Adequate Quantification of Project Cost Risks: Introduction of Non-Linear Probabilistic (Monte Carlo) Technique

Literature on project management contains an abundancy of references to abnormally high project cost overruns as well as bitter complaints that modern risk quantification methods could not accurately predict project cost outcomes in many cases. This article provides a) an explanation of abnormally high project cost overruns, b) a link of risk quantification with ‘project team's quality' (team's strengths and weaknesses) and bias, c) an explanation why all currently used risk quantification Monte Carlo methodologies are relevant to ‘strong teams' only, d) introduction of a new non-linear probabilistic (Monte Carlo) methodology to define adequate cost contingencies for projects managed by ‘weak teams', e) a practical case of the non-linear (Monte Carlo) probabilistic modeling, and f) rough calibration of non-linear probabilistic (Monte Carlo) models that could be practically used for rule-of-thumb estimating of project cost outcomes.