1 SA Meat and the Global Market André Jooste Senior Manager: Market and Economic Research Centre,...

1

SA Meat and the Global Market

André JoosteSenior Manager: Market and Economic Research Centre, National Agricultural Marketing Council

13 March 2008

2

Structure of presentation

International overview Price trends in SA Consumption trends in SA Pointers Conclusions

3

World cattle producers

200

2,200

4,200

6,200

8,200

10,200

12,200

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014T

ho

usa

nd

Met

ric

ton

nes

USA Brazil China EU India Austrtalia SA

SA ave: 630 000 t

Source: FAPRI, 2004

4

World supply and demand for beef and veal

26 000

26 500

27 000

27 500

28 000

28 500

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

kt c

we

15

15.2

15.4

15.6

15.8

16

16.2

kg/c

apita

Production Consumption Per capita consumption

Source: OECD and FAO secretariats

5

World beef exports

0

500

1000

1500

2000

250019

95

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

Year

Th

ou

san

d to

ns

EU North America Oceanea Mercosur

Source: OECD, 2004

6

Imports projections (beef and veal)

200

400

600

800

1 000

1 200

1 400

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015('0

00 t)

Japan Mexico Russia South Africa South Korea

Source: FAPRI 2006

7

World trade projections (beef)

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000

10 000

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

('000

t)

World trade OECD Developing Least developed countries

Source: OECD and FAO secretariats

8

World beef trade flows, EU-12, 1990

25-5050-100100-150

150-200

200-300

300-400

> 400

Vloei in '000 t cwe

Based on GIRA figures

92

195

116

393

126

134

98

33

Source: Spanghero, 2002

9

World beef trade flows ,EU-15, 1995

117

313

73

597

64

205

172

49 60

25-5050-100100-150

150-200

200-300

300-400

> 400

Vloei in '000 t cwe



10

World beef trade flows, EU-15, 2000

29

155

35

317

48

60

112

279

39 25

25-5050-100100-150

150-200

200-300

300-400

> 400

Vloei in '000 t cwe



11

World beef trade flows, AU/NZ - 2005

12

World beef trade flows, EU and North America - 2005

13

World beef trade flows, S.Am - 2005

14

World beef trade flows,2005 (GMC)

16

Per capita consumption 2006 vs 2016

0

10

20

30

40

50

60

70

Argentina

US

A

Brazil

Australia

Canada

New

Zealand

Mexico

EU

-25

Russia

South

Africa

kg/p

er

2006 2016

Source: FAPRI, 2007

Decline

17

Results - Beef finishingPurchase prices (US$ per 100 kg live weight)

0

100

200

300

400

500

600

700

800

900

AT-2

5FAT

-35

AT-1

20AT

-150

T

DE-2

30DE

-260

DE-2

80DE

-800

DE-5

25T

FR-4

5FR

-70

FR-9

0AFR

-90B

ES-6

30ES

-940

ES-6

790

IT-9

10IT

-288

0T

IE-1

85

UK-3

5UK

-90

UK-9

8

SE-1

40SE

-230

T

PL-1

2PL

-30

CA-9

600

US-7

200

AR-8

00AR

-220

0

BR-1

40BR

-240

BR-3

40BR

-600

CN-3

00CN

-940

AU-2

7K

ZA-7

5K

Calf price Weaner price Backgrounder price

18

Results - Beef finishingShort and medium term profitability (US$ per 100 kg carcass weight)

-400

-300

-200

-100

0

100

200

AT-2

5FAT

-35

AT-1

20AT

-150

T

DE-2

30DE

-260

DE-2

80DE

-800

DE-5

25T

FR-4

5FR

-70

FR-9

0AFR

-90B

ES-6

30ES

-940

ES-6

790

IT-91

0IT-

2880

T

IE-18

5

UK-3

5UK

-90

UK-9

8

SE-1

40SE

-230

T

PL-1

2PL

-30

CA-9

600

US-7

200

AR-8

00AR

-220

0

BR-1

40BR

-240

BR-3

40BR

-600

CN-3

00CN

-940

AU-2

7K

ZA-7

5K

Short-term: Total returns less cash cost

Medium-term: Total returns less cash cost+depreciation

19

Background: Evolution of the industry The major transition periods:

Opportunity driven (1970s) Production driven (1980s) Cost driven (1990s) Consumer driven (2000 -)

Liberalization in 1995Deregulation in 1997

- Beef industry already started in 1992

IS IT GOOD ENOUGH TO BE CONSUMER ORIENTATED??

20

Price trends

Source: AMT

Prices of different meat types

0500

100015002000250030003500

Oct

-03

Jan-

04

Apr

-04

Jul-0

4

Oct

-04

Jan-

05

Apr

-05

Jul-0

5

Oct

-05

Jan-

06

Apr

-06

Jul-0

6

Oct

-06

Jan-

07

Apr

-07

Jul-0

7

Oct

-07

Months

c/kg

Clas A2/A3 lamb Class A2/A3 beefPorkerprice Fresh chicken

21

Price trends – focus on beef

Source: DoA, 2008

0

200

400

600

800

1000

1200

1400

1600

1800

2000

19701971197219731974197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007

c/kg

0

5

10

15

20

25

30

Kg

per

capi

ta

Real price Nominal price Per capita consumption

22

Weaner and A2/A3 carcass prices

Source: AMT, 2007

500

700

900

1100

1300

1500

1700

1900

2100

2300

Jan-02

Apr-02

Jul-02

Okt-02

Jan-03

Apr-03

Jul-03

Okt-03

Jan-04

Apr-04

Jul-04

Okt-04

Jan-05

Apr-05

Jul-05

Okt-05

Jan-06

Apr-06

Jul-06

Okt-06

Jan-07

Apr-07

Jul-07

Oct-07

c/kg

Weaner A2/A3 carcass

23

Price trends

Source: DoA

0

50

100

150

200

250

300

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Year

Ind

ex

20

00

=1

00

PPI-Summer grains PPI-Cattle slaughtered

PPI-Sheep slaughtered PPI-Pigs slaughtered

FRPI-Fuel FRPI-Animal health and crop protection

More or less in balance

Increased volatilityPeriod of significant gains and losses

24

Producer share in the retail price of rump

y = -0.0059x + 38.082

25

27

29

31

33

35

37

Sep-99

Dec-99

Mar-00

Jun-00

Sep-00D

ec-00

Mar-01

Jun-01

Sep-01

Dec-01

Mar-02

Jun-02

Sep-02D

ec-02

Mar-03

Jun-03Sep-03

Dec-03

Mar-04

Jun-04

Sep-04D

ec-04

Mar-05

Jun-05Sep-05

Dec-05

Mar-06

Jun-06

Sep-06D

ec-06

Mar-07

Jun-07Sep-07

Dec-07

%

Producer share in retail price Trend

Source: STATSSA & own calculations

25

Producer share in the retail price of sirloin

y = 0.0158x + 12.258

25

27

29

31

33

35

37

39

Sep-99D

ec-99M

ar-00Jun-00Sep-00D

ec-00M

ar-01Jun-01Sep-01D

ec-01M

ar-02Jun-02Sep-02D

ec-02M

ar-03Jun-03Sep-03D

ec-03M

ar-04Jun-04Sep-04D

ec-04M

ar-05Jun-05Sep-05D

ec-05M

ar-06Jun-06Sep-06D

ec-06M

ar-07Jun-07Sep-07D

ec-07

%



26

Producer share in the retail price of topside

y = 0.005x + 35.668

35

37

39

41

43

45

47

49

Sep-99D

ec-99M

ar-00Jun-00Sep-00D

ec-00M

ar-01Jun-01

Sep-01D

ec-01M

ar-02Jun-02Sep-02D

ec-02M

ar-03Jun-03Sep-03

Dec-03

Mar-04

Jun-04Sep-04D

ec-04M

ar-05Jun-05Sep-05D

ec-05

Mar-06

Jun-06Sep-06D

ec-06M

ar-07Jun-07Sep-07D

ec-07

%



27

Producer share in the retail price of brisket

y = -0.013x + 72.256

45

50

55

60

65

70

Sep-99

Dec-99

Mar-00

Jun-00

Sep-00

Dec-00

Mar-01

Jun-01

Sep-01

Dec-01

Mar-02

Jun-02

Sep-02

Dec-02

Mar-03

Jun-03

Sep-03

Dec-03

Mar-04

Jun-04

Sep-04

Dec-04

Mar-05

Jun-05

Sep-05

Dec-05

Mar-06

Jun-06

Sep-06

Dec-06

Mar-07

Jun-07

Sep-07

Dec-07

%



28

Producer share in the retail price of chuck

y = -0.0291x + 89.771

40

45

50

55

60

65

Sep

-99

Dec-9

9

Mar-0

0

Jun

-00

Sep

-00

Dec-0

0

Mar-0

1

Jun

-01

Sep

-01

Dec-0

1

Mar-0

2

Jun

-02

Sep

-02

Dec-0

2

Mar-0

3

Jun

-03

Sep

-03

Dec-0

3

Mar-0

4

Jun

-04

Sep

-04

Dec-0

4

Mar-0

5

Jun

-05

Sep

-05

Dec-0

5

Mar-0

6

Jun

-06

Sep

-06

Dec-0

6

Mar-0

7

Jun

-07

Sep

-07

Dec-0

7%



29

Consumption trendsTotal and per capita consumption of beef

300

400

500

600

700

800

9001970/7

1

1972/7

3

1974/7

5

1976/7

7

1978/7

9

1980/8

1

1982/8

3

1984/8

5

1986/8

7

1988/8

9

1990/9

1

1992/9

3

1994/9

5

1996/9

7

1998/9

9

2000/0

1

2002/0

3

2004/0

5

Year

Th

ou

san

d t

on

s

10

12

14

16

18

20

22

24

26

kg

per

cap

ita

Total consumption of beef Per capita consumption of beef

Source: DoA

30

Consumption trends (…continue)

Source: DoA

Total and per capita consumption of white meat

0

200

400

600

800

1,000

1,200

1,4001970/7

1

1972/7

3

1974/7

5

1976/7

7

1978/7

9

1980/8

1

1982/8

3

1984/8

5

1986/8

7

1988/8

9

1990/9

1

1992/9

3

1994/9

5

1996/9

7

1998/9

9

2000/0

1

2002/0

3

2004/0

5

2006/0

7

Year

Th

ou

san

d t

on

s

0246810121416182022242628

kg

per

cap

ita

Total consumption of white meat

Per capita consumption of white meat

31


Source: DoA

Total consumption white meat and red meat

0

200

400

600

800

1,000

1,200

1,4001970/7

1

1972/7

3

1974/7

5

1976/7

7

1978/7

9

1980/8

1

1982/8

3

1984/8

5

1986/8

7

1988/8

9

1990/9

1

1992/9

3

1994/9

5

1996/9

7

1998/9

9

2000/0

1

2002/0

3

2004/0

5

2006/0

7

Year

Th

ou

san

d t

on

s

Total consumption of white meat

Total consumption of red meat

32


Source: DoA

Per capita consumption of white meat and red meat

05

101520253035404550

1970/7

1

1972/7

3

1974/7

5

1976/7

7

1978/7

9

1980/8

1

1982/8

3

1984/8

5

1986/8

7

1988/8

9

1990/9

1

1992/9

3

1994/9

5

1996/9

7

1998/9

9

2000/0

1

2002/0

3

2004/0

5

2006/0

7

Year

Kg

per

cap

ita

Per capita consumption of red meat

Per capita consumption of white meat

33

Short term trends

Beef prices are high and will most probably remain firm Aren’t we lucky??

Consumption on the up, i.e. total and per capita

Alternative scenario: Prices low Consumption on historical

downward trend (prior to 2000)

We know the end result!!

0

200

400

600

800

1000

1200

1400

1600

1800

2000

19701971197219731974197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007

c/kg

0

5

10

15

20

25

30

Kg pe

r cap

ita

Real price Nominal price Per capita consumption

34

Let’s look at this from another angle Red meat industry realized that much must be done

to change the image of red meat R&D on consumer behaviour Promotion Competitions

However, a closer look shows: Total per capita red meat consumption more likely to be

23.96kg Beef down to 15.73kg, Pork down to 3.27kg, Sheep down to 3kg.

Turn around in macro-economic conditions (Econ growth) Mainstreaming economic activity of blacks (“black

diamonds”)

35

Composition of food and non-alcoholic beverages

Source: IES 1995, IES 2000, IES 2005/06

36

Time to rethink our orientation??

Although the industry transformed with positive results one can safely postulate that being consumer orientated (in theory) is not sufficient It falls short of international developments in agro-

food chains.

37

Some pointers: Factors determining buying decisions Factors determining beef buying decisions

are changing Economic vs non economic factors This is the trend internationally

38

Desirable characteristics of beef USA(1=extremely desirable; 5 = not at all desirable)

0 0.5 1 1.5 2 2.5 3 3.5

Organic/natural Fat content

ConvienienceRaised in Your region in the US

Environmentally friendly prod

Source assuranceMarbling

Coutnry-of-origin labelingNutritional value

TenderHigh Quality Grade

LeannessPrice

Colour

USDA unspected for safetyFreshness

Sitz, Calkins, Umberger, Feuz -U of Neb., 2004

39

Desirable characteristics of beef Japan

89

81

72

70

59

52

47

46

41

39

Safe

HGP/Che

mica

l free

Delicio

us

Juicy

Reaso

nable

pric

e

Availa

bility

Tende

r

Non fa

tty

Nutrit

ional

0 20 40 60 80 100 120

% of consumers surveyed

Purch

ase

with co

nfide

nce

Source: MLA

40

Importance of product attributes per Cluster - (Free State Province)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

Attributes

Scal

e of

Impo

rtnac

e

Inferior Conumer (low nutrition) (34.8%) n = 282 At Home (Basics) (23.7%) n = 192Balanced Consumer (26.6%) n = 216 Value Added Orientated (12.3%) n = 100High Frequency Consumer (Broad Product Range) (2.6%) n = 21

Source: Botha, F., Taljaard, P., Jooste, A. & Pelser, A. (2007). UFS.

41

Some pointers: Other factors More sophisticated consumers and linking it

with product development E.g. Checkoff program in US – 500 new products

between 03 and 04 In SA probably not even a 100 since 2003 to date

Lack of internationally acceptable traceability system

Problem/impact compounded if one considers guarantees to comply with increasing and more stringent standards set at the retail level, as well as to export.

42

Some pointers: Other factors Is our grading system still appropriate?

Factor Grading Scheme

USDA JMGA MSA

Breed X X Yes

Growth X X Yes

Stimulation X X Yes

Hang X X Yes

Cut X X Yes

Marbling Yes Yes Yes

Ossification Yes X Yes

Meat Colour Yes Yes Yes

Fat Depth Yes Yes Yes

pH X X Yes

pH/temp/pattern X X Yes

Aging X X YesSource: MLA

43

Some pointers: Other factors Transparent, accurate and timely red meat

information system is basically non-existent. The result is far from optimal chain sequencing putting

pressure on chain governance and relationships.

Dualistic nature of beef industry Growing informal market

Policing of regulations and health standards very difficult Puts the whole industry at jeopardy since poor quality

product can now reach the market undetected. Very difficult to manage and control diseases

44

Let me repeat: No/very little information flows Traceability lacking Slackness in the industry to create uniqueness Problems with industry structure

Most notable is the dualistic nature of the industry

This at a time when: Productivity is increasing Improved technology (slaughtering and processing) Continued investment in “uniqueness” Traceability Information systems

45

Therefore:

A value chain orientation (in practical terms) is necessary, e.g. Relationships Info systems

Some companies/chain players are responding, but overall industry response lacking

Challenge for organised structures in red meat industry to respond and maintain momentum

46Source Roduner (2005)

47

Some value chain influencers

48

China – the growing tiger (“the vacuum”)

Has a fifth of the world’s population and GDP gorwth at 9-10%

Food is one of the largest budget items for households 38% for urban households 50% for rural households

The number of rural households in the middle class 7.6 million in 1995 42 million in 2005

This will grow to 199 million in 2015 (McKinsey Quarterly)

50

China – the growing tiger

As living standards increase they are curring back on staple foods such as rice and wheat.

Consumption of dairy, fish, wine and processed food on the increase.

Food imports in the region of US$25 billion 4th largest in the world

Do not only buy food, but want safe and sophisticated food.

51

Brazil – the food basket

SECEX, 2005

World AGRI-FOOD CHAINS US$ Million and World Market Share

1st SOYBEAN COMPLEX 10,048 (33%)

1st SUGAR/ETHANOL 3,143 (35%)

2nd POULTRY MEAT 2,595 (35%)

1st BEEF 2,487 (26%)

1st COFFEE 2,058 (30%)

1st TOBACCO 1,38 (27%)

1st ORANGE JUICE 1,4 (83%)

3rd PORK MEAT 774 (12%)

4st CORN & PRODUCTS 638

3rd COTTON 407 (5%)

52


Source: FAO

NEW AGRICULTURNEW AGRICULTURALAL FRONTIER FRONTIERSS IN BRAZIL IN BRAZIL

Belém

Nova Fronteira na Produção de Grãos

Rio Grande

Porto Alegre

Imbituba

ParanaguáSantos

Vitória

Aratu

Itacoatiara

Santarém

Rosário

BOLÍVIA

ARGENTINA

URUGUAI

Waterways

Ports

Railways

PARAGUAI

Itaqui

New AgriculturalFrontiers

World

%

13.000 850 7%

2.900 550 19%

1.500 55 4%

Brazil

Used

Arable

TOTAL

World’s Distribution of land:

MaceióWORLD BRAZIL

Million of ha Million of ha

53

Brasilië – die voedselmandtjie

54


Sources: Agrianual, Pensa, MAPA, CONAB, IBGE

* 2003 Crop

HARVEST 2003-04 Potential

PRODUCTS Production Area Yield Production Area Yield

(million t) (million ha) (t/ha) (million t) (million ha) (t/ha)

Soybeans 50,2 21,1 2,4 80,5 23,0 3,5Corn 42,7 12,7 3,4 165,9 23,7 7,0Rice 12,9 3,4 3,8 26,4 6,6 4,0Beans 3,2 4,2 0,8 6,0 4,0 1,5Cotton 3,2 1,0 3,2 5,2 1,5 3,5Wheat 5,9 2,7 2,2 8,0 3,5 2,3others 5,2 1,8 2,9 3,2 2,7 1,2Total Grains 120,1 46,9 2,6 290,1 65,0 4,5Sugarcane * 384,4 4,9 78,4 443,3 4,9 90,0

56

Other influencers

Biofuels industry Oil prices Consumer confidence Infrastructure (water, electricity, roads) Exchange rate etc

57

Concluding remarks From a South African and Southern African

perspective this industry vitally important Sustainability (the triple botton line)

Where is the quick wins with long run impacts Proper support services Proper information service Relationship building and cooperation Understand the economics and environment as it

changes

59

“It is not the strongest that survives, but the most adaptive”.

Thank you

1 SA Meat and the Global Market André Jooste Senior Manager: Market and Economic Research Centre,...

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Transcript of 1 SA Meat and the Global Market André Jooste Senior Manager: Market and Economic Research Centre,...