Download WHY BUILDING A MINE ON BUDGET IS RARE

CIM MES Toronto 2014
WHY BUILDING A
MINE ON BUDGET
IS RARE
A STATISTICALANALYSIS
Christopher Haubrich
16 October 2014
1
Agenda
• History of capital cost overruns in mining
• Project capital cost database
• Results from analysis
• Project characteristics not associated or weakly associated with
capital cost overruns
• Project characteristics strongly associated with capital cost
overruns
• What the results actually mean
• Insight into the nature and underlying causes of capital
cost overruns
• Questions
2
Common questions
1. What causes capital cost overruns?
2. Why have capital cost overruns been so consistent over
the past several decades?
3. Will the problem ever go away or self-correct?
4. What can be done to reduce capital cost overrun risk?
Actual capital cost
Note: capital cost overrun =
Estimated capital cost
3
Capital Cost Overruns: Serious problem,
long history, no explanation
• Capital cost overruns are significant and persistent
• Average overruns of 20%-60% recorded since 1965
• Mining industry has a worse record than other industries
• Merton (1988): Average overrun for mining = 1.99
• Oil refineries = 1.63; process plants = 1.67
• Many others have studied capital cost overruns in the mining
industry previously
•
•
•
•
•
Castle (1985)
Merrow (1988)
Bennett (1996) (Rothschild, now RCF)
Bertisen & Davis (2008) (RCF)
IPA (ongoing, but not just focused on mining)
• The capital cost overrun phenomenon is still largely
unexplained
• Has not self-corrected in 50 years of recorded data
4
Current State of Capital Cost Overruns
• Capital cost overruns are caused by a long list of factors:
• Poor engineering/planning
• Poor management/execution
• Poor weather
• Exchange rate fluctuation
• Inflation
• General industry trends
• Poor technical and/or management due diligence (for financers)
• But there are still things we do not understand or have not
yet acknowledged
• Evidence: 50+ year history of capital cost overruns in mining
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The Project
• Constructed database of 300+ mining projects completed
during the period 2005-2013
• Reduced the database down to 50 projects after many
iterations of checking and rechecking the data to ensure we
had it right
• Also recorded other potentially important project characteristics
including
•
•
•
•
•
•
•
•
project size
company size
project location
processing capacity
processing method
mining method
infrastructure requirements
and more…
• All data was gathered from public sources
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Data - A Representative Sample
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Results
• Analysis yielded two groups of project characteristics:
1) Those which showed no association or a weak
association with percentage capital cost overruns
2) Those which showed a strong association with
percentage capital cost overruns
No association or
weak association
Strong association
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Results
• No association or weak association between capital cost
overruns and the following project characteristics:
Financing (external vs. internal sources)
Company size (as measured by market cap at feasibility and
market cap at construction)
Project size (as measured by estimated capex, actual capex, and
processing capacity)
Mining method, infrastructure requirements, and power
requirements
Project location (by continent)
Primary commodity
Processing method
Project history (greenfield vs. brownfield)
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Results
No association or
weak association with
percentage capital cost overruns
Financing
Company size
Project size
Mining method
Infrastructure requirements
Power requirements
Project location
Primary commodity
Processing method
Project history
Strong association with
percentage capital cost overruns
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Results
• Strong association between capital cost overruns and the
following project characteristics:
✔Commodity market “heat” at beginning of construction (as
measured by a ratio of trailing commodity basket prices)
➔ Hotter markets = larger overruns
➔ Cooler markets = smaller overruns
✔Integrated design/build teams
➔ Feasibility author same as build (EPCM) team = smaller overruns
➔ Feasibility author independent from build (EPCM) team = larger overruns
✔Project “quality” (as measured by feasibility IRR or NPV:CAPEX
ratio)
➔ Marginal projects = larger overruns
➔ Stronger projects = smaller overruns
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Results
No association or
weak association with
percentage capital cost overruns
Financing
Company size
Project size
Mining method
Infrastructure requirements
Power requirements
Project location
Primary commodity
Processing method
Project history
Strong association with
percentage capital cost overruns
✔ Commodity market “heat” at
beginning of construction
✔Integrated design/build teams
✔ Project “quality”
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Relationship #1: Commodity Market
“Heat”
• Cost overruns increased as commodity prices rose and
decreased as prices fell
• Relationship based on mine cost data from 1965-2013
• Theory
• Short term effect: as commodity prices rise, so do costs of mine
inputs, especially those made of metal (mobile equipment, mills,
structural steel, etc.)
• Long term effect: as commodity prices rise, more projects are built
and increased competition for inputs drives up costs even further
• Result: Increased capital cost overruns
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Relationship #1: Commodity Market
“Heat”
• No standardized way to measure market “heat”, but
• Relative commodity prices and speed of change more
important to capital cost overruns than nominal prices
• $1200/oz gold today is considered a “cool” market, whereas that same price would
have been considered a “hot” market five years ago
• Relationship between capital cost overruns and market
heat is widely understood and does not typically erode
project value
• Revenue typically rises faster than costs in hot markets
• On net, costs increase but value is maintained or improved
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Relationship #2: Integrated Design/Build
Teams
• Cost overruns were significantly lower in projects where
the feasibility author and the EPCM team were the same
entity
• Theory: fewer informational gaps and more accountability
when design and build teams are integrated
➔ Feasibility author same as build (EPCM) team = smaller overruns
➔ Feasibility author independent from build (EPCM) team = larger
overruns
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Relationship #3: Project Quality
• Marginally economic projects tended to have much higher
percentage capital cost overruns than projects with robust
economics
Project Quality
Capital Cost
Overrun Risk
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Relationship #3: Project Quality
Capital Cost Overrun vs. Project Quality (log-log regression)
CCR vs. IRR - Before Tax
1.2
1.2
1
1
0.8
0.8
ln CCR
ln CCR
CCR vs. NPV:CAPEX - Before Tax
0.6
0.4
0.6
0.4
0.2
0.2
0
0
-2
-1
0
-0.2
1
ln NPV:CAPEX
2
3
-2.5
-2
-1.5
-1
ln IRR
* Capital Cost Overrun Ratio = Actual/Estimated Capital Cost
-0.5
0
-0.2
0.5
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Relationship #3: Project Quality
• Projects with marginal economics are under more
pressure to optimize their capital costs than projects with
robust economics
• For example, if first-pass economics yield 50% IRR, no optimization
required, but
• if first-pass economics yield 10% IRR, sharpen your pencils
• The data suggests that this extra pressure probably
results in higher capital cost overrun risk due to overoptimization
• The degree to which the estimate is biased is strongly correlated
with the economic quality of the project
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Optimizing the Capital Cost Estimate
Costs
Estimated value
+
Quantities
Distribution of
possible values
(uncertainty)
+
Schedule
=
----------------------------------------------------------------Estimated CAPEX
Target +/-15%
CAPEX
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“Good” Optimization
Good optimization
Costs
+
Good optimization
Quantities
+
Good optimization
Schedule
=
-----------------------------------------------------------------
CAPEX
Result: Reduced CAPEX with
unchanged risk of overrun
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Optimizing the Capital Cost Estimate
Costs
Estimated value
+
Quantities
Distribution of
possible values
(uncertainty)
+
Schedule
=
----------------------------------------------------------------Estimated CAPEX
Target +/-15%
CAPEX
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“False” optimization
False optimization
Costs
Pressure
+
False optimization
Quantities
Before pressure
After pressure
+
False optimization
Schedule
=
----------------------------------------------------------------Most likely actual CAPEX
Estimated CAPEX
CAPEX
Result: Reduced CAPEX with
increased risk of overrun
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Distribution of Capital Cost Overruns
Over budget
Frequency
Under budget
1
1.5
2
Capital Cost Overrun Ratio (Actual CAPEX/Estimated CAPEX)
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Capital Cost Estimation: Proceed with
Caution
• Over-optimization or “false” optimization happens more
often than it doesn’t
• Transcends entire mining industry
• Large projects (>$1B)
• Small projects (<$100M)
• Large companies (Market cap >$10B)
• Small companies (Market cap <$1B)
• All countries
• All commodities
• Greenfields and brownfields
• Most projects should be optimized, but optimized the
“good” way
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Capital Cost Overrun Risk Matrix
Feasibility Base-case Economics
Hot market
Cool market
Robust
Highest
Risk
Lowest
Risk
Increasing Risk
Increasing Risk
Commodity Market Heat
Marginal
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Conclusion
1. What causes capital cost overruns?
2. Why have capital cost overruns been so consistent over
the past several decades?
3. Will the problem ever go away or self-correct?
4. What can be done to reduce capital cost overrun risk?
26
What Causes Capital Cost Overruns?
• Poor execution? Poor due diligence? Bad weather?
Unforeseen exchange rate fluctuations? Labour strikes?
• Yes, but not the heart of the issue
• Most important factor: environment in which the capital
cost estimate was generated
• Hot market = typically higher overruns
• Marginal economics = typically higher overruns
• Smart management can help offset risks from external
factors
• Integrated design/build teams reduce average capital cost overruns
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Why Have Capital Cost Overruns Been
So Consistent? Will They Ever Go Away?
• Pressure to advance a feasibility stage project to
construction far outweighs the pressure to get the costs
right
• If something has to give it will be the risk level associated with the
cost estimate, not the forward progress of the project
• Once management decides they believe a project is viable, it is
hard to change their minds (probably because they don’t have any
better options)
• Typical result = capital cost overrun
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What Can Be Done?
• Risk identification  Risk management  Successful
project
• Risk identification is more difficult than it seems
• This is why Building a Mine on Budget is so Rare!
• Market heat and project economics are not often thought of as risk
factors contributing to capital cost overruns, but they ARE
• Common-sense business models such as integrated
design/build teams can offset capital cost overrun risks
that are beyond control of management
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Questions?
[email protected]