Understanding the complex linkages between operational variables at a mine site and financial performance of that mine is now more critical than ever as operators deal with the slump in commodity prices. Even before the downturn, many of Australia’s leading mining companies had started to implement a more structured approach to cost effective decision making across all areas of mine production. This paper highlights Australian coal mining best practice in both operations cost management and production value maximisation through robust modelling of operational value drivers.

1. Finding cost efficiencies in mining operations
through effective value driver modelling
Aaron Carter, Brian Gillespie and Chris Gilbert
Performance Improvement Group, Brisbane
February 2009

2. © 2009 PricewaterhouseCoopers. All rights reserved. “PricewaterhouseCoopers” refers to PricewaterhouseCoopers, a partnership
formed in Australia or, as the context requires, the PricewaterhouseCoopers global network or other member firms of the network,
each of which is a separate and independent legal entity.

3. Introduction
Understanding the complex linkages between operational
variables at a mine site and the financial performance of that
mine is now more critical than ever as operators deal with the
slump in commodity prices.
Even before the downturn, many of Australia’s leading mining
companies had started to implement a more structured approach to
cost effective decision making across all areas of mine production.
This paper highlights Australian mining best practice in both
operations cost management and production value maximisation
through robust modelling of operational value drivers.

4. A. Return to cost efficiency
For the five years until mid 2008, most major mining However, prior to the credit crunch, and probably as
companies in Australia emphasised cost effectiveness early as January 2008, some of the more forward thinking
over cost efficiency, particularly in the areas of Australian mining companies were already preparing for
maintenance and transportation. Mining the largest an expected change in market conditions. At the mine
possible quantities of minerals as quickly as possible site level, this involved a change in emphasis towards
has been more important than minimising the cost of maximising the profitability per tonne of product with
key maintenance or production activities due to the high an increasing focus on reducing costs rather than just
prices available. Operational efficiency had in effect maximising the total tonnage mined and shipped at any
been compromised to varying degrees in the quest for cost. This renewed focus on achieving acceptable return
production volume to take advantage of high prices. on investment per individual mining asset has now taken
hold across the sector as mining companies once again
Large capital projects have the potential to destroy
begin to take a closer look at the cost of capital items and
substantial shareholder value during extended periods of
their operational and maintenance practices.
low prices. Anticipating an extended price slump, almost
all of the major mining companies around the world took a
critical look at their major capital expenditure plans towards
the end of 2008, clearly demonstrated by a significant
lessening of lead times for many categories of major
capital items. As commodity prices continue to slump and
demand scales back from the growth markets of India
and China, many mining companies have already deferred
specific major development projects and many more have
announced non specific scale back of aggregate capex
projects over the next five years (Aeppel 2008).
Figure 1: Buying power is moving back to mining companies as demonstrated by the significant decreases in asset lead times
over the past 12 months
Tyres
Wagons
Locomotives
Draglines
Power generators
Crushers
Grinding mills
0 5 10 15 20 25 30 35 40 45 50
Source: The Australian Financial Review and PricewaterhouseCoopers
Average delivery time Jan 2008
Average delivery time Jan 2009
2 Finding cost efficiencies in mining operations through effective value-driver modelling

5. B. Barriers to finding cost efficiencies
Understanding how operational levers drive the financial have been determined for one mine site, the cost drivers
performance of an individual mine is the key to cost for the same process may vary considerably at another.
efficiency and value optimisation. There are a number of Even the simplest mine operations will have unique aspects
barriers that will typically compromise the many different of their operation that must be taken into account when
types of projects that in some way are geared towards estimating costs.
improving cost efficiency. Very often the first symptoms
of project failure occur when target operational metrics Lack of tools
have been achieved with smaller than expected financial
improvement. Typically this situation will arise when the Another barrier to finding cost efficiencies is that the
relationships between operational metrics and financial mining industry traditionally has underinvested in tools to
results are not sufficiently understood. The primary barriers quickly and reliably assess the financial impact of potential
to finding cost efficiencies are that: mine improvement ideas. Although many mines have mine
planning, process optimisation and financial modelling
1. There is little understanding of the relationship tools, they tend to be non integrated or receive limited
between operational metrics and financial results data feeds from each other and are therefore used in
2. There is a lack of tools available to assist this isolation for scenario modelling purposes. Often the sheer
understanding quantity of operational data and the linkages between
data contained in these stand-alone tools can give a false
3. Operating performance and financial results are not
sense of reliance on the output even when the hierarchy of
sufficiently disaggregated
operational effect and financial result is incomplete.
4. There is a lack of accountability for financial
performance below senior management level.
These barriers will be discussed further in the context Figure 2: An integrated approach to operational modelling
of the Australian mining industry. links all key aspects of a mine
Little understanding of the relationship between
operational metrics and financial results
It is now almost 60 years since mining companies started Financial
Refining
using the same accounting principles that were used to Operations
measure the financial performance of the company to help
measure the performance of equipment and operational
processes (Hoyt 1950). However, understandably, few
mining companies expect their trained engineers to be able
to apply cost accounting principles to each of the possibly
hundreds of operational decisions they make every week. Mining
Geology
Operations
This lack of understanding can take a number of forms.
At the most basic level, process controllers with minimal
understanding of component costs may be given the
task of optimising a part of the production process. Even
when the cost components of the production process
are well understood over a certain range of variability, a
lack of understanding of the various inter-relationships
between cost components will usually lead to simplistic Supply Maintenance
& Availability
assumptions about the drivers of value. Most difficult of all
is that each mine site is unique in its combination of factors
such as plant layout, mineral ore body and proximity to rail,
road or port. Even if the cost drivers of a particular process
Finding cost efficiencies in mining operations through effective value-driver modelling 3

6. Many major mining companies have also attempted to In addition to poor disaggregation of financial information,
use data provided by their financial reporting system often operational drivers and financial outcomes will not
for mine planning purposes and the large Enterprise be included within the same reporting framework, or if
Resource Planning (ERP) vendors now all offer mine they are, the linkages will not be clear. Without appropriate
planning modules to help integrate financial information reporting of both financial and operational information,
at the mine site. The advantage of major ERP systems it can be difficult to understand why performance has
can be the depth of the financial data and the ability to been tracked in a particular manner. In many cases,
provide simultaneous multi-user capability. Many mining operators and superintendents do not have the ability to
companies are using their historical financial data from report which operational metrics drove throughput and
an ERP system to assist annual budgeting and annual financial performance. Without obtaining a full and accurate
production planning. However the standardisation understanding of operational performance and the resulting
required from financial reporting systems is a significant financial implications from lower level staff, it is very difficult
limitation when it comes to modelling the uniqueness of the for senior management to effect cost reduction initiatives
operational set up at a mine within the ERP system. within an operation with any degree of certainty.
This creates a problem for mining companies seeking to
prioritise cost saving initiatives from a portfolio of possible Lack of accountability for performance
projects. Many opportunities are not explored properly and The final impediment to achieving cost efficiency is a lack
are accepted or rejected on the basis of weak logic based of appropriate accountability for those operational metrics
financial modelling. Inevitably many such cost reduction that have the greatest impact on financial outcomes. A lack
initiatives fail to deliver the expected financial results due to of visibility of the linkages between operational metrics
the impact of other parts of the mining operation not being and a significant negative or positive financial variance
adequately taken into account. Even more worrying is that means that an operator will not be required to provide
some value optimisation activities are never considered an explanation of the variance appropriate to the level of
due to the time and effort required to evaluate financial impact. Accordingly, the operational staff that
them properly. may have the ability to heavily influence financial outcomes
through the way they conduct their day-to-day operations,
Reported operating performance is not are not being measured in a manner likely to change
sufficiently disaggregated behaviour to improve financial performance.
In some mining companies, another impediment Conversely, senior personnel that are being measured
to sufficiently understanding costs is that financial against financial outcomes may have little influence on
performance is often only reported at a consolidated (or sufficient understanding of) how their operational staff
level, or at a lower level based on the cost hierarchy and can assist them to improve performance. If the inter-
cost elements as defined in the chart of accounts. In relationships and linkages between lower level operational
many instances, the cost hierarchy does not sufficiently metrics and higher level financial indicators were clearer,
disaggregate costs in a manner capable of accurate cost then the organisation would have a better chance of
reporting across operational processes, ie by activity. developing a set of useful metrics for all staff to reward
Even if there is a close alignment between operations and successful financial performance.
cost centre reporting, this reporting often provides little
consideration to the level of value created from incurring
these costs.
4 Finding cost efficiencies in mining operations through effective value-driver modelling

7. C. Linking operations and finance
Extracting minerals from the ground and then selling those Mining companies must have a solid understanding of the
minerals in a global market may be a simple business operational levers that drive financial performance if they
model, but the cost components of that business are want to be able to quickly and cost effectively configure
huge, complex and inter-related. Additional value adding for required production. Building an accurate operational
processes such as even basic refining further confuse the model where all components of that model link to the
components of cost. predicted production cost is the most straightforward way
to combine operations and finance.
Many mining engineers still believe that the process of
extracting minerals from the ground is straightforward and The most useful operational models are those that replicate
that the fundamental quality of the mine determines that the full structure of operations and process logic at a mine
mine’s position on the cost curve. site, or extended operation. The best models provide a
cascading top down view of operations, linking high-level
This assumption fails to understand the scope for
financial outputs to the key operational drivers of those
optimisation in even the most basic of mine operations.
outputs such as production performance metrics and the
For example, even financially aware senior operations
disaggregated operating costs of each major process
staff will struggle to optimise single large basic cost
or asset.
components such as the effective manpower cost of a
changing shift pattern. How then can they be expected to
minimise the combined production unit cost of hundreds
of equipment assets over an extended time period in a
dynamic production environment?
Figure 3: High-level value driver logic for development activities at an underground coal operation
Financial Mechanical Parts ($)
Continuous Miners ($) +
+
Shuttle Cars ($) + Electrical Parts ($)
Development ($) +
Breaker Feeders ($) + General Consumables ($)
+
Labour ($)
+ Other ($)
Development
($/metre)
+
Production Speed
(metres/hr) Calendar Time (hours)
x
-
Calendar Hours (hours)
Development Scheduled Time (hours) Unscheduled Time
x (hours)
(metres)
Calendar Availability (%) / -
x Calendar Time (hours)
Idle Time (hours)
Production Time (hours)
Utilisation (%) /
Scheduled Time (hours)
Operational
Finding cost efficiencies in mining operations through effective value-driver modelling 5

8. These tools are primarily implemented to provide an return that capital expenditure will yield through improving
accurate and reliable insight into the key elements of operating performance. Proposed cost and productivity
value creation at the mine being modelled. They are used improvements are entered into the model for comparison
for predictive modelling, sensitivity analysis and variance against a baseline operating scenario. Based on these
reporting purposes. Over the longer term, they will start inputs, the value driver model can calculate expected
to educate, then influence management thinking and operating performance under different scenarios, and can
encourage a sharp focus on the key metrics that have the highlight the source of key performance variances.
biggest impact on the performance of the mine.
Predictive value driver models can become a valuable tool
for the quick evaluation and prioritisation of improvement
The power of predictive models opportunities. For example, questions that are often tested
Predictive value driver models are focused on evaluating through a predictive value driver model include:
the impact that alternative operating scenarios will have • Which capital investment options will have the biggest
on performance and modelling the core value drivers of impact on operational performance?
a mining operation. They show how changes in capacity,
leverage points and process inputs can influence • How will improving the reliability and availability of key
operational and financial results. The design of a predictive plant items impact the performance of the mine?
value driver model must allow the model, when populated, • What operational improvement initiatives will have the
to replicate the true factors underpinning the economics biggest financial impact?
of a mine. Production constraints, mine geology, mine
planning data, and the operating performance and Another common use for predictive value driver models
maintenance constraints of key assets are combined is to conduct comprehensive sensitivity analysis. The
with precise financial data to create a model capable of sensitivity of financial performance and mine production
mirroring mine performance. They differ to traditional mine volumes to each driver in the model is calculated and
planning, scheduling and optimisation tools due to the prioritised to highlight those elements of the mine that
emphasis placed on the financial implications of different create and destroy value.
operational scenarios. This knowledge empowers management and staff to
Predictive value driver models can be used to assess focus their time and resources on ‘where the money is’ to
the likely benefit of proposed operational improvement improve the performance of their mining operation.
and cost reduction opportunities, or predict the level of
Figure 4: Example sensitivity analysis highlighting the key operational drivers of financial performance
% change to EBIT
Value Drivers -1.00% -0.50% 0% +0.50% +1.00%
Longwall Idle Time
Longwall Operating Delays
Conveyor Maintenance Delays
Longwall Change - Out Time
Development Unit Cut Rate
EBIT impact of + 5% change
CPP Unscheduled Time in operational value driver
EBIT impact of -5% change
Development Idle Time in operational value driver
6 Finding cost efficiencies in mining operations through effective value-driver modelling

9. Jointly reporting finance and operations operating delays and unplanned maintenance of key assets
representing the lower operational levels of the value
Value driver models can also be used to report a driver model. A well constructed value driver model can be
combination of historical operational and resulting used as the basis of an accountability framework that can
financial performance data covering all aspects of a mining embed key performance metrics across an organisation.
operation. The key point of difference, from conventional
reporting mechanisms, is that the value driver model can One of Australia’s largest mining companies has
be used to present operating performance in a logical implemented such frameworks in a number of its mining
cascading model structure, disaggregating and refinery assets in Western Australia and Queensland,
high-level reported financial performance into the lower linking value driver models to business intelligence. Senior
level operational elements driving that performance. management meets with plant superintendents on a
monthly basis to examine a variance report, which requires
Reporting in this way can enhance the level of control input from all key areas of the operation. A negative
that management has over operations by providing variance on the model can be tracked to its source
transparency of the key drivers of monthly results. operational driver(s).
Managers can understand exactly which elements of the
mine have positively and negatively impacted reported
results, and the extent of this impact.
Figure 5: Example value driver reporting tool and accountability framework
Continuous Miners ($) Mechanical Parts ($/ROM t)
Cost ($) 754,201 738,722 Cost ($/ROM t) 0.762 0.754
Variance (15,479) -2.1%
+ Variance (0.008) -1.0%
+ Accountability Darryl Keating Shuttle Cars ($/ROM t) Accountability Mike Stapleton
Cost ($) 1.885 2.174
Shuttle Cars ($) x Variance 0.289 15.3% Electrical Parts ($/ROM t)
Cost ($) 420,715 487,002 Accountability Jason Stubbs Cost ($/ROM t) 0.459 0.443
+ Variance 66,287 15.8% + Variance (0.016) -3.5%
Accountability Geoff Price Development Production ($/ROM t) Accountability Daneil Cotters
Mine Development ($)
Cost ($) 2,141,219 2,160,346 ROM t 223,191 224,012
Variance 19,127 0.9% Breaker Feeders ($) Variance 821 0.4% General Consumables ($/ROM t)
Accountability Jason Stubbs Cost ($) 243,202 236,299 Accountability Jason Stubbs Cost ($/ROM t) 0.192 0.422
Variance (6,903) -2.8% Variance 0.230 119.8%
+ Accountability Sarah Smith
+
Accountability David Stanton
Labour ($) Lubricants ($/ROM t)
Cost ($) 723,101 698,323 Cost ($/ROM t) 0.218 0.212
Variance (24,778) -3.4% Variance (0.006) -2.8%
Accountability Jason Stubbs
+
Accountability David Stanton
Other ($/ROM t)
Cost ($/ROM t) 0.254 0.343
Variance 0.089 35.0%
Accountability Geoff Price
Developing an accountability framework
Key measures in the regular reporting pack can be Personnel accountable for negative variances must provide
assigned to appropriate personnel to create accountability an explanation and rectification plan for variances below
for performance. Management level personnel, such certain tolerances. There are two clear benefits to this
as superintendents, are typically made accountable for approach: first, operators and superintendents clearly
performance metrics higher up on the value driver model, understand the economic impacts of their operational area,
such as plant or major asset availability. and second, this granular level of visibility can be used
to motivate individual operators to improve the priority
Operators can be held directly accountable for the specific
operational metrics that they control.
metrics particular to their part of the process, such as
Finding cost efficiencies in mining operations through effective value-driver modelling 7

10. D. Modelling cost reduction
opportunities in turbulent times
In the current market conditions, many companies are reduction during a period of continued low commodity
undertaking urgent cost reduction programs to counter prices. A true cost improvement program for reduced
significant shortfalls in revenue due to price slumps and production levels requires sustainable cost reduction
slackening demand. Mines have already been closed over a longer period. This is particularly the case where
in Queensland and Western Australia where the cost of production levels may be substantially reduced for an
extracting the reserves significantly exceeds revenue extended period requiring a significantly altered cost
available under the forecasted commodity price. structure for the operation.
For many more mines in Australia, there will still be a lag Modelling scenarios of significantly lower production
between the drop in the market price available for near levels than recent levels is not straightforward. Production
term production and the input costs of that production. constraints can change significantly when the requirement
For some operators, there will be a transition period lasting for the number of major capital plant items such as power
well into 2009 of considerable reductions in revenue with generators, draglines or crushers is reduced in number
little drop in input costs under existing contracts. When but give rise to significantly higher asset utilisation. A
presented with shrinking or even negative margins, the flexible value driver model can calculate expected costs
options of implementing immediate measures such as under different production level and operating performance
turning off production, reducing headcount or delaying scenarios, even when historical cost data is not available
major capital expenditure must be considered. for the particular mine capacity configuration being
considered. Predictive value driver models can become
Whilst these measures are clearly necessary for some
significantly more valuable than mine planning tools using
mining operations, for other mines it will be important to
ERP cost data in such circumstances.
understand which levers will have the most impact on cost
8 Finding cost efficiencies in mining operations through effective value-driver modelling

11. E. Conclusion
Understanding the complex linkages between operational References
variables and the financial performance of a mine site
is now more critical than ever as operators deal with Aeppel, Timothy, December 2008. “Miners Cut Spending
the slump in commodity prices. This paper has sought in Half” Wall Street Journal Vol. 252
to highlight the importance of finding greater cost Charlton, S, May 2007. “Mining sector has to formalise
efficiencies by modelling the operational drivers of financial processes and systems to improve productivity” Mining
performance. Weekly Vol. 142
There are currently four barriers to finding greater cost Fordham, P, Jan 2004. “Mining Company
efficiencies through use of such initiatives. Performance Improvement Programs and
1. Little understanding of the relationships between Results — Summary of Benchmarking Study”
operational metrics and financial results. Plant Operators Forum 2004, Colorado
2. Lack of tools available. Hoyt, Charles D, September 1950. “Time Studies
and Cost Accounting increase efficiency at Titania”
3. Operating performance and financial results Mining Engineering Vol. 187
are not sufficiently disaggregated.
PricewaterhouseCoopers, 2008. “Aussie Mine* Reaping
4. Lack of accountability for financial performance below the rewards. A review of trends in the Australian mid-tier
senior management level. mining industry” Global Energy, Utilities and Mining
Several leading Australian mining companies have PricewaterhouseCoopers, 2008. “Global Mine*
implemented value driver models linking operations and Bulletin — May 2008: Cascading KPIs” Global
finance. Value driver models provide mining companies Energy Utilities and Mining
with four significant capabilities:
PricewaterhouseCoopers, 2008. “Mine* as good as it gets?
1. An understanding of the operational levers Review of global trends in the mining industry” Global
that drive financial performance. Energy, Utilities and Mining
2. The ability to jointly report on financial results
and the operational drivers of those results.
3. The ability to identify and prioritise cost
reduction opportunities.
4. An accountability framework to drive
financial performance.
Acknowledgements
This paper has been developed following insights gained
by PricewaterhouseCoopers while working on operational
improvement projects with Anglo Coal Australia, BHP
Billiton, Newcrest, Rio Tinto and Xstrata Coal.
Our special thanks to Xstrata Coal, Newcrest and BHP
Billiton who recently engaged PricewaterhouseCoopers
to work with them to develop value driver models at mine
sites and refineries in the Australian states of Queensland,
New South Wales and Western Australia.
Finding cost efficiencies in mining operations through effective value-driver modelling 9

12. About the authors
Brian Gillespie Chris Gilbert Aaron Carter
Partner Director Senior Consultant
Performance Improvement Performance Improvement Performance Improvement
Brisbane Brisbane Brisbane
T: +61 7 3257 5656 T: +61 7 3257 8126 T: +61 7 3257 8679
E: brian.gillespie@au.pwc.com E: chris.gilbert@au.pwc.com E: aaron.carter@au.pwc.com
Brian is a Partner with the Performance Chris is a Director with the Performance Aaron is a Senior Consultant in the Brisbane
Improvement Group in Brisbane, leading Improvement Group in Brisbane. He specialises Performance Improvement Group. He has
Strategy and Operation Improvement in operational improvement and cost reduction experience across a number of industries
assignments. In recent years, he has worked and has led multiple value driver modelling including resources, transport and logistics and
on large projects with organisations such as assignments. In recent years Chris has played utilities, with a specific focus on operational
Anglo Coal Australia, BHP Mitsubishi Alliance, a lead role on assignments with Anglo Coal, modelling, cost and revenue analysis and
Rio Tinto, Queensland Resources Council, the BHP Billiton, Dalrymple Bay Coal Terminal, operational improvement.
Queensland Rail Coal Division, Dalrymple Bay Queensland Rail Coal, Bulk and General Freight
Divisions, Queensland Resources Council, Rio Aaron has recently been heavily involved in
Coal Terminal and Xstrata Coal.
Tinto and Xstrata Coal. He has experience in a number of operational modelling projects,
Brian holds the degrees of BSc and MBA and coal, aluminium (bauxite mining and alumina with his experience including a value driver
is a Chartered Engineer with the Institute of refining), copper and iron ore. modelling engagement with Xstrata Coal and the
Engineering and Technology in the UK. development of financial forecasting and retail
Chris holds a Bachelor of Mechanical pricing models for Queensland Rail. He has also
He also sits on the Advisory Board of the Engineering from the University of Queensland recently delivered a project to identify the core
Brisbane Graduate School of Management at and an MBA from the Australian Graduate drivers of cost and value in the newly formed
the Queensland University of Technology and on School of Management, which he completed on South East Queensland bulk water sector.
the National Executive of the Chartered Institute exchange at the University of Chicago.
of Logistics and Transport, Australia. Aaron holds a Bachelor of Accounting and
Bachelor of Business (Information Systems) from
Central Queensland University where he was
awarded the Business and Law Faculty Medal on
graduation.
Australian Resources Team
Resources Industry Leader South Australia PricewaterhouseCoopers,
Michael Happell, Melbourne Andrew Forman, Adelaide Riverside Centre,
T: +61 3 8603 6016 T: +61 8 8218 7401 123 Eagle Street, Brisbane QLD 4000
E: michael.happell@au.pwc.com E: andrew.forman@au.pwc.com GPO Box 150, Brisbane QLD 4001
Australia
New South Wales Western Australia
Marc Upcroft, Sydney Mark Bosnich, Perth Office: +61 7 3257 8995
T: +61 2 8266 1333 T: +61 8 9238 3376 Facsimile: +61 7 3023 0936
E: marc.upcroft@au.pwc.com E: mark.bosnich@au.pwc.com Website: www.pwc.com.au
Queensland Victoria
Brian Gillespie, Brisbane Tim Goldsmith, Melbourne
T: +61 7 3257 5656 T: +61 3 8603 2016
E: brian.gillespie@au.pwc.com E: tim.goldsmith@au.pwc.com