volatility of factor costs (incl. co ) and implications ... · pdf filevolatility of factor...

Volatility of factor costs (incl. CO2) and implications for the steel industry

May 23, 2013

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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


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


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


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)


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


… 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





Contents


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


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


… 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





Contents


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


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


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


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)


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


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


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


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)


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


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


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)


Questions

SOURCE: McKinsey

Michel Van Hoey

Email: [email protected]

Mobile: +32/477 480.165

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