Misguided Objectives that Destroy Value

Although everyone is committed to the company’s success, it is common for different parts of a mining/mineral processing organisation to work to local subobjectives, such as maximising the size of the resource, maximising life-of-mine/operation, minimising mining costs, and maximising processing recoveries. Whilst being well-meant, these can be demonstrated in many situations to be counter-productive to the overall corporate objective of maximising value. The fact is that most planning decisions are linked in terms of the consequences they have on the overall outcome, so many complex trade-offs must be considered. A comprehensive, holistic approach should be taken to planning decisions, and this must be supported by the appropriate analysis. Addressing this is both a challenge and an opportunity for business planning and optimisation specialists. INTRODUCTION The observations made in this paper are based on the author’s experiences during optimisation studies involving over 15 mining and mineral processing companies during the last six years. The companies ranged from junior miners to divisions of the large, well-known mining houses. The behaviours referred to are certainly not universal, but have been observed on more than one occasion. The reason for challenging these behaviours is to promote, in the interest of furthering the objectives of the company, the understanding of the broad consequences of decision criteria that are too narrow. When undertaking optimisation studies for mining and mineral processing operations, it is not unusual to observe behaviours that reduce or limit the economic value of the business. These can occur due to the acceptance of certain simple subobjectives, which appear to be consistent with creating value or increasing viability, but which, with more insight, can be shown to be counterproductive. Misguided objectives have been observed at a range of levels, from departmental to corporate, and in several types and sizes of mining companies. The fact that this can happen is a reflection of the complexity of the mining and mineral processing industry, as well as the difficulty of running organisations involving wide ranges of specialists. This topic represents an opportunity for value enhancement that has not yet been comprehensively exhausted. The figures used here are based on a fictitious nickel operation. The geological model is a real lateritic deposit with some waste added on top, but is being treated as if it were a sulfide operation with a concentrator and smelter. This serves the purpose of numerical illustration. MAXIMISING THE SIZE OF THE DEPOSIT Original resource estimates are generally developed using fairly arbitrary mineral cut-off grades, based on industry standards or previous experience. This is inevitable, as resource estimates are usually made well in advance of detailed studies and the consideration of geo-technical, mining, and mineral processing, as well as market factors. The result is that terminology such as ‘two million ounces of gold’, or ‘100 Mt of ore above 0.8 per cent nickel’ is used to indicate the size of the mineral deposit. Note that the JORC code prescribes strict guidelines for the basis of ‘Resources’ and ‘Reserves’ statements. This paper refers to the more general internal process of project scoping and scaling, not the onerous topic of substantiating public announcements. The next step is likely to run Gemcom-Whittle (or another Lerchs-Grossman approach) using estimated slopes, recoveries, mining and processing costs, and metal prices. Depending on the level of confidence in the resource model and the various estimates, the contents of the resulting revenue factor = 1 pit shell using the marginal cut-off grade, may be regarded as the quantification of how much of the deposit is economic. Having a large deposit implies validity, viability, economies of scale, and intrinsic value. It can be argued that a large deposit supports obtaining finance and market valuations, perhaps rightly because it presents a wider range of future options, or perhaps wrongly because size is used as a surrogate for value in the absence of the proper analysis. It is therefore tempting to select a development option that involves large tonnages. For a given deposit, however, there is usually a significant difference between the maximum tonnes that are economic (if that means above break-even), and the tonnes that maximise the economic value. The issue becomes apparent when developing an optimal mining, processing and production plan. The following factors need to be considered: • The curve of cash value versus tonnage tends to be flat at the top (Figure 1). For example, it is common for the last third of the life-of-mine to be quite marginal. Whilst it is worth maintaining the option to operate during this period and in this part of the deposit in case prices, costs, or technology improve, this part of the resource should not be regarded as a core part of and driver of the project. • When the time value of money is taken into account, the outer shells of the revenue factor = 1 pit can be shown to reduce value, due to the fact that the cost of waste stripping precedes the margins derived from ore ultimately obtained. The effect of discounted cash flow means the discounted costs outweigh the more heavily discounted revenues. The optimal pit from a Net Present Value (NPV) viewpoint can be between revenue factor 0.65 and 0.95, depending on the deposit’s structure and the mining constraints (minimum mining width, maximum vertical advancement per year, and limit on total movement) and processing capacity. This can be seen where the peak of the discounted cash flow of the specified case is at a lower overall tonnage than the peak of the undiscounted total cash curve (also Figure 1). • When the cut-off grade is optimised and therefore raised in the early part of the schedule to maximise value (Lane, 1988), then the tonnage of material to be processed reduces further. Stockpiling may mitigate this (Figure 2). • If new capital expenditure is taken into account, and it is generally not in the pit optimisation process described above, then the hurdle for margin is increased further, disqualifying even more tonnes of seemingly economic material. All mine plans seek to exclude negative margin material (below the marginal cut-off grade, below break-even) as this obviously reduces value. The lower range of positive margin material should also be excluded as it will also dilute value, due to the above factors. Ken Lane published his work in 1988, but it still appears to take great courage for some managers to take this latter step, even when the analytical evidence is indisputable. There are therefore a number of reasons why the ‘optimal’ size of the mined deposit (ie maximum value as measured by NPV) is significantly smaller than the apparent ‘economic’ resource (which usually includes all material above the marginal cut-off Orebody Modelling and Strategic Mine Planning Perth, WA, 16 18 March 2009 97 1. MAusIMM, Managing Director, Whittle Consulting Pty Ltd, Suite 13, 333 Canterbury Road, Canterbury Vic 3126. Email: [email protected] grade). Presenting an optimal plan that only mines and processes perhaps 60 to 80 per cent of what was previously regarded as the economic resource can lead to disappointment. The resource geologist should not be left to determine the useful size of the deposit alone. Plans for how much of the resource should be mined and processed require proper consideration of a range of factors, including mining methods and constraints, downstream recoveries, costs, throughputs, capital and ultimate metal price outlooks, and the understanding of how these affect the outcome. MINIMISING MINING COSTS It appears obvious to want to minimise cost per tonne or cubic metre of the mining activity; this objective is often pursued by simplifying and regularising the mining operation. It is easy to agree that any opportunity to reduce fuel consumption, tyre wear, haul distances, etc for the same effective work completed is beneficial, as it will reduce costs. It seems to make sense to minimise total mining activity whilst maintaining sufficient feed to the plant. It is more difficult, however, to determine the total consequence of these mining decisions.