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(EST-2328) Statistical Analysis of Parameters Influencing Capital Overruns on Mining Projects

Primary Author: Murray Pearson, P.Eng.
Co-Author(s): Connor Oughtred; Katherine Wong-Cameron, P.Eng.

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

Abstract: For more than 20 years, the mining and metallurgical sector has been plagued with a poor record of estimating initial capital costs. Capital overruns have been well documented both in the media and mining specific publications. In an effort to improve the quality and maturity of studies throughout the project lifecycle, this paper examines factors contributing to error and systematic bias in feasibility study cost estimates. Based on regression analysis of 98 mining projects completed from 1997-2015, project elements are identified to have a statistically significant impact on capital overruns. The importance of sufficient execution planning and schedule risk mitigation in the feasibility study will be highlighted, bridging the gap between cost estimation and execution. The proposed hypotheses and their explanations envelop elements that are both dependant and independent of project location. By complementing the aforementioned factors with an acute approach to execution planning and schedule risk mitigation, major project parameters and their influences can be better understood, thereby flagging serious flaws, or weaknesses that can mitigate the risk of capital overruns.