August 2016

Productivity in mining operations: reversing the downward trend

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  • By Ajay Lala, Mukani Moyo, Stefan Rehbach and Richard Sellschop, McKinsey & Company

A new methodology for measuring mining productivity shows the industry’s performance is stabilising, and points the way to improving productivity more effectively

The surge in demand for metals and minerals during the 2000s quickly translated into much higher prices and profitability for mining companies. Boosting production volumes became the industry’s top priority, and it had considerable success, expanding global production of certain major commodities by 50 per cent or more over the past decade.

However, mining companies worldwide largely lost sight of the productivity goals that had underpinned operating discipline in the lean years of the 1980s and 1990s, when parts of the industry had set a healthy record in productivity improvement. As the demand boom gathered pace, cost increases related to expanding production got badly out of control.

With the end of the super-cycle and collapse in profitability, there is intense interest across the industry in reversing the excesses of the 2000s. CEOs have been acknowledging to investors that poor productivity performance must be addressed. In the meantime, governments in major mining countries are also trying to understand the productivity challenge, with publicly funded research institutions studying the issue closely.

But it is hard to improve something you can’t properly measure. Efforts to boost productivity have been hampered by the challenge of decoupling the factors mining managers can influence from those over which they have no control.

Managers in the industry have traditionally focused on labour productivity, which is typically measured in terms of the final product output – not the total material moved – per person employed. This fails to take into account how output might be affected by geological conditions, such as declining ore quality, or investment in equipment or spending on consumables such as tires or explosives. Similarly, the overall equipment effectiveness metric, commonly calculated from dispatch data about equipment operating time and delays, provides important insights about availability, utilisation and tempo performance, but is focused on component parts of the operation, such as shovels or a processing plant, rather than the whole operation.

Economists have also applied more advanced metrics such as total factor productivity (TFP). However, as the TFP approach measures output in terms of value added, it is handicapped in two important areas:

  1. it is unable to take account of changes in geological conditions such as ore grade quality
  2. it is affected by commodity prices, which are constantly moving.

In addition, these measures can’t separate the effect of rising input prices, such as fuel and explosives, from unnecessary consumption caused by process inefficiencies.

Measuring what really counts

To get a clearer picture of mining productivity trends, we have developed a new metric – the MineLens Productivity Index (MPI) – that enables mine managers to measure the aspects of productivity that are within their control, namely capital, labour and non-labour operating expenditure. The metric deliberately excludes a number of factors that can seriously affect productivity but are outside of management’s control. The first is the variable nature of ore grades and the depth of the orebody. These worsen and deepen as a mine is exploited, leading to rising extraction costs and falling output. Given that mining companies typically measure the output of the actual ore being mined rather than the total material moved, productivity measured in this way tends to be constantly in decline. Another important factor concerns more extensive regulatory requirements across the industry worldwide. These can directly or indirectly affect productivity but, again, lie largely outside of management’s control.

To calculate the performance index, the three elements of capital, labour and non-labour operating expenditure are linked with a measure of physical mine output, which is not affected by changes in the ore grade and stripping ratio. The basis for MPI is the well-established Cobb-Douglas production function equation used to measure productivity in national economies, which we have modified in such a way that it can measure the productivity of mining operations.

We have collected data from approximately 100 mines worldwide between 2004 and 2014 to create a picture of industry performance overall, sectoral performance and trends in major mining geographies.

An industry in transition

The picture that emerges is that the industry in aggregate has succeeded in stabilising its productivity performance over the past five years after a steep decline in the mid-2000s. Looked at over the past decade, mining productivity as measured by MPI has declined four per cent per year, meaning that mining companies are 30 per cent less efficient in digging and moving a ton of total material today than they were ten years ago.

Figure 1 also makes clear that 2009 marks a watershed in industry productivity performance. The MPI data suggest that over the 2009-14 period, the industry has more or less stabilised the downward trend in productivity, with MPI performance running on average at a positive 0.6 per cent per year over the five years, and showing an encouragingly upward trend in 2013 and 2014.

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We have also investigated in more detail how the four factors that drive productivity performance evolved over the 2004-2014 period (Figure 2). From 2004 to 2009, producers were trying to quickly increase production to meet demand growth in a time of rapidly rising prices. Control of operating costs was weak, and much of the production expansion was not efficiently executed. As a result, higher operating costs and capital spending contributed most to the decline in productivity before 2009.

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Commodity prices fell sharply in 2009 during the financial crisis and then rebounded. However, our analysis clearly shows that despite the price recovery, there was a major shift in the industry’s attitude to productivity. Between 2009 and 2014, labour spending rose at a slightly higher growth rate. Capital expenditure and operating expenses also continued to grow, but at a slower rate, particularly in the case of capital expenditure. Meanwhile, output expanded, and the combination of these changes led to a halt in the overall productivity decline.

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Analysis by geography and commodity shows a similar pattern to that of the mining industry overall (Figure 3). The pronounced decline in productivity between 2004 and 2009 is evident across the major mining geographies and different commodities, including copper and gold (Figure 3). This decline stands after adjusting for external factors such as mine cost inflation, including escalations in the prices of mine inputs such as fuel and explosives. Since 2009, the productivity trend has more or less stabilised. North America and Latin America have seen their productivity trend inch back into positive territory. Australia’s trend since 2009 is slightly negative, while sub-Saharan Africa has seen a further small decline. Similarly with the commodities, gold has moved back into positive territory but copper has seen a further small decline.

Addressing the industry’s productivity challenge

What is the way forward? To address the challenge of productivity improvement, miners will need to make moves on two levels:

  1. to achieve short-term gains
  2. to set their operations on the right course for higher long-run productivity performance.

On the first level, the way forward is clear. Our research identifies that capital expenditure and non-labour operating expenditure have been the main drivers of the productivity decline. Clearly, the industry has already started to work on this, with many companies already reining in capital expenditure and making moves to obtain more value-adding output from their asset base. Work also needs to continue on lowering non-labour operating expenditure, notably by improving procurement performance. Indeed, the improvements that are already starting to be seen in the MPI data point that way, with an upturn in productivity performance in some regions where capital expenditure has been reduced dramatically and where a number of large assets have come online and boosted output, while major efforts have been undertaken to drive costs out of operations.

Moving to the second level of actions, there are three important areas of focus to address the root causes of productivity decline.

Embed effective management operating systems at mines

Establishing such systems will create greater transparency on operations performance and identify areas for improvement. The operating systems should also free people and resources to focus on productivity and operational excellence and support effective performance management. This approach will help resolve what has been a long-standing challenge for many mining companies: making productivity performance (and its measurement) a priority. Operators have typically concentrated on improving one or two variables, such as reducing cost, lowering capital intensity or increasing throughput. However, a holistic focus on drivers of productivity that is shared at multiple levels is rare in mining organisations.

Prioritise operational excellence and capabilities development

Operational excellence implies a sustained focus on cost reduction and throughput improvement. This will require mining companies to shift away from the traditional approach of making occasional intensive drives for improvement and instead embed manufacturing systems and continuous improvement approaches in their organisations. This manufacturing-inspired approach focuses on standardised work and the disciplined execution of processes to improve performance over time. Particular areas for focus include elimination of waste, reducing variability and improving productivity of assets through advanced reliability and maintenance.

Improving productivity requires building individual and organisational capabilities. Many mining companies still consider productivity improvement the domain of a continuous-improvement department or a handful of Lean experts or Six Sigma black belts, rather than a core competence that should be embraced throughout the organisation.

Focus on innovation

Innovation and the adoption of breakthrough technologies could also help in the productivity battle, and the mining industry has room to raise its game here. In particular, digitisation offers several useful approaches.

One of the most accessible approaches is to draw insights from the data that mining companies routinely gather and then use them to forecast when a piece of equipment may fail. Estimating the probability of failure of specific components, rather than using a traditional time-based approach for scheduling their replacement, helps reduce maintenance spending and prevents interruptions that affect production.

At the same time, real-time data and better analytical engines are enhancing scheduling and processing approaches that can help maximise equipment utilisation and yields. In the mine pit, combining traditional dispatching with smart algorithms can optimise the efficiency of machine movements. In processing plants, applying new mathematical techniques that look for hidden relationships between second- and third-order variables can improve yields three to ten per cent within months. 

Digitisation also facilitates increased automation and mechanisation. Automated haulage and drilling have now been commercialised, while other technologies such as automated blasting and shoveling are in testing, making it possible to both reduce labour costs and the number of people working in the most dangerous areas.

To support these efforts, mining company management should encourage openness to trying new approaches and to adopting new technologies. For this to happen, it will require a broadening of the expectations of what operations leaders are responsible for and tighter integration with other corporate functions. It will also necessitate looking beyond the boundaries of the mining industry to seek inspiration from other industries’ successes. Partnering between mining companies and equipment and technology providers should also increase so that innovation in mining can succeed more broadly.

Mining commodity prices are volatile, and investors are currently unenthusiastic about the industry’s prospects. Nevertheless, we think the long-term supply-demand fundamentals of many important mining commodities suggest that companies that can cost-effectively raise their output will be rewarded. This means that the companies able to succeed in the race to achieve higher productivity will be among the biggest winners. The initiatives described in this article are important enablers of those productivity improvements. Combined with a commitment to monitor productivity performance, they will be an important factor in that race.  

Ajay Lala is a consultant in McKinsey’s Basic Materials Institute in Belgium. Mukani Moyo is a consultant in the Toronto office, Stefan Rehbach is a consultant in the Düsseldorf office and Richard Sellschop is an expert partner in the Stamford office.

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