Mine management is often expected to make rapid evaluation decisions at different stages of projects based on limited and uncertain data. The challenge is exacerbated by having to distil technical complexity into a financial model that is usually designed to produce only one or two key indicators, eg net present value (NPV), internal rate of return (IRR). Mining is a complex environment with many sources of uncertainty ranging from sampling to economics._x000D_
In order to optimise investment decision-making, an appropriately structured evaluation framework must be utilised._x000D_
An evaluation framework should be designed to encapsulate and integrate the complexity across the evaluation cycle, ie sampling, resource estimation, mine planning and treatment, and financial and economic modelling. This complexity is diverse and ranges from sampling support, scale effects to understanding the impact of variability, uncertainty and flexibility on operational efficiency and economic viability. These complexities, combined with time and capital constraints, usually do not allow all facets of evaluation to be integrated into the model. The model must strike a balance between simplified estimation techniques and sufficient incorporation of aspects of the project that will make a material difference to the investment decision._x000D_
This paper demonstrates the impact of the scale of measurement on the valuation of a mineral project. Comparisons are made between global estimation averages using a top-down approach and local estimates using a bottom-up approach. Three sampling campaigns were conducted on a virtual orebody to compare the relative NPV accuracies. Stochastic forward models were run on foreign exchange rates and are compared with the results from a fixed foreign exchange rate model.