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(EST-2223) Assessing Estimate Uncertainty using Monte-Carlo Simulations

Primary Author: Marie Peche
Co-Author(s): Julien Loron; M. Alexandre Farge

Audience Focus: Intermediate
Application Type: Research
Venue: 2016 AACE International Annual Meeting, Toronto, ON, Canada

Abstract: Assessing the uncertainty of a cost estimate can be a tricky issue. The AACE International’s classification of estimates provides guidelines to assess the relationship between the estimate accuracy and the level of project maturity, but provides no absolute standard range. Indeed, accuracy ranges differ depending on the type of industry concerned; even within a company, accuracy standards may vary from one department to another. Hence there is a clear need for an objective and analytical method to calculate the uncertainty of a cost estimate.

This paper therefore introduces a probabilistic approach based on Monte-Carlo simulations applied to technical and economic input data, providing a quantitative picture of the uncertainty range of a cost estimate. The method and concepts are illustrated through the example of a project from the energy production industry and the results are compared to the existing standards. The method developed in this paper can also be used to perform sensitivity analysis on parameters which may influence the estimate.