Why do mining projects exceed their capital budgets?

THIS week Allan Trench tries to answer one of his own mineral economics exam questions – within a 12 minute deadline.
Why do mining projects exceed their capital budgets? Why do mining projects exceed their capital budgets? Why do mining projects exceed their capital budgets? Why do mining projects exceed their capital budgets? Why do mining projects exceed their capital budgets?

 

Staff Reporter

Hallelujah: lecturing is over for another trimester with the participants on the Mining Industry Cost & Capital intensive course returning to their employers this week.

Unfortunately the task of marking assignments and exam scripts still lies ahead. So in wrapping up the course, your scribe thought he might take his own exam – or at least one question therefrom.

The last question (of 10) on the exam paper read simply “Why do mining projects exceed their capital budgets?”

Given that the exam ran to two hours that left those in the hot seats just 12 minutes to formulate a credible answer.

So with the stopwatch running, here is an attempt at a model answer. Each question had ten marks assigned to it – so to go for the bonus point here are eleven reasons relating to mining project cost overruns from the hip. Can you think of more?

Market optic. Companies do not like to surprise the market with high capital cost projects, so budgets released in scoping, prefeasibility and even definitive feasibility work can contain an inherent (even sub-conscious) bias towards under-calling costs to manage perception.

Time is money (financially). Scoping level assessments are completed many years before eventual project construction – with such studies seldom explicit as to whether the costs therein costs are real or nominal, and whether the scoping-level costs take into account for potential escalation in the intervening years towards the project’s final investment decision. Inflation is more prevalent than deflation – and real cost escalation more prevalent than real cost de-escalation. Numbers therefore naturally rise as time progresses – but with the first released number the one most often remembered by the market.

Time is money (practically). The multiple sources of non-discretionary delays in mining projects are hard to predict. At the construction stage time is literally money. The same mantra applies prior to construction too – although to a lesser extent. The first cost estimate (e.g at scoping stage) seldom fully accounts for the delays unearthed in pre-feasibility and final feasibility work – let alone actual construction and ramp-up.

Asymmetric estimation effects. Estimates that cite plus/minus a percentage are seldom symmetrical. The cost upside (cost overrun) is usually larger the downside side (cost underrun). The net effect of successive plus/minus ranges to project cost estimates from scoping through to final feasibility means that mathematically the final cost must be higher the first estimate.

Technical challenges. Even new large-scale projects where previous mining has previously been undertaken or where small-scale mining is ongoing can throw up unforeseen technical challenges during or prior to start-up. Ground conditions is one common issue here (think Oyu Tolgoi), as are processing challenges (think Windimurra closer to home).

Logistical challenges. Outside the geology, metallurgy and mining aspects of any project lie the logistical challenges – particularly in the bulk commodities. For example if your transport corridor passes through land held by 100 or more private landowners and through multiple shires (and for large projects even jurisdictions), it can takes just one squeaky wheel to cause a project headache.

Commodity price impacts. Rising or elevated commodity prices can drive up project costs. The reasons are several-fold – including a rational economic trade-off of having to spend more money to deliver the project quickly – else that key project components have risen in price specifically because of the additional demand created by a raft of new project developers. Conversely low commodity prices do not always guarantee a cheaper build. Take financing as one issue here. Low commodity prices can drive delays in successful financing, as the project economics are less attractive, with any time delay still correlated to project spend even when prices are low.

False economies. Total cost of ownership is a concept that is well known to industrial engineers but not always immediately apparent to cost estimators. Procurement of non-OEM price-discounted components of lower quality (that ultimately result in higher cost) is one example. Faced with buying component X for $180,000 or its inferior replacement Y for $100,000, the great temptation is to select the latter – but the former may actually be the better choice should the inferior component fail in start-up. Inevitably the inferior component will reside in the cost estimate.

Outright miscalculation. Simply getting the answer wrong is one source of cost overrun. Cost estimators are not infallible. The correctly estimation labour cost escalation is just one aspect that carries significant uncertainty.

Economies of scale drive increased absolute costs. As project definition progresses, economies of scale are typically identified thereby lowering costs right? Sort of. Economies of scale typically lower unit costs per tonne of metal, but not surprisingly also typically involve greater scale – driving up costs in absolute terms. Economies of scale nevertheless drive good outcomes; scope creep of a project, on the other hand, is not quite so good.

Project management issues. Experienced project builders are rare. There are not enough to go around. Even if the project cost estimate is “correct” it still needs to be managed well in order to be delivered to budget – and skilled project management is far from a given.

Of course there is always one other reason too: Murphy is alive and well.

Marks out of ten? I’ll give myself a seven as the 12-minute stop-watch alarm rang whilst scribbling commodity price impacts (bullet point 7 above). I fully expect that many other reasons will emerge by the end of reading through the exam scripts. How did you do?

Good Hunting.

Allan Trench is a Professor of Mineral Economics at Curtin Graduate School of Business and Professor (Value & Risk) at the Centre for Exploration Targeting, University of Western Australia, a Non-Executive Director of several resource sector companies and the Perth representative for CRU Strategies, a division of independent metals & mining advisory CRU group (allan.trench@crugroup.com).

This article first appeared in ILN's sister publication MiningNews.net.

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