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(RISK-2808) Non-Linear Probabilistic (Monte Carlo) Modeling of Systemic Risks

Literature on project management contains an abundancy of references to abnormally high project cost overruns as well as complains that modern risk quantification methods could not accurately predict project cost outcomes in many cases. Although the accuracy could be high in some other cases.

Initially, a hybrid cost contingency development methodology was introduced as a major attempt to explain the low accuracy through introduction of so called ‘systemic risks’. It combined standard probabilistic (Monte Carlo) methodology for project-specific risks with parametric methodology for systemic risks.

The purpose of this paper is to introduce a replacement of the parametric part of the hybrid methodology by means of a non-linear probabilistic (Monte Carlo) modeling in a consistent way. Systemic risks are considered additional causes of project-specific cost risks giving rise to non-linear cost impacts.

This article provides with
• explanation and Monte Carlo modeling of abnormally high project cost overruns including modeling of ‘tipping in blow-out’,
• a link of systemic risks with a ‘project team’s quality’ concept reflecting a project team’s strengths and weaknesses,
• an explanation why most currently used standard probabilistic (Monte Carlo) methodologies are relevant to ‘strong teams’ only,
• introduction of a non-linear probabilistic (Monte Carlo) methodology to define adequate cost contingencies for projects managed by ‘weak teams’,
• a practical case of the non-linear probabilistic (Monte Carlo) modeling,
• rough calibration of non-linear probabilistic (Monte Carlo) models that could be practically used for rule-of-thumb estimating of project cost outcomes in case of ‘weak teams’.