital projects. As opposed to more adequate nonlinear Monte Carlo methodology counting risk interactions, the reviewed version is dubbed linear. Limitations of the linear Monte Carlo methodology and its L-SCRA version are discovered: ignoring risk interactions as a major contribution to project risk exposure results in high systematic error and, hence, optimistic (low) contingencies. A simplistic business case devoted to L-SCRA modelling concludes the chapter. It demonstrates main steps of the L-SCRA process. It utilizes six project execution risks collected in the previous chapter as primary inputs. This allows to probabilistically estimate the required schedule and cost contingencies.

Suggested Citation

  • Yuri G. Raydugin, 2024. "Linear Monte Carlo Methodology," Springer Books, in: Risk-Based Project Decisions in Situations of High Complexity and Deep Uncertainty, chapter 0, pages 115-156, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-56988-3_4
    DOI: 10.1007/978-3-031-56988-3_4
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