WHY BUILDING AMINE ON BUDGET

IS RAREA STATISTICALANALYSIS

CIM MES Toronto 2014

Christopher Haubrich16 October 2014

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 costoverruns

• What the results actually mean

• Insight into the nature and underlying causes of capitalcost overruns

• Questions

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Common questions

1. What causes capital cost overruns?

2. Why have capital cost overruns been so consistent overthe past several decades?

3. Will the problem ever go away or self-correct?

4. What can be done to reduce capital cost overrun risk?

Note: capital cost overrun =

2

Actual capital cost

Estimated capital cost

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 miningindustry 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 largelyunexplained• Has not self-corrected in 50 years of recorded data

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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 notyet 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 wehad it right

• Also recorded other potentially important project characteristicsincluding• 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 weakassociation with percentage capital cost overruns

2) Those which showed a strong association withpercentage capital cost overruns

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No association orweak association

Strong association

Results

• No association or weak association between capital costoverruns and the following project characteristics:

Financing (external vs. internal sources)

Company size (as measured by market cap at feasibility andmarket cap at construction)

Project size (as measured by estimated capex, actual capex, andprocessing capacity)

Mining method, infrastructure requirements, and powerrequirements

Project location (by continent)

Primary commodity

Processing method

Project history (greenfield vs. brownfield)

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Results

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No association orweak association with

percentage capital cost overruns

Strong association withpercentage capital cost overruns

FinancingCompany sizeProject sizeMining methodInfrastructure requirementsPower requirementsProject locationPrimary commodityProcessing methodProject history

Results• Strong association between capital cost overruns and the

following project characteristics:

✔Commodity market “heat” at beginning of construction (asmeasured 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:CAPEXratio)➔ Marginal projects = larger overruns➔ Stronger projects = smaller overruns

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Results

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No association orweak association with

percentage capital cost overruns

Strong association withpercentage capital cost overruns

FinancingCompany sizeProject sizeMining methodInfrastructure requirementsPower requirementsProject locationPrimary commodityProcessing methodProject history

✔ Commodity market “heat” atbeginning of construction✔Integrated design/build teams✔ Project “quality”

Relationship #1: Commodity Market“Heat”

• Cost overruns increased as commodity prices rose anddecreased 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 builtand 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 moreimportant 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 marketheat is widely understood and does not typically erodeproject 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/BuildTeams

• Cost overruns were significantly lower in projects wherethe feasibility author and the EPCM team were the sameentity

• Theory: fewer informational gaps and more accountabilitywhen design and build teams are integrated

➔ Feasibility author same as build (EPCM) team = smaller overruns

➔ Feasibility author independent from build (EPCM) team = largeroverruns

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Relationship #3: Project Quality

• Marginally economic projects tended to have much higherpercentage capital cost overruns than projects with robusteconomics

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Project Quality Capital CostOverrun Risk

Relationship #3: Project Quality

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Capital Cost Overrun vs. Project Quality (log-log regression)

* Capital Cost Overrun Ratio = Actual/Estimated Capital Cost

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

-2 -1 0 1 2 3

lnC

CR

ln NPV:CAPEX

CCR vs. NPV:CAPEX - Before Tax

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

-2.5 -2 -1.5 -1 -0.5 0 0.5ln

CC

R

ln IRR

CCR vs. IRR - Before Tax

Relationship #3: Project Quality

• Projects with marginal economics are under morepressure to optimize their capital costs than projects withrobust 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 probablyresults in higher capital cost overrun risk due to over-optimization• 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

+

Quantities

+

Schedule

=-----------------------------------------------------------------

CAPEX

Estimated value

Distribution ofpossible values(uncertainty)

Target +/-15%

Estimated CAPEX

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“Good” Optimization

Costs

+

Quantities

+

Schedule

=-----------------------------------------------------------------

CAPEX

Result: Reduced CAPEX withunchanged risk of overrun

Good optimization

Good optimization

Good optimization

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Optimizing the Capital Cost Estimate

Costs

+

Quantities

+

Schedule

=-----------------------------------------------------------------

CAPEX

Estimated value

Distribution ofpossible values(uncertainty)

Target +/-15%

Estimated CAPEX

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Costs

+

Quantities

+

Schedule

=-----------------------------------------------------------------

CAPEX

“False” optimization

Before pressure

After pressure

Most likely actual CAPEX

Estimated CAPEX

Pressure

Result: Reduced CAPEX withincreased risk of overrun

False optimization

False optimization

False optimization

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Distribution of Capital Cost OverrunsF

req

uen

cy

Capital Cost Overrun Ratio (Actual CAPEX/Estimated CAPEX)

Over budgetUnder budget

1 21.5

Capital Cost Estimation: Proceed withCaution• 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

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Marginal RobustH

ot

mark

et

HighestRisk

Co

olm

ark

et

LowestRisk

Feasibility Base-case EconomicsC

om

modity

Mark

et

HeatIn

creasin

gR

isk

Increasing Risk

Conclusion

1. What causes capital cost overruns?

2. Why have capital cost overruns been so consistent overthe past several decades?

3. Will the problem ever go away or self-correct?

4. What can be done to reduce capital cost overrun risk?

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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 capitalcost estimate was generated• Hot market = typically higher overruns

• Marginal economics = typically higher overruns

• Smart management can help offset risks from externalfactors• Integrated design/build teams reduce average capital cost overruns

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Why Have Capital Cost Overruns BeenSo Consistent? Will They Ever Go Away?

• Pressure to advance a feasibility stage project toconstruction far outweighs the pressure to get the costsright• 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 ishard to change their minds (probably because they don’t have anybetter options)

• Typical result = capital cost overrun

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What Can Be Done?

• Risk identification Risk management Successfulproject

• 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 riskfactors contributing to capital cost overruns, but they ARE

• Common-sense business models such as integrateddesign/build teams can offset capital cost overrun risksthat are beyond control of management

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Questions?

chrish@jdsmining.com

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