ACI 20140807 lin

Danie Schoeman

Examining Port and Hinterland Links -Maximising Efficiency Within the Value Chain

Same Village, Different World

© 2014 Danie Schoeman & Company

Shifting Seas


An Interdependent Global Economy

• In 2010 the World Bank published the book titled: “Global Value Chains in a Postcrisis World: A Development Perspective”

• It stated that “the world is in the midst of a sporadic and painful recovery from the most severe economic crisis since the 1930s Great Depression. The unprecedented scale of the crisis and the speed of its transmission have revealed the interdependence of the global economy and the increasing reliance by businesses on global value chains (GVCs). These chains represent the process of ever-finer specialization and geographic fragmentation of production, with the more labour-intensive portions transferred to developing countries. As the recovery unfolds, it is time to take stock of the aftereffects and to draw lessons for the future. Have we experienced the first global crisis of the 21st century or a more structural crisis of globalization?”

• A significant realization


The Need To Think Differently

• In 2012 the World Economic Forum published its annual The Global Enabling Trade Report 2012 under the theme “Reducing Supply Chain Barriers” where it explores how the globalization of value chains impacts measurement of trade and overall trade policies, as well as addresses logistics investments, customs administration and state of the merchant fleet.

• It stated that “To reflect the changing global economic structure, our system of measuring economic activity and our policy orientation, which are still sovereign based, must be expanded and adjusted. This requirement does not contradict the need to build a domestic industrial base, but rather complements it. The world has become highly integrated by information technology, global supply chains, and trade and capital flow linkages—in large part because of the ownership-based operating model. To stick strictly to a model tailored to national boundaries is neither progressive nor realistic.”

• Another significant realization


The Global Operating Model

Adapted from G. Linden, K.L. Kraemer, and J. Dedrick (2009), “Who Captures Value in a Global Innovation Network? The Case of Apple’s iPod”, Communications of the ACM, March 2009, Vol. 52, No. 3, pp. 140-144.

$80

$75

$85

$19

$27

$7 $5 $1

$40

Apple (Margin)

Distribution and Retail

Major Components

Other Inputs

Japan (Margin)

USA (Margin)

Taiwan (Margin)

Korea (Margin)


Global Supply Chains Drive Trade

World Bank WDI, IAPH, Containerisation International

0,1

1

10

100

1000

1970 1975 1980 1985 1990 1995 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Container Throughput (TEU, millions) Exports (current US$, trillions) GDP (current US$, trillions) Population (billions)

Africa Rising


Hopeless Case Or Hopeless Forecast?

“Floods in Mozambique; threats of famine in Ethiopia (again); mass murder in Uganda; the implosion of Sierra Leone; and a string of wars across the continent. The new millennium has brought more disaster than hope to Africa. Worse, the few candles of hope are flickering weakly.”

“Since The Economist regrettably labelled Africa ‘the hopeless continent’ a decade ago, a profound change has taken hold.”

May 2000 December 2011


The Lions Of Africa Are Roaring

2001-2010 Actual 2011-2012 Actual 2014 Forecast

Azerbaijan 15.5% Sierra Leone 15.2% Mongolia 15.3%

Qatar 13.4% Afghanistan 14.4% Sierra Leone 11.2%

Macao SAR, China 12.8% Mongolia 12.3% Turkmenistan 9.2%

Angola 12.1% Turkmenistan 11.1% Bhutan 8.8%

Armenia 10.8% Niger 10.8% Libya 8.8%

China 10.7% Panama 10.7% Iraq 8.5%

Chad 10.6% Liberia 10.2% Lao PDR 8.5%

Equatorial Guinea 10.4% Burkina Faso 10.0% Timor-Leste 8.5%

Nigeria 9.4% Macao SAR, China 9.9% Eritrea 8.0%

Bhutan 8.7% Cote d'Ivoire 9.5% Zambia 7.9%

World’s Ten Fastest Growing Economies

Economist Intelligence Unit (2013)

Economist Intelligence Unit (2013), World Bank WDI, DS&C Analysis


Africa’s Future Consumer Markets

2012 2020

Household final consumption, current US$

$25-50bn >$100bn$50-100bn

World Bank, DS&C Analysis, McKinsey Global Institute


Africa’s Retail Markets

AT Kearney ARDI (2014)

Start with thebasics

Opt out

Move quickly

Differentiate

Rwanda

Nigeria

Namibia

Tanzania

Gabon

Ghana

South Africa

Botswana

Mozambique

Ethiopia

-10

0

10

20

30

40

50

60

70

80

90

100

110

0 10 20 30 40 50 60 70 80 90 100 110

Mar

ket

Satu

rati

on

(1

00

= u

nsa

tura

ted

, 0 =

fu

lly

satu

rate

d)

Market Size


Different Groups, Different Considerations

Oil ExportersDiversified

Pre-transitionTransition

McKinsey Global Institute, World Bank WDI, DS&C Analysis

South Africa

Nigeria

Egypt

AlgeriaMorocco

Libya

Angola Tunisia

Sudan Kenya

Ethiopia

Tanzania

Cameroon

Cote d'IvoireGhana

Uganda

Botswana

Senegal

Zambia

Gabon

Equatorial Guinea

DRC Mozambique

Namibia

Chad

Mauritius

Congo

Burkina FasoMali

Madagascar

Zimbabwe

Benin

Rwanda

Gambia

10

100

1000

10000

0 10 20 30 40 50 60 70 80 90 100

Exp

ort

s p

er c

apit

a (c

on

stan

t 2

00

5 U

S$)

Economic Diversification (Manufacturing & Services sector share of GDP, %)

Trade Flows Like Water


Trading For Africa Is DifficultEnabling Trade Index

WEF ETI (2014)


What Makes Trade Difficult

0 2 4 6 8 10 12 14 16 18

Rules of origin requirements aboard

Burdensome procedures and corruption at foreign borders

High cost or delays caused by domestic transportation

High cost or delays caused by international transportation

Difficulties in meeting quality/quantity requirements of buyers

Technical requirements and standards abroad

Inappropriate production technology and skills

Access to imported inputs at competitive prices

Access to trade finance

Identifying potential markets and buyers

Problematic Factors for Exporting

0 5 10 15 20 25

Inappropriate telecommunications infrastructure

Crime and theft

Domestic technical requirements and standards

High cost or delays caused by domestic transportation

Corruption at the border

High cost or delays caused by international transportation

Burdensome import procedures

Tariffs and non-tariff barriers

Problematic Factors for Importing

WEF ETI (2012)

© 2014 Danie Schoeman & Company Based on the WEF ETI framework

An Evaluation Framework






South Africa

Nigeria

Egypt

AlgeriaMorocco

Libya

Angola Tunisia

Sudan Kenya

Ethiopia

Tanzania

Cameroon

Cote d'IvoireGhana

Uganda

Botswana

Senegal

Zambia

Gabon

Equatorial Guinea

DRC Mozambique

Namibia

Chad

Mauritius

Congo

Burkina FasoMali

Madagascar

Zimbabwe

Benin

Rwanda

Gambia

10

100

1000

10000

0 10 20 30 40 50 60 70 80 90 100

Exp

ort

s p

er c

apit

a (c

on

stan

t 2

00

5 U

S$)



Enabling Trade

0

1

2

3

4

5

6

No

rth

Am

eric

a

Asi

an T

iger

s

Euro

pe

Mo

rocc

o

Ch

ina

Sou

th A

fric

a

Rw

and

a

Tun

isia

Lati

n A

mer

ica

Nam

ibia

Bra

zil

Bo

tsw

ana

Ken

ya

Zam

bia

Ind

ia

Egyp

t

Gam

bia

Sen

egal

Uga

nd

a

Gh

ana

Ru

ssia

Lib

ya

Mo

zam

biq

ue

Eth

iop

ia

Cam

ero

on

Alg

eria

Gab

on

Nig

eria

Be

nin

An

gola

Enabling Trade Index

Diversified Transition Pre-transition Oil Exporters BRIC Blocs

WEF ETI (2014)


Customs Quality

Most of the African customs and related agencies provide services of lower quality and/or less comprehensive by world standards.

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Sou

th A

fric

a

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Cu

sto

ms

Serv

ices

Ind

ex

Customs Services Index World Avg

DS&C Analysis, WEF ETI (2014)


Death By Document

0

2

4

6

8

10

12

14

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Sou

th A

fric

a

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

No

. of

do

cum

ents

Import Export

DS&C Analysis, World Bank Doing Business (2014)


… Due To Complexity?

GhanaNigeria

Cape VerdeThe Gambia

BeninTogo

Côte d’Ivoire

Niger

Burkina Faso

Guinea-Bissau MaliSenegal

Liberia

Sierra Leone

Guinea

Chad

ECOWAS

São Tomé& Príncipe

CameroonCentralAfricanRep.

Gabon

Equatorial Guinea

Rep. of Congo

Egypt

BurundiRwanda

DR CongoAngola

Tanzania

South AfricaBotswana

Lesotho

Namibia

Mozambique

Swaziland

Malawi

Zambia

Zimbabwe

LibyaAlgeria

Morocco

Mauritania

Tunisia

SahrawiArab DR

Djibouti

Ethiopia

EritreaSudan

Kenya

Uganda

Mauritius

Seychelles

Comoros

Madagascar

South Sudan

Somaliland

AFRICAN UNION

CEN-SAD

WAMZ

SADC

ECCAS

CEMAC

COMESA

IGAD

AMU

SACU

EAC

LGAUEMOA

MRU

CEPGL

AfDB, African Union, DS&C Analysis


Too Slow …

0

10

20

30

40

50

60

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Sou

th A

fric

a

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

No

. of

day

s

Import Export



… And Too Expense

0

1000

2000

3000

4000

5000

6000A

sian

Tig

ers

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Sou

th A

fric

a

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Co

st (

US$

per

co

nta

iner

)

Import Export



Efficiency Drive Predictability

0

1

2

3

4

5

6

7

0 0,5 1 1,5 2 2,5 3 3,5 4 4,5

Tim

e p

red

icta

bili

ty o

f im

po

rt p

roce

du

res

Efficiency of the clearance process

Time predictability is core to efficient supply chains. There is a clear correlation between the efficiency of the clearance process and time predictability of import procedures

resulting in more efficient supply chains.

DS&C Analysis, World Bank LPI (2014), WEF ETI (2014)


Efficiency Drive Predictability

For the Asian Tigers there is a high correlation between the clearance process efficiency and time predictability – evidence of their supply chain success. The relation holds true for

most of the African economies but of lesser correlation.

0

0,5

1

1,5

2

2,5

3

3,5

4

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Sou

th A

fric

a

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Sco

re (

1 =

ver

y lo

w, 5

= v

ery

hig

h)

Clearance Process Efficiency Time predictability

DS&C Analysis, World Bank LPI (2014), WEF ETI (2014)


Customs Integrity

Irregular payments are 1.6 times more likely to occur in the Oil Exporters grouping than in the Diversified grouping, with about 25% less transparency.

Brazil

Russia

India

ChinaSouth Africa

Morocco

Rwanda

Nigeria

Gabon

Ghana

Ethiopia

Benin

Angola

Uganda

Cameroon

Gambia

Kenya

Egypt

Hong Kong

Indonesia

Korea, Rep.

Malaysia

Philippines

Singapore

Taiwan

Thailand

0

0,2

0,4

0,6

0,8

1

1,2

0 1 2 3 4 5 6 7

Cu

sto

ms

Tran

spar

ency

Ind

ex

Irregular Payments (1 = common, 7 = never occurs)

Honest Joe’sHonest Crooks

AngelsDark Horses



Getting To The ContinentLiner Shipping Connectivity

UNCTAD (2013)


Connecting To Trade

Liner Shipping Connectivity Index for Diversified Economies is significantly higher than any other grouping.

0

20

40

60

80

100

120

140

160

180

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Sou

th A

fric

a

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Liner Shipping Connectivity Index

DS&C Analysis, UNCTAD (2014)


No Field Of Dreams

0

20

40

60

80

100

120

140

160

180

0 1 2 3 4 5 6 7 8

Lin

er S

hip

pin

g C

on

nec

tivi

ty In

dex

Quality of port infrastructure

Improved port quality does not necessarily guarantee in increased liner shipping connectivity. It means maintaining the current services.

“If You Build It, He Will Come”- Field of Dreams (1989)

DS&C Analysis, UNCTAD (2014), WEF ETI (2014)


Port Infrastructure Outpaces

For Asian Tigers and BRIC countries port infrastructure and intermodal change are well balanced, making for efficient supply chains. For most of Africa though, port infrastructure

outpaces the hinterland links resulting in inefficient supply chains.

0

1

2

3

4

5

6

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Sou

th A

fric

a

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Sco

re (

1 =

ext

rem

ely

un

der

dev

elo

ped

, 7 =

wel

l-d

evel

op

ed

and

eff

icie

nt

by

inte

rnat

ion

al s

tan

dar

ds;

1 =

no

t ef

fici

ent

at a

ll, 7

= e

xtre

me

ly e

ffic

ien

t)

Quality of port infrastructure Efficiency of transport mode change



Physical Infrastructure

Generally roads are considered of better quality and more reliable than rail, except for Russia, India and China in the BRICS Bloc.

0

1

2

3

4

5

6

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Sou

th A

fric

a

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Sco

re (

1 =

ext

rem

ely

un

der

dev

elo

ped

, 7 =

ex

ten

sive

an

d e

ffic

ien

t b

y in

tern

atio

nal

sta

nd

ard

s)

Quality of railroad infrastructure Quality of roads



Roads – Connecting The Dots

AfdB


Roads - The Burden Of Maintenance

Corridor Length (km)Roads in good condition (%)

Trade density (US$

million/km)

Implicit speed (km/hour)

Freight tariff (US$/tonne-

km)

Western 2050 72 8.2 6 0.08

Central 3280 49 4.2 6.1 0.13

Eastern 2845 82 5.7 8.1 0.07

Southern 5000 100 27.9 11.6 0.05

Teravaninthom and Rablland (2008)


Then There’s African Road Rage!


Railways - Not Pulling Their Weight

AfdB


Electricity – Still The Dark Continent?

88

28

40

52

43

Northern Africa

Eastern Africa

Middle Africa

Southern Africa

Western Africa

Access to electricity (% of population)

International Energy Agency, World Energy Outlook

© 2014 Danie Schoeman & Company DS&C Analysis, World Bank LPI (2014)

Moving Stuff On The ContinentLogistics Performance Index


Ease and Affordability

Ease and affordability of shipments are largely driven by local logistics competence although more so by international logistics competence in some countries.

0

0,5

1

1,5

2

2,5

3

3,5

4

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Sou

th A

fric

a

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Sco

re (

1 =

ver

y lo

w, 5

= v

ery

hig

h)

Ease and affordability of shipment Logistics competence

DS&C Analysis, World Bank LPI (2014)


Timeliness

Timeliness of shipments are determined by local logistics competence as well as the ability to track and trace consignments.

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Sou

th A

fric

a

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Sco

re (

1 =

ver

y lo

w, 5

= v

ery

hig

h)

Logistics competence Tracking and tracing ability Timeliness of shipments in reaching destination

DS&C Analysis, World Bank LPI (2014)


A Mobile Continent

Mobile is dominant and as such Africa has leap frogged fixed broadband internet to active mobile broadband instead.

0

20

40

60

80

100

120

140

160

180

200

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Sou

th A

fric

a

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Wo

rld

Sub

scri

pti

on

s/1

00

po

p.

Mobile phone Fixed broadband Internet Active mobile broadband Internet

DS&C Analysis, ITU World Telecommunication (2013)


Business Technology

Use of ICT and the Internet for B2B and B2C transactions is prolific but it seems that the number of users drives the success of these technologies.

0

10

20

30

40

50

60

0

1

2

3

4

5

6

Asi

an T

iger

s

Bra

zil

Ru

ssia

Ind

ia

Ch

ina

Mo

rocc

o

Tun

isia

Rw

and

a

Nig

eria

Nam

ibia

Tan

zan

ia

Gab

on

Gh

ana

Sou

th A

fric

a

Bo

tsw

ana

Mo

zam

biq

ue

Eth

iop

ia

Be

nin

An

gola

Zam

bia

Sen

egal

Uga

nd

a

Cam

ero

on

Gam

bia

Ken

ya

Egyp

t

Alg

eria

Lib

ya

Perc

enta

ge

Sco

re (

1 =

no

t at

all,

7 =

to

a g

reat

ext

ent)

ICT use for business-to-business transactions Internet use for business-to-consumer transactions

Individuals using Internet (%)


An Agenda






South Africa

Nigeria

Egypt

AlgeriaMorocco

Libya

Angola Tunisia

Sudan Kenya

Ethiopia

Tanzania

Cameroon

Cote d'IvoireGhana

Uganda

Botswana

Senegal

Zambia

Gabon

Equatorial Guinea

DRC Mozambique

Namibia

Chad

Mauritius

Congo

Burkina FasoMali

Madagascar

Zimbabwe

Benin

Rwanda

Gambia

10

100

1000

10000

0 10 20 30 40 50 60 70 80 90 100

Exp

ort

s p

er c

apit

a (c

on

stan

t 2

00

5 U

S$)



Conclusions

• The Asian Tigers still outstrip the sample field by far.• Diversified economies are comparative to BRIC countries except for

Infrastructure and Technology.• Diversified economies outstrip the other African economic

groupings, probably due to higher levels of complexity and the requirements in their supply chains. They are also more globally connected.

• The Oil Exporters generally lag the field in logistics infrastructure and services, mainly due to the fact that the resource nature of their exports is pipeline orientated rather than container.

• The Transition and Pre-transition economies general find themselves in 2nd and 3rd place in the African groupings across categories, signifying the need of their supply chains as they move to the diversification.

• The framework sets an agenda for the development of efficient supply chains that can integrate into the larger global value chains.


In 2012 A Man Fell From Space*

It was a fall that caught the imagination of all humanity. But it was a thousand years of human imagination that caught him.

*Ok, the actual border of “space” is much higher than the altitude Felix’s capsule attained, the lowest point being the Kármán line, recognized by aeronautic agencies at 100 km (62 miles) up. Still, Felix was above 99% of Earth’s atmosphere, where air pressure is virtually non-existent and the sky above is black. I don’t know about you, but that’s good enough for me!


Disclaimer

This document has been prepared by Danie Schoeman and Companyto provide background information on the subjects mentioned herein,the forecasts, opinions and expectations are entirely those of DanieSchoeman and Company. This presentation was prepared with theutmost due care and consideration for accuracy and factualinformation; the forecasts, opinions and expectations are deemed tobe fair and reasonable. However there can be no assurance thatfuture results or events will be consistent with any such forecasts,opinions and expectations. Therefore the authors will not incur anyliability for any loss arising from any use of this presentation or itscontents or otherwise arising in connection herewith. Neither will thesources of information or any other related parties be held responsiblefor any form of action that is taken as a result of the proliferation ofthis document.

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