How can you use sensitivity analysis to evaluate mining projects?

1 What is sensitivity analysis?

Sensitivity analysis is a technique that measures how the output of a model or a system changes in response to variations in the input parameters. In mining projects, sensitivity analysis can help you to estimate the impact of changes in factors such as commodity prices, production costs, exchange rates, discount rates, ore grades, recovery rates, and environmental regulations on the net present value (NPV), internal rate of return (IRR), or payback period of your project. Sensitivity analysis can also help you to compare different scenarios and options, and evaluate the trade-offs and risks involved.

3 What are the benefits of sensitivity analysis?

Sensitivity analysis can provide several benefits for evaluating mining projects, such as understanding the behavior and performance of your model or system, exploring different scenarios and options, communicating and presenting project evaluation results, and improving your model or system. It can also help you to identify the key drivers and assumptions of your project evaluation, evaluate the potential outcomes and impacts of your project decisions, highlight the uncertainties and risks involved, and refine your input parameters and assumptions based on new information or feedback.

4 What are the limitations of sensitivity analysis?

Sensitivity analysis can be a useful tool for evaluating mining projects, but it can also have some limitations. It can be time-consuming and complex, especially when there are many input parameters and interactions involved. Additionally, it can be subjective and biased, depending on the choice of input parameters, ranges, methods, and tools. It can also be misleading or inaccurate if the input parameters or the model or system are not realistic or reliable. Furthermore, sensitivity analysis can be over-simplified or over-generalized if the output of the model or system is not sensitive to the input parameters, or if the sensitivity analysis does not capture the full range of uncertainties and risks.

5 How to improve sensitivity analysis?

To improve the quality and usefulness of sensitivity analysis for evaluating mining projects, you should define the objective and scope of your analysis, identify the input parameters and their ranges, choose the method and tool for sensitivity analysis, run the analysis and interpret the results critically, and communicate and present your results clearly. Align your analysis with the goals and questions of your project evaluation, base parameters on credible sources, validate results with other methods or sources, and acknowledge uncertainties and risks involved. Doing so can help ensure a successful sensitivity analysis.