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Competitiveness and challenges in the steel industry
OECD Steel committee74th session
Paris, July 1, 2013
CONFIDENTIAL AND PROPRIETARYAny use of this material without specific permission of McKinsey & Company is strictly prohibited
McKinsey & Company | 1
Disclaimer
While McKinsey & Company developed the outlooks and scenarios in
accordance with its professional standards, McKinsey&Company does not
warrant any results obtained or conclusions drawn from their use. The analyses
and conclusions contained in this document are based on various assumptions
that McKinsey&Company has developed regarding economic growth, and steel
demand, production and capacities which may or may not be correct, being
based upon factors and events subject to uncertainty. Future results or values
could be materially different from any forecast or estimates contained in the
analyses.
The analyses are partly based on information that has not been generated by
McKinsey&Company and has not, therefore, been entirely subject to our
independent verification. McKinsey believes such information to be reliable and
adequately comprehensive but does not represent that such information is in all
respects accurate or complete.
McKinsey & Company | 2
Contents
▪ Challenges in the steel industry –cyclicality and increasing competition from emerging economies
▪ Competitiveness of the steel industry
– beyond cost optimization
▪ Implications for enhancing competitive-
ness – few actions to launch and promote
McKinsey & Company | 3
The development of the industrial production index shows fundamental differences by region
0
100
200
300
400
500
600
Industrial production index – mature regionsPoints (based on 2005)
Years
China: 10.1% p.a.
Europe 1.5% p.a.
202019181716151413121110092008
0
50
100
150
200
250
19181716151413121110092008
Industrial production index – developing regionsPoints (based on 2005)
Years
Dev Asia +6% p.a.
2020
▪ China and Western Europe
are the dominant players in
global consumers
▪ While projections on China
are positive, mature regions
suffer from no growth
▪ Emerging regions follow a
growth trend line over the
next few years
▪ In all of those regions next to
GDP growth, some countries
have clear growth
stimulating drivers such as
energy and resources
Africa
MENA
Latin America
Europe (EU15)
North America
SOURCE: Global Insight; McKinsey
McKinsey & Company | 4
Within major steel economies macro-economic factors indicate uncertainty for demand and utilization
0
0,5
1,0
1,5
2,0
Debt GDP ratioIndex (based on 2005)
121110090807062005
GER
EU-15
China
US
2016151413
▪ Economically uncertain markets in traditional steel-consuming econo-mies
▪ China's economy stabilizes while the debt to GDP ratio in the US and EU-15 has been increasing steadily since 2008 in combination with strongly declining infrastructural investments
▪ In addition to weak GDP growth and higher debts, infra-structure investments in EU-15 countries have declined more than 30% between 2011 and 2012
0
1,0
2,0
3,0
4,0
Infrastructure spendingIndex (based on 2005)
EU-15
US
GER
China
2016151413121110090807062005
SOURCE: Global insight; McKinsey
McKinsey & Company | 5
Current projections based on consumption forecasts indicate a global slow-down
270 293 318 354 394 439
93106
120
94
113119
122125
128
153
148153
167172
176
7265
141
14
1,500
81
686
143
18
1,702
765
141
16
1,607
12
1,413
646
141
2010
1,306
India
China
Developed Asia
North America
Europe
2020
1,797
794
141
589
134
730
2.8% p.a.
3.5% p.a.
Other1
SOURCE: World Steel Association (WSA); McKinsey Steel Demand Model
Regional growthPercent p.a.
2010 - 16 2016 - 20
0
1
1
Share of ChinaPercent
45 46 45 4546 44
1
4
1
7
2
6
4
Apparent steel demand per regionMillion metric tons
1 Africa, other Asia, CIS, Oceania, MENA, Latin America
5 5
McKinsey & Company | 6
The steel industry is very volatile and with depressed profitability since 2008 – mature regions are losing in profitability
SOURCE: Bloomberg; McKinsey analysis
EBITDA marginPercent1
Average
NAFTA
Developed Asia
Europe
China
1 Based on a sample of 84 of the largest steel companies globally
▪ Margin develop-mentfollows a negative trend line
▪ Current situation worst for a long time
-5
0
5
10
15
20
25
30
040302012000 201211100908070605
2008 - 12: margin deterio-ration and leveraging
2000 - 03: price-margin squeeze
2003 - 08: margin improvement and
upstream integration
McKinsey & Company | 7
HRC value chain1 profit pool split evolution since 1995, USD billions
SOURCE: McKinsey Steel Model, McKinsey Mining Value Pools Model
Within the entire steel value chain, profitability is challenged and margins move to mining
815 17
44 46 42
11
81
100% =
Steelmaking(HRC)
Cokingcoal
Iron ore
2017
135
27
05
125
61
22
2000
23
78
7
1995
54
32
2011
230
26
28
10
156
35
22
1 HRC assumed to represent 85% of total hot-rolled flat products. Flat production assumed to use 85% of pig iron as raw materials. Assuming 1.6 t of
iron ore per tonne of pig iron and 0.5 tonne of coke per tonne of pig iron
▪ In the medium
term, the value
pool in steel will
remain in favor of
the raw material
producers
▪ There might be
shifts in between
years, but
demand and
supply for steel
combined with
cost for marginal
producers will
stabilize EBITDA
distribution
McKinsey & Company | 8
From a perspective on the EBITDA pool, emerging regions benefited most from the China-driven boom of the last decade
SOURCE: McKinsey (BMI Value Pools Model)
13
56
28
38
37
121
14
20121
164
2009
58
2007
136
42
2003
39
16
10
157
OECD steelNon-OECD steelMining
CAGR2003 - 2012
17%
33%
9%
-1%
HRC value chain EBITDA poolUSD billions
1 Based on preliminary estimates
McKinsey & Company | 9
Contents
▪ Challenges in the steel industry –
cyclicality and increasing competition
from emerging economies
▪ Competitiveness of the steel industry – beyond cost optimization
▪ Implications for enhancing competitive-
ness – few actions to launch and promote
McKinsey & Company | 10
Margin development in steel is a major issue, driven by external factors and plant situation
SOURCE: SBB, MEPS, McKinsey Flat Steel database
Typical factors driving/challenging competitiveness
Brazil
462460
922
Price Cost EBITDA
497256
753
EBITDACostPrice
2008 2012
Western Europe
698
255
953
EBITDACostPrice
622
35
657
Cost EBITDAPrice
2008 2012
Regional factors
and conse-quences
Intrinsicindustry
playeractions
Industry-wide
factors
Development of industry attractiveness USD per ton of HRC
1
▪ Supply balance
▪ CO2 and technology
challenges
▪ …
2
▪ Access to raw
materials/resources
▪ Fx-rate and cost
inflation
▪ Regulation
▪ …
3▪ Asset quality
and actions
▪ Operational
performance
▪ …
4
McKinsey & Company | 11
150100500
400
200
200
0
Cumulative capacity, Mt
900850800750700650600500400 550350300250
600
450
800
600400200
0
800
800600400200
0
Global HRC cost curve1, ex works, USD/t
SOURCE: McKinsey flat steel cost model; steel press; VDEh; WSA
1 Operating costs excluding SG&A, considering captive raw materials, standard utilization (90%)
2 90% of capacity
Q1 2013
Marginal manufacturer
2002
2017E
Marginal manufacturer2
1st quartileEurope
1st quartileEurope
Marginal manufacturer2
~ 47%
1st quartileEurope
~ 55%
33%
Globally competitiveness of some regions gets challenged through erosion of cost position – example Europe/Germany
1
German plants
Other
Europe 1st quartile
McKinsey & Company | 12
Global CO2e emissions Steel CO2e emissions
Percent, 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 Carbon Cost Curve 2.1)
1.7
Steel (Direct)5.6
Steel (Power)0.7
Power24.4
Forestry 15.0
Waste2.9
Building
6.8
Transport
12.1
Other
industry
3.0
Chemicals
3.9Cement
5.0Petroleum
and gas
5.5
Steel (mining1
and ferro-alloys2)
Agriculture
13.3
100% = 49.4 GtCO2e per year 100% = 4.0 GtCO2e per year
70
Ferro-alloys2
4Mining1
17
Power 9
Direct
2 Steel will remain a source of CO2 emissions which is a consequence of the process …
McKinsey & Company | 13
Total CO2 footprint
1.0
5%
33%
39%
8%
0.2
0.5
0.100.2
BF route
SOURCE: McKinsey Steel CO2 Model
▪ Technology
differences
between
integrated
route and
EAF route
result in
significant
emission
levels
▪ However,
input factor
salso change
EAF route
require
additional
power supply
BOFMining and raw material processing
Coke making
Sintering /Pelletizing
BF Downstream
Ferroalloyssmelting
Coke Fuel (includingoff-gas)
PCI coal Electricity Pig Iron Limestone Mining
0.20.2
0.8
3.4
43%
12%10%
6%4% 2%
21%
0.30.2
1.7About 0.50 for
transportation
of raw materials
not included
EAF route
About 0.18 for
transportation
of finished
products
not included
DownstreamMining and raw material processing
Pelletizing DRI making EAF
About 0.2 for
transportation
of raw materials
not included
Ferroalloyssmelting
ElectricityPig Iron & DRIMiningFuel (includingoff-gas)
About 0.2 for
transportation
of finished
products
not included
1 CO2 emissions linked to off-gas are allocated to the process step where the gas is used
2
Coke
… however, technology differences can lead to significant differences in emissions
McKinsey & Company | 14
▪ Commodity countries exposed to external factors
▪ Cost base for raw materials inflating
▪ The rationale that inflation results in devaluation does no longer seem to hold true
▪ Overall economics of raw material countries will challenge markets (higher cost makes steel less attractive)
SOURCE: Global Insight; OANDA; McKinsey
41
19
1515
BrazilAustraliaEurope1US
37
11
2
AUS/USD
REAL/USD
EUR/USD
Currency development of "commodity countries"
Exchange rate changes (2006 - 13) Percent
Price evolution
Consumer price index growth(2006 - 13)Percent
1 Eurozone countries
Some raw material supplying countries get challenged by appreciation of their currencies and cost inflation
3
McKinsey & Company | 15SOURCE: Ministério das Minas e Energia, Aneel, Economist Intelligence Unit, James F. King
Energy costUSD/MWh
Supply chain costUSD transport cost/t coking
coal
Labor costUSD/hour
46
180
+288%
20122003
12.0
+272%
20122003
3.2
17
11
+52%
20122003
Development of factor costs in BrazilMillion metric tons
Brasil shows how regionally attractivity of a production basecan deteriorated
3
McKinsey & Company | 16
1 Average applied MFN tariffs
2 In addition China, Russia, Ukraine, India, Guinea, Iran, Argentina, Kazakhstan, Pakistan, UAE and Vietnam impose export taxes
EXAMPLES
0
5
2
8
00
2
4
6
8
10
12
14
16
18
Import duties and taxes1
Percent
South
Africa
Turkey
2 - 17
12
India
5 - 7.5
China
3 - 10
Brazil
2 - 12
Finished iron & steel products
Semi-finished products
SOURCE: WTO, OECD, European Commission
Import duties for steel products Export barriers for raw materials
▪ Indonesia export
ban on iron,
except for miners
that build local
processing facili-
ties from 2014
▪ Bans on scrap
exports in Indo-
nesia, Mongolia,
Saudi Arabia, and
many other
countries2
20
Post 03/2011Pre 03/2011
5 - 10
Export duties, iron ore IndiaPercent Export bans
Also, import and export taxes influence competitiveness, while protecting or even taking away the need for continuous improvement
3
McKinsey & Company | 17
1,400
1,200
1,000
800
600
400
200
0
Year
201312111009080706052004
Capacitymt
2,200
2,000
1,800
1,600Non-OECD
SOURCE: McKinsey Crude steel capacity database
+720
OECD
+105
Due to low economic attractiveness new assets have been built manlyoutside OECD
4
McKinsey & Company | 18SOURCE: VDEh Plantfacts; Experts Estimate
Average converter size (TAB weight)
Average European steel plants, % of capacity
older 25 years Average US steel plantsAverage CIS steel plants
Average India steel plants
182t 204t 204t 217t 203t 236t 93t 139t
Age comparison BOF route
Assets had been ageing over time and lose potential structural advantages
4
18
2000
18
20132013
95
2000
77
92100
2000 2013 20013
81
2000
71
McKinsey & Company | 19
2,0001,5001,0005000
40
45
50
55
60
65
70
Average BF size, Ktpy
4,0003,5003,0002,500
15
20
25
30
35
Average BF age, years
0
5
10
SOURCE: VDEh Plantfacts; McKinsey
InlandSea portRiver portLocation:
▪ Majority of European blast furnaces have
– An average age of more than 35 years(not considering relines)
– An average blast furnace capacity of below 2 million tonnes
▪ Additionally, more than 60% of European BF plants have logistical disadvantages (located inland with either river port or rail access)
MarginalPoor Average
EUROPE EXAMPLE
Economical
challenged
In some regions the asset base calls for reviewing sustainability of assets and to be rebalanced
4
McKinsey & Company | 20
Greenfield3
▪ Once capacities are
offshored, there will
be no economies to
relocate quantities
back to Europe
▪ Greenfield plants of
new entrants will be
able to compete at
any price in Europe,
especially from
MENA
HRC costUSD/t Result
551 530 569672
59
Slab cost (incl.
Transport
to EU)
HRC
conversion
Depreciation2
Europe
4th quartile4
731
Brazil
688
5069
CIS
642
5161
MENA
603
28 24
In contrast greenfield plants can effectively compete against these low positioned plants in mature region – example Europe
SOURCE: McKinsey
1 Including EU exports; In HRC equivalent; includes HRC and all downstream products
2 Based on capex of 1,200 USD/t for integrated plant, 300 USD/t for EAF slab plant; 170 USD/t for HRC mill; depreciation period 20 years
3 Without captive raw materials
4 Incl. CO2 costs based on a CO2 price of 20 USD/t
MODEL RESULTS4
McKinsey & Company | 21
Contents
▪ Challenges in the steel industry –
cyclicality and increasing competition
from emerging economies
▪ Competitiveness of the steel industry
– beyond cost optimization
▪ Implications for enhancing competitive-ness – few actions to launch and promote
McKinsey & Company | 22
EU launched a programme to support steel industry
SOURCE: EU Commission
Regulatory framework
▪ Assessment of impact of existing and new policies and legislation on competitiveness
▪ Support sustainable steel production to boost demand and EU market share
▪ Fight VAT evasion and black markets in steel
Boosting demand▪ Promote steel end-use sectors, e.g., through simulating demand for alternative fuel
vehicles and renovation of buildings by energy and resource-efficient construction
Level playing field
▪ Ensure to eliminate or reduce tariffs and non-tariff barriers on third markets for EU steel
and raw materials
▪ Update anti-dumping and anti-subsidy regulations
▪ Monitor scrap markets and include coking coal in the list of critical raw materials
Energy, climate, resource policies
▪ Create regulatory environment conducive to sustainable growth (renewable energy,
impact of the ETS on electricity prices, energy efficiency)
▪ Support internationally binding agreements on climate change and GHG
Innovation
▪ Integrate steel industry into RDI programme for energy-efficient products
▪ Support R&D efforts for new technologies, and shift focus to up-scaling and pilots,
including steel/raw materials/recycling
Skills and restructuring
▪ Promote skills relevant to the steel industry going forward
▪ Work with member states and industry on alleviating impact of restructuring or plant
closures on local labor markets and societies
Programme elements
McKinsey & Company | 23
Competitiveness should be promoted in a focused way
SOURCE: McKinsey
Macro-economic initiatives to secure competi-tiveness
B
Company specificaction
▪ Monitor implications of competitive assets outside OECD which change the game, and reflect on unpredictable (opportunistic) tradeflows
▪ Promote industrialization levels with industrial GDP contribution and establish right incentives, permissions and timely execution
▪ Allow for consolidation in steel where possible and secure no more legacy assets remain kept up
▪ Secure level playing field to allow for sustainable production, e.g., to allow for environmental standards, avoid structural penalties and/or bottlenecks, e.g., in energy
▪ Discover market and customer opportunities for steel and adjust accordingly (specialized assets, productivity focused assets, depending on market opportunities), recognize substitution risks
▪ Optimize internal performance further and do some structural adjustments
A
McKinsey & Company | 24SOURCE: McKinsey "Lightweight, heavy impact"; advanced industries perspective 2012
15
38
5
12
9 12
Other non-
lightweight3
Steel (< 550 MPa)
HSS2
Aluminum
Magnesium
Plastics
Carbon fiber
2030
100%
20
13
5
0.5
2010
100%
19
52
Material mix in automotivePercent
67%
Lightweight29% share1
14
-70%
20302010
46
RoW
China
Europe
North America
2030
40
2010
11
+273%
Material demandin automotivemt
Steel HSS2
1 HSS, aluminum, magnesium, plastics, carbon fiber
2 High-strength steel (> 550 MPa)
3 Mainly other metals, glass, fluids, interior parts
▪ In applications, the profile ofsteel will change
– Need for light-weight appli-cations due to environmental requirements
– Need for high-strength steels for safety and power applica-tions
– Alternative solutions due to new power-train concepts (incl. BEV and hybrids)
– Feasible com-binations of high-strength structures and light panels
A In some applications, the profile of steel used will dramatically change and high value add grades will be increasing in importance due to light weight concepts
McKinsey & Company | 25SOURCE: MEPS Transaction Prices HRC; London Metal Exchange
1,000
500
20131211100908070605040302012000
2,500
3,000
3,500
2,000
1,500
Al is ~ 3.0 x steel price(2000 - 07)
Al is ~ 2.4 x steel price(2009 - 12)
Steel, European CRC
Aluminum, LME daily official
Averaged monthly price of steel and aluminumUSD per tonne
▪ Steel to aluminum spreads have been shrinking
▪ However, current gap between 2 raw materialsis over USD 1,200/tonne
A However, competitiveness of aluminum relative to steel has dramatically increased due to falling price differential …
McKinsey & Company | 26
251209
152
3054
20 156
110+41%
Net per part
costs
Increased
tooling
life
Additional
coatings/
post pro-
cessing
Increased
scrap
Net
material
cost
Lower
density of
aluminum
requires
fewer lbs
Higher per
lb landed
raw material
cost1
Price per
steel part
(indexed
to 100 for
mild steel)
Cost disadvantage in some
applications has reduced to less than 1 EUR/kg, thus provides a
real alternative
HIGH-LEVEL
ESTIMATES
SOURCE: Interviews; ISIS; SRI; The Aluminum Association; FKA Weight Reduction Report
Body panel example, high-strength steel (HSLA) to aluminum cost bridgeIndexed
A … with the result that after "cost in use" calculations the aluminum disadvantage is affordable and attractive
McKinsey & Company | 27
Specific dust emission Kg dust per t crude steel
Specific energy consumptionMetric ton coal equivalent per t crude steel
Accident rateNumber of accidents per million working hours
Specific CO2 emission (Average BF/BOF and EAF)Metric ton CO2 per t crude steel
SOURCE: Wirtschaftsvereinigung Stahl, plant facts, McKinsey CO2 model
1
0
-41%
2
1.5
0
-45%
2.5
2.0
0
2
4
6
8
10
-96%
0
20
40
60
80
-88%
1960 200770 200080 90
1960 200770 200080 90 1960 200770 200080 90
1970 2007200080 90
A Ongoing innovation has been a source for enhancing competitiveness
McKinsey & Company | 28
Capabilities of producing high value added products increase, withrequire producers in OECD countries to invest in more competiveness
= 100%224
-8.3%
EU-27 HDG
EU-27 CRC
RoW HDG
RoW CRC
2013
15%
5%
51%
29%
12
221
15%
5%
51%
29%
2010
205
15%
5%
49%
30%
05
152
18%
7%
46%
29%
2000
113
20%
8%
47%
25%
90% ofcapacities in"new world"
High value add capacity additions 2012 - 14 and capacity evolution 2000 -13kt
Loss ofshare EU-27
SOURCE: VDEh Plantfacts 2012; McKinsey Analysis
▪ Downstream steel production is signi-ficantly built up in emerging regions, with focus on value add
▪ Relevance of producers in mature world and therefore steel production in those regions is decreasing
▪ Steel mills need to have the funds to compete in these dynamic develop-ments
New HDG 8.2
New CRC 38.0
B
McKinsey & Company | 29
Less predictable trade flows require monitoring and countermeasures if the conditions do not match
Developed Asia-North
America
SOURCE: ISSB trade flow data base
13.911.3
6.07.2
20112006
Exports
12.214.7
10.511.6
China-Other developing
Asia
CIS-Western Europe
DevelopedAsia-China
23.712.9
DevelopedAsia-Otherdeveloping
Asia
16.820.7
CIS-MENA
6.37.6
4.56.4
Latin America-North America
Western Europe-North America
Major export flows 2006 and 2011Million metric tons (origin and destination region given)
Emergingobservations
▪ Productionflows due to regional imbalances change due to
– FX changes and cost advantages (e.g., Brazil)
– Country development combinedwith local consumption trends (e.g., Russia)
– Surplus capacity and change of addressable markets (e.g., Europe to US)
B
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