Linear Monte Carlo Methodology

Yuri G. Raydugin
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Yuri G. Raydugin: Risk Services & Solutions Inc.

Chapter Chapter 4 in Risk-Based Project Decisions in Situations of High Complexity and Deep Uncertainty, 2024, pp 115-156 from Springer

Abstract: 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.

Keywords: Linear Monte Carlo methodology; Linear schedule and cost risk analysis (L-SCRA); Correlations; Unknown unknowns; Probabilistic distribution; Decision-making confidence level; Project contingency; Corporate reserve; Stretched target; Contingency drawdown; What-if scenarios (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-56988-3_4

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DOI: 10.1007/978-3-031-56988-3_4

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