One of the requirements of NI 43-101 for Item 22 Economic Analysis is “sensitivity or other analysis using variants in commodity price, grade, capital and operating costs, or other significant parameters, as appropriate, and discuss the impact of the results.”
The result of this 43-101 requirement is typically the graph seen below, which is easily generated from a cashflow model. Simply change a few numbers and then you get the new economics. The standard conclusions derived from this chart are that metal price has the greatest impact on project economics followed by the operating cost. Those are probably accurate conclusions, but is the chart itself telling the true story?
I have created the same chart in several economic studies so I understand the limitations with it. The main assumption is that sensitivity economics are based on the exact same mineral reserve and production schedule.
That assumption may be applicable when applying a variable capital cost but is not applicable when applying varying metal prices and operating costs. Does anyone really think that in the example show, the NPV is $120M with a 20% decrease in metal price or 20% increase in operating cost?
Potentially a project could be uneconomic with such a significant decrease in metal price but that is not shown by the sensitivity analysis. Reducing the metal price would result in a change to the cutoff grade. This changes the waste-to-ore ratio within the same pit. So assuming the same the mineral reserve is not correct in this scenario.
These changes in economic parameters would impact the original pit optimization used to define the pit upon which everything is based. A smaller pit size results in a smaller ore tonnage, which may justify a smaller fleet and smaller processing plant, which would have higher operating costs and lower capital costs.
A smaller mineral reserve would produce a different production schedule and shorter mine life. It can get quite complex to do it properly.
Hence the shortcut is to simply change inputs to the cashflow model and generate outputs that are questionable but meet the 43-101 requirements.
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To be frank, this is one section of a 43-101 where I don’t bother wasting my time reading. Even metal price sensitivity can be distorted if the mine produces more than one product, which is more often than not the case. What I DO look at is the metal price assumptions, the capital cost estimate, the operating cost estimate, the resource estimate (for how tonnes and grade are calculated) and the estimated recoveries. If these factors are reasonable then the cash flows will likely be reasonable.
Most financial houses can supply metal price estimates, and one can develop a more or less “normal” distribution if one has 20 or more of them. It’s a simple matter then to decide how much risk to take on metal price. I generally drop back by one sigma to ensure my assumed price will be less than the consensus at least 83% of the time.
Grade and recovery have killed a lot of mines, so I pay a lot of attention to how the resource grade was determined and how much metallurgical work was done. Cash flow is very sensitive to these two factors. Issues such as the composite length, block size, geological constraints, etc need to be correctly determined for the orebody in question. Any sensitivity should include these factors.
Lastly, one needs to decide what discount rate is appropriate. Most operators would accept 8% in today’s world for an operating mine, but not for a project. Projects still carry significant risk, and therefore should be evaluated at a higher discount rate. If the project is at FS level a discount rate of 15% might be acceptable. At any earlier stage the discount rate should be even higher.
over at Jack’s site there was a very interesting discussion on decoupled NPV. (DNPV) by David Esponoza and Jeremy Morris. It’s worth reviewing their work to learn how they de-risk NPV.