Monte Carlo simulation in platinum mine project evaluation

Abstract

ABSTRACT The purpose of this research is to explore and understand whether adopting a Monte Carlo simulation approach in evaluation of Platinum mine projects provides for better investment decision making in selection and approval of the projects. Mining projects are complex business opportunities and tend to be capital intensive. They are relatively risky and the business case attractiveness is influenced by many underlying natural, economic and physical uncertainties. While Discounted Cashflow (DCF) method with Net Present Value (NPV) and Internal Rate of Return (IRR) measures is one of the most commonly used evaluation methods in mining, adopting a Monte Carlo simulation to model uncertainties in calculating NPV and IRR can provide for a more realistic financial evaluation of the project. For the research, a sample of three Platinum mining project business case were analysed and the key parameters influencing the projects’ attractiveness were identified. A business case model for one of the project was developed in Excel. Monte Carlo simulation was done using @ Risk software with the respective distribution associated with those input parameters. The results were then analysed and presented to a mix of industry professionals from different disciplines. Qualitative input was collected to determine whether the simulated NPV and IRR results provide for better decision making than the NPV and IRR provided from the static DCF results. The survey results concluded that despite certain concerns regarding complexity in Monte Carlo model and lack of sufficient transparency in selecting the input parameter distributions, it still caters for better decision making in evaluation and selection of a business case. It provides decision makers with insight into the relevant uncertainties and their impacts on the business case. It helps managers appreciate the range of the impact of the input factors and allows them to identify mitigating levers to boost the value of the project’s return. It confirmed that, probabilistic simulation, if done correctly, can significantly improve the project evaluation process add to competitive advantage of the organisation. Note: The real name the projects has not been included in this research report. The Excel model developed for simulation used price sensitive information and hence

has not been shared with the research report. But the variability and probability distributions used has been depicted for analysis and conclusion.