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Volatility of factor costs (incl. CO2) and implications for the steel industry
May 23, 2013
CONFIDENTIAL AND PROPRIETARYAny use of this material without specific permission of McKinsey & Company is strictly prohibited
Presentation document
McKinsey & Company | 1
▪ Volatility of factor costs (incl. CO2)
▪ Why volatility matters
▪ What can be done to manage risk and capture upside
Contents
McKinsey & Company | 2
With the exception of energy in the 70s, volatility is at an all time high
across all commodity classes3
SOURCE: Grilli and Yang, 1988; Pfaffenzeller et al, 2007; World Bank Commodity Price Data; IMF primary commodity
prices; OECD statistics; FAOStat; UN Comtrade; MGI Analysis
Energy
One standard deviation2
Ave annual change in real price1
Percent
-60
-40
-20
0
20
40
60
Metals
-60
-40
-20
0
20
40
60
Food
-60
-40
-20
0
20
40
60
Agricultural Raw Materials
-60
-40
-20
0
20
40
60
1900
-09
10-
19
20-
29
30-
39
40-
49
50-
59
60-
69
70-
79
80-
89
90-
99
2000
-13
1900
-09
10-
19
20-
29
30-
39
40-
49
50-
59
60-
69
70-
79
80-
89
90-
99
2000
-131 Calculated as the arithmetic average of the annual change in prices across that timeframe
2 Calculated as the standard deviation of the commodity sub-index divided by the average of the sub-index over the timeframe
3 Data for 2013 are calculated as an average for the first 3 months od 2013
McKinsey & Company | 3
Merchant coke2 Scrap2 Raw material basket
PCI coal1
Coking coal1
(Aggregate hard, semi-soft)Iron ore1
(aggregate fines, lump, pellet)
0
50
100
150
200
250
0
100
200
300
400
0
100
200
300
400
Steelmaking commodity prices are highly volatile and declined
significantly over the last 2 years USD/metric ton, CIF Europe
SOURCE: McKinsey, SBB, AMM, EEX
0
100
200
300
400
500
600
0
200
400
600
800
0
100
200
300
400
500
600
Jan 01 Mar 13
Jan 01 Mar 13 Jan 01 Mar 13 Jan 01 Mar 13
Jan 01 Mar 13 Jan 01 Mar 13
1 Contract FOB prices + dry bulk oceanic freight
2 Spot prices European domestic
McKinsey & Company | 4
0
100
200
300
400
500
600
Raw material basket price
92123268
High commodity prices have aggravated effect of volatility
USD/metric ton, CIF Europex Yearly volatility1 Percent per year
SOURCE: McKinsey, SBB, AMM, EEX
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
FOR DISCUSSION
2012
86 13 10 13 4
1 Calculate as (standard deviation)/(average)
McKinsey & Company | 5
Carbon prices have fallen due to over allocation of allowances, the
economic slowdown and lack of policy intervention …
SOURCE: Point Carbon
0
5
10
15
20
25
30
35
40
€/tEUA phases II and III
EUA1 phase I
1 European Union Allowance, the tradable carbon allowance in the European Union Emission Trading Scheme (EU ETS)
EUA phase I price
collapse due to over
allocation and no
banking into phase II
EUA price fell first in
response to global
financial crisis, then
Eurozone crisis. Ability
to bank allowances
beyond 2020 and
prospect of policy
intervention keeps
price above zero
Vote in
European
Parliament
against back-
loading
allowances
2005 2006 2007 2008 2009 2010 2011 20132012
McKinsey & Company | 6
… and volatility has typically been in line with Brent Oil prices but started
deviating as of 201221-day historical volatility in Percent1
SOURCE: Point Carbon; Bloomberg (Bloomberg European Brent Blend Crude Oil Spot Price; Ticker: EUCRBREN Index)
0
5
10
15
20
25
30
35
40
2010 2012 2013201120092008
1 Calculated based on the standard deviation of the daily price change for a period of 21 days
Brent blend crude oil
EUA Phase II & III
▪ EUA prices 21-day historical volatility since January 2008 is not higher than Brent
▪ However, regulatory and economical shocks have changed the dynamics since July 2011 – Energy efficiency Directive proposal, Greek crisis, Euro recession
McKinsey & Company | 7
▪ Volatility of factor costs (incl. CO2)
▪ Why volatility matters
▪ What can be done to manage risk and capture upside
Contents
McKinsey & Company | 8
Economic uncertainties, variability of market prices, uncertainties in sales
volumes combined with existing usages leads to EBITDA uncertainty
SOURCE: McKinsey
Variability in futureEBITDA
EBITDA variability can lead to
▪ Periods with unexpectedly
large profits
▪ Periods with critical bottom-
line
▪ Higher volatility of overall
P&L (budget/ actuals)
SalesOperationsPurchasing
Scrap
EBITDA
Hurdle
FXP
El. powerP
PCI coalP
Merchant coke
P
Coking coal
P
CO2P
Iron oreP
Sales of steel products
P V
▪ Misalignments between sales and purchase contracts
– Timing
– Duration
– Inception
– Pricing mechanism
▪ Uncertainties in future sales volumes
▪ Storage and production management
V
V
PriceP VolumeV
P
McKinsey & Company | 9
RM delivery over 3 months
Steel production: Misalignment between purchasing and sales creates an
exposure …
SOURCE: McKinsey analysis
Exposure to raw material volatility
Contract type & resulting exposure
Operations
T=0 T+3 T+5
Raw material order Raw material delivery& Steel order
Steeldelivery
1.5 month Average 1.5 month
Average 2 months
QuarterlyRM contract
Costs plus margin :prices based on actual production costs plus constant margin
No exposure, as steel price defined according to the actual raw material prices
Locked-in prices :prices agreed at time of contract signature
3 months exposure, as steel price defined based on RM prices agreed 3 months earlier
Spot : Prices agreed at time of steel delivery
5 months exposure, as steel price defined based on RM prices agreed 5 months earlier
Steel order
Exposure to raw material price volatility will :▪ Increase EBITDA if raw material prices go up▪ Decrease EBITDA if raw material prices go down
1
2
3
Raw material basket prices (dependant on contract type)+ Constant transformation & fixed cost (205 USD/t)+ Constant operating margin (140 USD/t)
= Steel price
McKinsey & Company | 10
… that can be estimated at ~6 USD/ton EBITDA at risk per ton of steel
produced if raw materials basket price decreases by 10% (example)
SOURCE: McKinsey
Potential salescontract designs
Resulting risk exposure EBITDA at risk, USD per tonDescription
6
16
2
0
ROUGH
ESTIMATES
▪ Steel sold at actual commodity costs plus fixed transformation costs and constant margin
Costs plus margin
1
▪ Steel sold at commodity costs at the time of thecontract plus fixed transformation costs and constant margin, for a 6 month period
Locked-in prices
2
▪ Steel sold at commodity costs at the time of delivery plus fixed transformation costs and constant margin
Spot3
▪ 10% of cost plus contracts (e.g. internal sales)▪ 60% locked-in contracts (e.g. direct sales)▪ 30% spot contracts (e.g. through distribution)
Mix of contracts
4Equivalent to 9% of 2010 EBITDA (70 USD/ton)
Simulation, EBITDA/t exposure, USD per ton
McKinsey & Company | 11
▪ Volatility of factor costs (incl. CO2)
▪ Why volatility matters
▪ What can be done to manage risk and capture upside
Contents
McKinsey & Company | 12
How to manage risks from volatility
SOURCE: McKinsey
Reduce CO2
emissions
Take value-
chain
perspective
▪ Create transparency on exposure
▪ Define risk/return trade-offs along the
value chain (incl. aligning purchasing
and sales activities)
▪ Optimize operations to minimize GHG
emissions and, potentially, monetize
abatement
Develop CO2
regulatory
strategy
▪ Engage in constructive dialogue with
the regulator
▪ Increase share of funding for
breakthrough technologies
Levers applicable to raw materials and CO2
CO2-specific levers
McKinsey & Company | 13
Optimize risk/return trade-offs along the value chain
SOURCE: McKinsey
Procurement Warehousing,
transport & distribution
Production Sales
▪ Stock reduction
▪ Proactive stocking/destocking
▪ Freight hedging
▪ Carbon credit inventory
Markettransactions
Steelmaker
▪ Asset base flexibility
– Flexible production
– Optimal VIU of Raw Materials
▪ Value-added services
▪ Demand planning
▪ Pooled sourcing
▪ Upstream integration
▪ RM and CO2 market intelligence
NOT EXHAUSTIVE
▪ Centralized hedging
▪ Trading (incl. CO2)
▪ Contract portfolio management
▪ FX hedging
▪ Purchasing and sales alignment
▪ Contract design (CO2 cost transfer)
▪ Contract performance measurement
McKinsey & Company | 14
May JulMar Jun NovJan Feb DecApr Sep OctAug
Supply contract properties
▪ Construction/engineering –
quarterly/monthly or shorter
▪ Shipbuilding – yearly or longer
▪ Packaging – mainly yearly
contracts
▪ Appliance – mainly yearly
contracts
▪ Alloys – long plus short-term
▪ Electricity – more long-term
▪ CO2 – typically long term
Client contract properties
▪ Automotive – mainly yearly
contracts
▪ Scrap – mainly 1 - 3 months'
price surcharge
Understanding true volatility risk exposure and
maximizing value from mismatch of purchasing
and commercial contracts Contract duration
Price fixing
Negotiation phase
SOURCE: McKinsey
Misalignment between
purchasing and sales contracts
Purchasing
Commer-cial
ILLUSTRATIVE
McKinsey & Company | 1515
In practice, risk book approach is implemented
through an integrated software tool
SOURCE: McKinsey
Outputs
Sales contracts
Historical commodity price data
Process economics
Procure-ment
contracts
Simulation engine
Cash margin development
Predefined sensitivity and exposure
reports
Inputs
Contract structure
optimization tool
-500
0
500
1,000
1,500
2,000
2,500
Price decomposition
Fixed cost
Variable cash cost
Cash margin
▪ Historical analysis
▪ Forward-looking analysis
▪ Alternative contract structures
0
200
400
600
800
1,000
1,200
January 2014
January 2012
January 2010
January 2008
January 2006
January 2004
Example path
10% quartile
Scenario mean
90% quartile
Historical
McKinsey offers a solution
▪ Based on MS Access
▪ Enables quick diagnostic
▪ Easily customizable
Including
interface to
market data
(downloadable)
McKinsey & Company | 1616
Contract management and hedging can be
measures to ensure sustainable operating cash flows
SOURCE: McKinsey
σ Risk
Interest
&
Principal
Divi-
dends
Sustain-
ing
Capex
Ongoing
project
Capex
R&D and
marketing
investment
Probability
EBITDA +
cash
reserve
CashNeedsUSD
Hurdle
Expected
value
Operating
cash flow
distribution
Reshape to ensure strategi-cally "healthy" EBIT distribution
▪ Structural
changes in
business
▪ Contract management
▪ Hedging
ILLUSTRATIVE
McKinsey & Company | 17
Contract management – in contract design a variety
of dimensions should be considered
SOURCE: McKinsey
▪ Duration of contract
▪ Cycle times for renegotiation
Contract parameters
Volume
flexibility50%
90%
…
Spot
1 month
2 years
Index
Index
Fix
Fixed volume
Take or pay
…
Currency
USD
EUR
RUB
…
Zero
…
Three
Lag
▪ Time lags between commodity price point in
index of sales and procurement contracts
▪ Time lag between procurement of raw material and
delivery (e.g., to account for lead times)
▪ Prices indexed to single commodities or raw
material baskets
▪ Different denominations (currencies) for
procurement, but particularly sales contracts
▪ Flexible volume structures that allow customers
to adjust volumes within pre-defined boundary
conditions
Term
Sample types Comments Parameters
Iron ore
HRC
CO2
Freight
….
NOT EXHAUSTIVE
McKinsey & Company | 18
Steel sector is responsible for 8.0% of global GHG emis-
sions if indirect emissions are also taken into accountPercent, 2010e
1 Includes mining and beneficiation of iron ore, coal, limestone, and ferro-alloy ores
2 Production of Ni, FeCr, FeSi, FeMn, SiMn and Al consumed during steel production
Direct emissions
Indirect emissions
SOURCE: McKinsey steel CO2 model; Global McKinsey carbon cost curve 2.1
13.3
15.0
6.8
12.13.9
5.0
5.5
5.6
24.4
Agriculture
Forestry
Waste2.9
Building
Transport Other
industry
3.0
Chemicals
Cement
Petroleum
and gas
Steel (mining1
and ferro-alloys2)1.7
Steel (Direct)
Steel (Power)0.7
Power
Global CO2e emissions
100% = 49.4 GtCO2e per year
Steel CO2e emissions
100% = 4.0 GtCO2e per year
70
Ferro-alloys2
4Mining1
17
Power 9
Direct
McKinsey & Company | 19
8006004002000 1,000
300
250
200
150
100
50
0
-50
-150
-200
-250
Abatement potentialMtCO2e per year
2,2002,0001,8001,6001,4001,200
Abatement costEUR per tCO2e
-100
2007
Close to half of the abatement potential in the steel
industry has a negative abatement cost
Process change Energy efficiency Credits CCSRaw materials
INCLUDING STRUCTURAL
CHANGES AND BREAK-
THROUGH TECHNOLOGIES
SOURCE: McKinsey
▪ Five broad categories of abatement levers
– Energy efficiency (30%)
– Process change (20%)
– Carbon capture and storage (20%)
– Levers around raw materials (15%)
– Credits (15%)
CCS attractive
location
CCS unattrac-
tive location
Dry coke
quenching
Increased use
of pellets
Top gas
recovery
turbine (TRT)
McKinsey & Company | 20
Example energy efficiency levers: Steel industry can achieve 10-15%
energy cost saving with <2 years pay-back
25
Initiatives with no capex
Energy cost baseline
400
340
-15%
Improve-ment target
Initiatives with capex >2 mn
15
Initiatives with capex <2 mn
2084%
-17%
Improve-ment target
Other improve-ment levers
10%
Initiatives with capex < RMB 3.5 mn
2%
Initiatives with no capex
5%
Energy cost baseline
100%
SOURCE: McKinsey
Subsidiary of a leading Chinese steelmaker
Energy saving with payback < 2 years and implementation < 18 months USD millions
Energy saving with payback < 2 years and implementation < 12 months % in energy cost
An integrated steelmaker in North America
Saving 5% energy cost with no capex, and another 2% with limited capex
Saving 6% energy cost with no capex, and another 5% with limited capex
McKinsey & Company | 21
Example raw material levers: Iron ore linked
abatement opportunities
SOURCE: McKinsey
NOT EXHAUSTIVE
▪ Higher Fe grade reduces slag generation (SiO2 and Al2O3), and fuel rate
▪ Lower fraction of volatile impurities (Alkali's, Zn and Pb), reduces total fuel rate
▪ Lower fraction of reducable impurities (Mn, S and P) reduces the total fuel rate
▪ Lower moisture content reduces the total fuel rate
Blast furnace
- fuel rateB1
▪ Higher permeability of the blast furnace burden allows for replacement of coke
by PCI/natural gas/oils/coke oven gas (permeability of Pellets > Sinter > Lump)
▪ Higher sinter strength (higher RDI - mainly low Al2O3), reduces the coke rate
Blast furnace
- coke
replacement
(e.g., burden
permeability)
B2
▪ Avoidance of sintering saves ~ 60 kg of coke breeze consumption per ton of sinter
▪ Avoidance of pelletization saves ~ 0.7 GJ/ton of pellets
▪ Higher sinter strength (higher RDI, mainly driven by Al2O3) reduces fraction of
return fines, lowering coke breeze consumption
Raw material
preparationA
▪ Lower impurities (mainly Mn, S and P) reducing CO2 emissions during
steelmaking (e.g., desulphurization requiring CaC2, dephosphorization requiring
additional lime, removing Mn leads to additional oxygen consumption)
SteelmakingC
McKinsey & Company | 22
External financing is available for breakthrough
climate change initiatives
SOURCE: McKinsey
NOT EXHAUSTIVE
Research and
development
programs
▪ Regional/country funding of public private
partnerships aiming at developing a range of
breakthrough steelmaking technologies e.g.,
– ULCOS (Europe)
– COURSE50 (Japan)
– The Technology Roadmap (TRP) (US)
Funding of
carbon capture
and storage
▪ Regional/country subsidies for demonstration of
carbon capture and storage plants (CCS) and
innovative technologies. E.g.,
– “NER300” (Europe)
– Australian Carbon Capture and Storage Institute
(Australia)
– Fossil Energy’s Carbon Sequestration program
(Department of Energy; US)
McKinsey & Company | 23
Questions
SOURCE: McKinsey
Michel Van Hoey
Email: michel_van_hoey@mckinsey.com
Mobile: +32/477 480.165
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