Transcript Sub-Saharan Africa forecast

The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Research Forecast Report
The Sub-Saharan Africa telecoms market: trends and
forecasts 2011-2016
February 2012
Roz Roseboro and William Hare
© Analysys Mason Limited 2012
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Contents
Slide no.
Slide no.
5.
Executive summary
6.
Retail telecoms services revenue in Sub-Saharan Africa will grow at a
10% CAGR between 2010 and 2016
22. Mobile connections in Sub-Saharan Africa will nearly double between
2010 and 2016, as services become more widely available and more
affordable
7.
Growth in penetration of mobile handset SIMs will begin to slow towards
the end of the forecast period, as inability to pay begins to limit take-up
23. Mobile penetration rates will begin to level off towards the end of the
forecast period
8.
Mobile services dominate the telecoms markets in Sub-Saharan Africa,
and will continue to account for the majority of voice connections
24. Despite strong growth in 3G connections, 2G will continue to be the
dominant mobile technology in the region throughout the forecast period
9.
Most of the new broadband connections will be via mobile devices
because of the lack of widespread, suitable fixed infrastructure
25. Mobile voice revenue will grow at a much slower rate than connections
because of sustained price pressure
10. Key implications
11. Key implications
12. Market definition and methodology
13. Geographical coverage
14. Forecasting methodology: our comprehensive Sub-Saharan Africa
telecoms forecast model is supported by a sound knowledge of markets
15. Forecasting methodology: we base our forecasts on reported metrics,
and insight into market and competitive dynamics
16. Key forecast assumptions
17. Data series definitions: mobile
18. Data series definitions: fixed
19. Sub-Saharan Africa forecast
20. Mobile data will drive up revenue in the Sub-Saharan Africa telecoms
market during 2011–2016
21. Increasing usage of mobile broadband and handset data will drive up the
share of revenue from non-voice services from 13% in 2010 to 21% in 2016
© Analysys Mason Limited 2012
26. Mobile service usage and the number of outgoing voice minutes will
increase as the price per minute declines
27. Fixed retail revenue in Sub-Saharan Africa will grow only slightly
because of the decline in fixed voice revenue
28. Fixed broadband subscriptions will drive growth in the fixed market in
Sub-Saharan Africa, while fixed voice subscriptions will be flat
29. Country forecasts
30. Ghana’s telecoms markets are highly competitive and growth is forecast
to track that in the region as a whole, except in the fixed voice market
31. Ghana’s mobile market will benefit from additional spectrum and more
competition
32. Kenya’s telecoms market is more balanced than most in the region, and
will outpace the region as a whole in mobile voice and broadband
growth
33. Kenya should gain more-affordable mobile services and more options
for fixed services
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Contents
Slide no.
Slide no.
34. Nigeria is the largest mobile market in the region, and will experience
faster-than-average growth in mobile non-messaging data revenue
40. Tanzania’s mobile market is extremely competitive, unlike its fixed
market, but the country’s growth rates will lag those for the region
overall
35. Nigeria will become increasingly focused on mobile services, as
traditional wireline markets continue to decline
36. South Africa has the most-mature telecoms market in the region and
accounts for much of its revenue, but it will have lower growth rates
37. South Africa should experience greater mobile data usage and greater
fibre availability
41. Mobile data services in Tanzania should grow as costs decline, while
the fixed market will continue to be challenging
42. Uganda’s telecoms market is the most dependent on mobile of those
in the countries modelled, and its growth will outpace the region in
most areas
38. Sudan’s telecoms market is in an earlier stage of development than
most others in the region, so has higher growth rates than the region
overall
43. Consolidation in Uganda should help to rationalise mobile pricing,
and the market overall will benefit from continued fibre deployments
39. Sudan will benefit from greater mobile network coverage and continued
growth in services based on fixed–wireless technology
45. About the authors
44. About the authors and Analysys Mason
46. About Analysys Mason
47. Research from Analysys Mason
48. Consulting from Analysys Mason
© Analysys Mason Limited 2012
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
List of figures
Figure 1:
Retail revenue by service type, Sub-Saharan Africa, 2010–2016
Figure 18: Retail revenue by service type, Ghana, 2010–2016
Figure 2:
Mobile SIM penetration rates by device type and technology
generation, Sub-Saharan Africa, 2010–2016
Figure 19: Growth rates of retail revenue by service type, Ghana, 2010–2016
Figure 3:
Voice connections by type, Sub-Saharan Africa, 2010–2016
Figure 21: Retail revenue by service type, Kenya, 2010–2016
Figure 4:
Broadband connections by type, Sub-Saharan Africa, 2010–2016
Figure 22: Growth rates of retail revenue by service type, Kenya, 2010–2016
Figure 5:
Countries covered in this report
Figure 23: Kenyan population, GDP and GDP per capita, 2010
Figure 6:
Key factors influencing forecast assumptions
Figure 24: Retail revenue by service type, Nigeria, 2010–2016
Figure 7:
Key metrics for historical and forecast data
Figure 8:
Retail revenue by service type, Sub-Saharan Africa, 2010–2016
Figure 25: Growth rates of retail revenue by service type, Nigeria,
2010–2016
Figure 9:
Growth rates of retail revenue by service type, Sub-Saharan
Africa, 2010–2016
Figure 20: Ghanaian population, GDP and GDP per capita, 2010
Figure 26: Nigerian population, GDP and GDP per capita, 2010
Figure 27: Retail revenue by service type, South Africa, 2010–2016
Figure 10: Mobile revenue by type and non-voice services’ share of mobile
revenue, Sub-Saharan Africa, 2010–2016
Figure 28: Growth rates of retail revenue by service type, South Africa,
2010–2016
Figure 11: Mobile connections by country and mobile penetration, SubSaharan Africa, 2010–2016
Figure 29: South African population, GDP and GDP per capita, 2010
Figure 12: Mobile penetration by country, Sub-Saharan Africa, 2010–2016
Figure 13: Mobile connections by technology generation, and 3G
penetration, Sub-Saharan Africa, 2010–2016
Figure 14: Mobile revenue by type, and mobile ASPU and ARPU, SubSaharan Africa‚ 2010–2016
Figure 15: Outgoing mobile voice minutes by country, Sub-Saharan Africa,
2010–2016
Figure 30: Retail revenue by service type, Sudan, 2010–2016
Figure 31: Growth rates of retail revenue by service type, Sudan, 2010–2016
Figure 32: Sudanese population, GDP and GDP per capita, 2010
Figure 33: Retail revenue by service type, Tanzania, 2010–2016
Figure 34: Growth rates of retail revenue by service type, Tanzania,
2010–2016
Figure 35: Tanzanian population, GDP and GDP per capita, 2010
Figure 16: Fixed retail revenue by type, Sub-Saharan Africa, 2010–2016
Figure 36: Retail revenue by service type, Uganda, 2010–2016
Figure 17: Fixed line connections by country, Sub-Saharan Africa,
2010–2016
Figure 37: Growth rates of retail revenue by service type, Uganda,
2010–2016
Figure 38: Ugandan population, GDP and GDP per capita, 2010
© Analysys Mason Limited 2012
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Executive summary
Key implications
Market definition and methodology
Sub-Saharan Africa forecast
Country forecasts
About the authors and Analysys Mason
© Analysys Mason Limited 2012
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Retail telecoms services revenue in Sub-Saharan Africa will grow at a 10%
CAGR between 2010 and 2016
Figure 1: Retail revenue by service type, Sub-Saharan Africa, 2010–2016
[Source: Analysys Mason, 2012]
Retail revenue (USD billion)
70
60
50
 Retail telecoms revenue in Sub-Saharan Africa will grow at
a CAGR of 10% during 2010–2016, from USD40 billion in
2010 to USD69 billion in 2016. South Africa’s telecoms
markets are far more mature than those in other modelled
countries. Consequently, while it accounts for much of the
revenue, its growth rates tend to be lower than those seen
elsewhere in the region.
 Mobile voice retail revenue will increase at a CAGR of 9%,
but will be under continual pressure because of sustained,
strong competition and the expansion of networks into
more-rural and price-sensitive regions. With the exception of
South Africa, telecoms markets in the region are more heavily
dominated by mobile voice services than markets elsewhere
in the world.
40
30
20
10
0
2010 2011 2012 2013 2014 2015 2016
Business network services
Dial-up
Fixed broadband
Fixed voice
Mobile handset data
Mobile broadband
Mobile messaging
Mobile voice
© Analysys Mason Limited 2012
 Fixed voice retail revenue will decline at a CAGR of –6% and
the number of connections will remain largely unchanged.
Overall, voice will continue to account for most retail revenue
throughout the forecast period. Only Kenya and South Africa
generate more than 10% of revenue from fixed voice services,
and this figure is declining in both markets.
 Mobile and fixed broadband will generate only 8% of retail
revenue in 2016, because most users will continue to access
the Internet via their handsets. Handset data will account for
8% of retail revenue in 2016.
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Growth in penetration of mobile handset SIMs will begin to slow towards
the end of the forecast period, as inability to pay begins to limit take-up
Figure 2: Mobile SIM penetration rates by device type and technology
generation, Sub-Saharan Africa, 2010–2016 [Source: Analysys Mason, 2012]
80%
 Network coverage will increase in rural areas, but inability to
pay will limit take-up.
70%
Percentage of the population
 Growth in the penetration rates for mobile handset SIMs in
Sub-Saharan Africa will slow in the later years of the forecast
because of the region’s comparatively low GDP per capita.
 Mobile broadband SIM penetration will grow to just 4% of
the population in Sub-Saharan Africa by 2016, as the low
penetration rate of PCs limits the opportunity for broadband
services.1
60%
50%
 3G penetration will increase from 3% in 2010 to 20% in 2016
as a result of improved network quality and availability. 4G
will have a limited impact in Kenya and South Africa, but only
at the end of the forecast period.2
40%
30%
20%
10%
0%
2010
2011
2012
2013
Handset SIMs
3G
Mobile broadband SIMs
4G
© Analysys Mason Limited 2012
2014
2015
2016
1
Analysys Mason’s definition of mobile broadband includes PC, laptop, netbook or tablet PC
connections via a USB modem or datacard. It excludes handset-based Internet access or use of
the handset as a modem.
2
Analysys Mason’s definition of 4G includes any mobile technology greater than 3.5 G (for
example, HSDPA, HSUPA, CDMA2000 1× EV-DO Rev. A and Flash OFDM) even if it does
not meet the ITU’s definition of 4G.
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Mobile services dominate the telecoms markets in Sub-Saharan Africa,
and will continue to account for the majority of voice connections
Figure 3: Voice connections by type, Sub-Saharan Africa, 2010–2016
[Source: Analysys Mason, 2012]
700
 Mobile services accounted for 97% of voice connections in
2010, and their share will increase to 98% by the end of the
forecast period.
600
Connections (million)
 The number of voice connections in Sub-Saharan Africa will
increase at a CAGR of 9%, from 395 million in 2010 to
671 million in 2016.
 Most of the growth in mobile connections is coming from
non-urban areas, where there is little fixed infrastructure.
We do not expect this situation to change, as operators will
largely rely on wireless technologies (WiMAX and HSPA)
to expand connectivity into underserved areas.
500
400
 The fixed markets in most countries of Sub-Saharan
Africa are dominated by national incumbent operators, which
are rarely challenged to improve their services. However,
CDMA-based limited-mobility fixed–wireless services are a
threat to PSTN-based voice services in some markets, such
as South Africa.
300
200
100
0
2010 2011 2012 2013 2014 2015 2016
Mobile
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Fixed
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Most of the new broadband connections will be via mobile devices
because of the lack of widespread, suitable fixed infrastructure
Figure 4: Broadband connections by type, Sub-Saharan Africa, 2010–2016
[Source: Analysys Mason, 2012]
60
Connections (million)
50
40
 The number of broadband connections in Sub-Saharan Africa
will increase significantly during the forecast period, from
9 million in 2010 to 50 million in 2016. This represents a
CAGR of 33%. Increased international connectivity and
greater use of fibre in national backbones, aggregation and
access networks should lead to lower pricing. It should be
noted that the total cost per megabyte may increase for
operators because of the cost of fibre deployment and the
need to buy more international capacity.
 However, the broadband penetration rate will have reached
only 5% of the population by 2016. PC penetration rates are
very low across the region, and this is unlikely to change
significantly during the forecast period.
30
20
 USB-modem-based mobile broadband services accounted
for 73% of broadband connections in 2010. This share will
grow to 84% by 2016.
10
 Other than in some major urban centres, there is no fixed
infrastructure suitable for broadband services.
0
2010 2011 2012 2013 2014 2015 2016
Mobile broadband
DSL
Cable modem
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BFWA
FTTB
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Executive summary
Key implications
Market definition and methodology
Sub-Saharan Africa forecast
Country forecasts
About the authors and Analysys Mason
© Analysys Mason Limited 2012
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
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Key implications
 The mobile markets in Sub-Saharan Africa’s urban areas are approaching saturation, so mobile operators will need to
provide services in secondary cities and towns in order to increase subscriber numbers. These newer users will be more
price sensitive, making it challenging for operators to achieve attractive ROIs. As a result, mobile operators will be under pressure
to reduce their opex and capex. Government-led efforts to make telecoms services more widely available in countries such as
Kenya, Nigeria, Tanzania and Uganda will also help to focus efforts away from urban areas. Operators will consider network sharing
and outsourcing opportunities as means to reduce their costs.
 Mobile operators will need to focus on retaining their high-ARPU customers because newer subscribers have less to
spend on telecoms services. In order to capture a larger portion of spend, operators will encourage customers to reduce their use
of multiple SIMs. Mobile network operators (MNOs) will be looking for solutions that will support creative customer loyalty schemes.
Today, operators mostly use heavily discounted on-net pricing to encourage usage, which has led to high levels of multiple-SIM usage.
 Improved network availability and quality will drive increased usage of voice and data services. In the next 2–3 years,
operators will increase network capacity in order to ensure network quality and to fill in coverage gaps, in many cases through
network-sharing arrangements. Regulators in Ghana, Kenya, Nigeria and Uganda have been putting significant pressure on
operators to increase network quality, and may resort to fining and restricting the commercial activities of operators that do not
show sufficient improvement.
 Increased international connectivity from new submarine cables should help to reduce broadband pricing. The lighting of
the ACE and WACS cables in 2012 should help to reduce operators’ costs and to increase capacity, which should ultimately lead to
lower prices for broadband services for end users. However, this effect may take more than 1–2 years, as indicated by the lack of
much movement in broadband pricing since the launch of multiple submarine cables in recent years. Operators will nonetheless
also need to focus on reducing costs in national backbones, aggregation and access networks.
 Fixed voice services will not be a significant driver of operator revenue. Fixed infrastructure is generally found only in major
urban centres in Sub-Saharan Africa, and is often of poor quality. Any new fixed network deployments will be to support backhaul
and transport services, rather than voice or broadband services for end users. Telecoms services for non-urban populations will use
mobile or fixed–wireless technologies.
© Analysys Mason Limited 2012
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Executive summary
Key implications
Market definition and methodology
Sub-Saharan Africa forecast
Country forecasts
About the authors and Analysys Mason
© Analysys Mason Limited 2012
12
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Geographical coverage
Figure 5: Countries covered in this report [Source: Analysys Mason, 2012]
 The following countries are modelled individually:
 Ghana, Kenya, Nigeria, South Africa, Sudan, Tanzania and
Uganda.
 The following countries were modelled as part of the region
of Sub-Saharan Africa as a whole:
■
■
■
Countries modelled
individually
Countries modelled as part
of the region as a whole
Countries not covered by
this report1












1
These countries are covered by Analysys Mason’s report “The Middle East and North Africa
telecoms market: trends and forecasts 2011–2016”.
© Analysys Mason Limited 2012


Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Cape Verde
Central African
Republic
Chad
Comoros
Congo,
Democratic
Republic of
Congo,
Republic of
Côte d'Ivoire
Djibouti

















Equatorial Guinea
Eritrea
Ethiopia
Gabon
Gambia
Guinea
Guinea-Bissau
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mayotte
Mozambique
Namibia













Niger
Réunion
Rwanda
São Tomé
and Principe
Senegal
Seychelles
Sierra Leone
Somalia
Saint Helena
Swaziland
Togo
Zambia
Zimbabwe.
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Forecasting methodology: our comprehensive telecoms forecast model is
supported by a sound knowledge of markets
 All our forecasts are prepared and reviewed by analysts who
are deeply familiar with the underlying technologies and
services we are forecasting, and with the commercial and
regulatory characteristics of the markets being modelled.
 The forecasts are intended to predict outcomes and expected
market development, rather than to model market
opportunity.
Figure 6: Key factors influencing forecast assumptions [Source: Analysys
Mason, 2012]
Telecoms market insights
 Expected consumer behaviour
 Operators’ and vendors’ plans
and projections
 Anticipated regulatory developments
 The key assumptions in our forecasts take into account likely
commercial and regulatory developments in particular
markets, as well as technology developments and evolution.
As part of the process, we also solicit opinions on market
developments from major players.
 We are happy to discuss our key assumptions in more detail
with clients.
Market
insight
Inter-country
comparison
Inter-country comparisons
 Knowledge of the structural
similarities and differences
between markets
 Benchmarking with similar
markets
© Analysys Mason Limited 2012
Macroeconomics
Macroeconomics
 Population, household and
workforce trends
 GDP forecasts
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Forecasting methodology: we base our forecasts on reported metrics, and
insight into market and competitive dynamics
 We forecast fixed and mobile services in relation to each
other, not in isolation. The major (interrelated) dynamics in
the market are:
Figure 7: Key metrics for historical and forecast data [Source: Analysys
Mason, 2012]
 substitution (fixed–mobile, mobile–fixed)
Historical
Forecast
Retail revenue
Price per unit
 complementary usage.
 Our general approach to forecasting telecoms markets is
econometric. The key assumptions that underpin our
forecasts are:
 usage trends
 pricing trends.
Inputs
from which
we derive:
Forecasts
from which
we derive:
Traffic
Traffic
Price per unit
Retail revenue
 Services covered include fixed and mobile voice, fixed
and mobile broadband and mobile messaging and
non-messaging data.
= Price elasticity of demand
© Analysys Mason Limited 2012
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
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Key forecast assumptions
Demographic and economic considerations:
 The rising number of more price-sensitive users from outside urban centres will maintain pressure on mobile voice pricing.
 The increasing average age of the population and rising GDP per capita will expand the size of the addressable market for
telecoms services.
 Growth in GDP in Sub-Saharan Africa (expected to be faster than that worldwide) will support demand for business network
services.
Technology considerations:
 Operators will expand mobile network coverage, increase capacity and improve quality, partly in response to government
initiatives towards universal service, but also as a result of their own need to better support mobile data services.
 Increases in international connectivity and fibre availability will help to reduce broadband pricing and increase take-up. This
will be reflected mostly in demand for handset data, rather than mobile broadband, given the low PC penetration rates in the region.
 LTE roll-outs will not be a factor in most of Sub-Saharan Africa during the forecast period.
 Fixed infrastructure will continue to be available only in urban centres, for the most part; new investment in more-rural areas will
be to support mobile services, rather than fixed.
Commercial considerations:
 Fixed voice pricing will be relatively stable because of lack of competition.
 Continued demand for fixed voice services from business users will keep the number of fixed voice lines steady during the
forecast period.
 Consolidation and rationalisation in some mobile markets will mitigate some of the price pressure on mobile voice.
© Analysys Mason Limited 2012
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Data series definitions: mobile
 Active subscribers: refers to handset and mobile broadband
SIMs active within the past three months, rather than to the
number of customers. These include mobile virtual network
operators’ (MVNOs’) retail subscribers, which are allocated to
the hosts’ networks.
 Subscriptions are split by:
 type: prepaid and contract
 device: handsets, mobile broadband and M2M
 generation: 2G, 3G and 4G (corresponding to the highest
technology supported by the device and networks in the
country).
 Further detail on device type:
 handsets: all voice devices, either basic phones or
smartphones
 mobile broadband: non-voice devices, such as USB
modems, either mid-screen mobile broadband or
large-screen mobile broadband devices.
© Analysys Mason Limited 2012
 Service revenue is composed of:
 retail revenue: all end-user revenue, exclusive of direct
equipment sales
 termination revenue: all inter-operator revenue, inclusive of
roaming-in revenue.
 Revenue is split by service type:
 messaging: SMS and MMS, by definition on handsets only
 handset data: non-voice, non-messaging services on
handsets, including use of the handset as a modem.bil
 Average revenue per user (ARPU) is service revenue
accrued during the period divided by the average number of
subscriptions, while average spend per user (ASPU) is the
equivalent measure for retail revenue.
 Voice usage (minutes) – mobile-originated or outgoing traffic:
all traffic generated by operators’ and MVNOs’ end users.
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Data series definitions: fixed
 Connections are split by service type:
 voice: supported by either PSTN/ISDN or VoIP
 fixed broadband: see further technology split below.
 Multi-play accounts are counted as many times as the
number of services they take.
 Fixed broadband connections are split by technology:
 DSL
 cable modem
 FTTH (by definition, residential only)
 BWFA.
© Analysys Mason Limited 2012
 Service revenue is composed of:
 retail revenue: all end-user revenue, exclusive of
equipment sales, made up of revenue from:

voice retail services (PSTN/ISDN or VoIP)

fixed broadband retail services

business network services
 wholesale revenue: all inter-operator revenue.
 ARPU is service revenue accrued during the period divided
by the average number of subscriptions, while ASPU is the
equivalent measure for retail revenue.
 Voice usage (minutes) – fixed-originated or outgoing traffic:
all traffic generated by the operators’ end users. We do not
include fixed-terminating traffic.
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Executive summary
Key implications
Market definition and methodology
Sub-Saharan Africa forecast
Country forecasts
About the authors and Analysys Mason
© Analysys Mason Limited 2012
19
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Mobile data will drive up revenue in the Sub-Saharan Africa telecoms
market during 2011–2016
Retail revenue (USD billion)
Figure 8: Retail revenue by service type, Sub-Saharan Africa, 2010–2016
[Source: Analysys Mason, 2012]
Figure 9: Growth rates of retail revenue by service type, Sub-Saharan Africa,
2010–2016 [Source: Analysys Mason, 2012]
70
Service type
60
50
Change
2010–2011
CAGR
2011–2016
Fixed voice
–4.4%
–6.0%
Fixed broadband
21.6%
14.4%
Business network services
10.4%
7.4%
Mobile voice
13.6%
8.4%
30
Mobile messaging
21.4%
12.3%
20
Mobile handset data
41.0%
18.1%
100.5%
21.3%
14.0%
8.5%
40
Mobile broadband
10
Total
0
2010 2011 2012 2013 2014 2015 2016
Business network services
Dial-up
Fixed broadband
Fixed voice
Mobile handset data
Mobile broadband
Mobile messaging
Mobile voice
© Analysys Mason Limited 2012
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Increasing usage of mobile broadband and handset data will drive up the
share of revenue from non-voice services from 13% in 2010 to 21% in 2016
Figure 10: Mobile revenue by type and non-voice services’ share of mobile
revenue, Sub-Saharan Africa, 2010–2016 [Source: Analysys Mason, 2012]
25%
60
Revenue (USD billion)
20%
50
15%
40
30
10%
20
5%
10
0
0%
2010 2011 2012 2013 2014 2015 2016
Voice
Mobile broadband
Termination
© Analysys Mason Limited 2012
Mobile messaging
Handset data
Non-voice services
Percentage of total mobile retail revenue
70
 Mobile revenue in Sub-Saharan Africa will grow at a CAGR
of 11% during 2010–2016, from USD37 billion in 2010 to
USD68 billion in 2016. In Kenya, Nigeria, Tanzania and
Uganda, mobile revenue will grow more quickly than in the
region as a whole, while in South Africa it will grow more
slowly.
 Non-voice services’ share of mobile retail revenue will grow
from 13% in 2010 to 21% in 2016. Most value-added services
are still SMS-based, so handset data will continue to be a
relatively small element of mobile retail revenue.
 Increasing 3G capacity will bolster the growth in revenue
from handset data and mobile broadband – although low
PC penetration will limit mobile broadband usage. Most
subscribers will access the Internet via handsets. The impact
of LTE will be seen only in certain areas (such as in Kenya
and South Africa) during the forecast period.
 Mobile voice services will come under pricing pressure in
markets where a large proportion of new users are very price
sensitive (and tend to have lower usage).
 Mobile broadband is mostly used as a substitution for fixed
broadband because penetration rates for the latter are low
throughout the region. In countries where voice margins are
already thin, the market for mobile broadband will struggle
even more.
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Mobile connections in Sub-Saharan Africa will nearly double between 2010
and 2016, as services become more widely available and more affordable
800
80%
700
70%
600
60%
500
50%
400
40%
300
30%
200
20%
100
10%
0
0%
2010 2011 2012 2013 2014 2015 2016
Ghana
Kenya
Nigeria
South Africa
Sudan
Tanzania
Uganda
Rest of SSA
Mobile penetration
Note: SSA = Sub-Saharan Africa
© Analysys Mason Limited 2012
Percentage of the population
Connections (million)
Figure 11: Mobile connections by country and mobile penetration,
Sub-Saharan Africa, 2010–2016 [Source: Analysys Mason, 2012]
 The number of mobile connections will increase at a CAGR
of 10% during the forecast period, from 388 million in 2010 to
700 million in 2016. Connections will grow in Kenya, Sudan
and Uganda at a higher rate than in the region as a whole,
but Nigeria will record the greatest number of new
connections.
 The increasing average age of Sub-Saharan Africa’s young
population will expand the addressable market for mobile
services.
 As growth in the rate of penetration slows, operators
will continue to compete on price, but will focus more on
increasing customer loyalty in order to gain a larger share
of users’ minutes.
 About 95% of customers in Sub-Saharan Africa use prepaid
services – between 98% and 99% in most of the countries
we modelled – and this proportion is unlikely to change
during the forecast period.
 Multiple-SIM use is a significant factor in the region, and we
also expect this to continue. We have assumed 1.4–2.1 SIMs
per user in the countries we have modelled. The level of
multiple-SIM usage will decline somewhat during the forecast
period as a result of operator consolidation and gradual
reduction in the difference between on-net and off-net pricing.
23
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Mobile penetration rates will begin to level off towards the end of the
forecast period
Figure 12: Mobile penetration by country, Sub-Saharan Africa, 2010–2016
[Source: Analysys Mason, 2012]
Percentage of the population
140%
120%
 We expect operators to focus on improving network quality
in their established footprints, and on providing somewhat
expanded coverage in secondary cities.
100%
 Growth in penetration rates will begin to slow long before
they reach 100%, as network coverage and affordability,
although improving, will continue to present challenges.
Countries such as Kenya, Tanzania and Uganda will have
lower penetration rates than the average for the region
overall because of their predominantly rural populations.
80%
60%
40%
20%
0%
2010
 Mobile penetration rates are nearing saturation in the major
urban centres of Sub-Saharan Africa. As a result, operators
will focus increasingly on bringing services to non-urban
areas. National broadband plans in countries such as Kenya
and Nigeria will help to further this trend.
2011
Ghana
South Africa
Uganda
© Analysys Mason Limited 2012
2012
2013
Kenya
Sudan
SSA
2014
2015
2016
Nigeria
Tanzania
 We do not expect 2.1GHz technologies to be deployed
outside urban centres. 800MHz spectrum, which is more
suitable for rural coverage, will not become available until
2015 at the earliest. Re-farming of 900MHz spectrum to
support HSPA would allow operators to bring services to rural
areas sooner, but this measure is still under discussion.
 Growth in mobile penetration will come primarily from
handsets and not from new mobile broadband SIMs because
of low PC penetration rates.
24
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Despite strong growth in 3G connections, 2G will continue to be the
dominant mobile technology in the region throughout the forecast period
Figure 13: Mobile connections by technology generation, and 3G penetration,
Sub-Saharan Africa, 2010–2016 [Source: Analysys Mason, 2012]
800
25%
 South Africa has the highest proportion of 3G SIMs in the
region, at 15% in 2010, and this will increase to 39% in 2016.
Nigeria and Tanzania will experience similar increases in the
proportion of 3G SIMs.
700
Connections (million)
500
15%
400
10%
300
200
5%
100
0
0%
2010 2011 2012 2013 2014 2015 2016
2G
3G
© Analysys Mason Limited 2012
4G
3G penetration
Percentage of the population
20%
600
 3G penetration in Sub-Saharan Africa will grow from 3%
of the population in 2010 to 19% in 2016, when mobile
broadband connections will account for 21% of 3G SIMs.
 A key driver of the growth in 3G penetration will be the
availability of more-affordable 3G smartphones (priced at less
than USD100), as the volume of smartphones worldwide
increases in response to demand from developing markets.
 2G penetration will decline from 94% of SIMs in 2010, to 69%
in 2016.
 3G is still in the early stages of maturity, so we do not
expect 4G (that is, LTE) to feature in the region until 2013 at
the earliest (and then only in a few countries, such as Kenya
and South Africa). It will account for only 4% of mobile
connections by 2016.
25
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Mobile voice revenue will grow at a much slower rate than connections
because of sustained price pressure
 Mobile voice revenue will grow at a CAGR of 9% from 2010
to 2016, whereas non-voice revenue will rise at a CAGR of
28%.
Figure 14: Mobile revenue by type, and mobile ASPU and ARPU,
Sub-Saharan Africa‚ 2010–2016 [Source: Analysys Mason, 2012]
80
10
 We anticipate consolidation in markets such as Nigeria and
Uganda, which would tend to stabilise pricing, but the
acquisition of price-sensitive users from outside urban areas
will result in sustained price pressure.
9
70
7
50
6
40
5
4
30
3
20
2
10
1
0
0
2010 2011 2012 2013 2014 2015 2016
Voice
Non-voice
ASPU
ARPU
© Analysys Mason Limited 2012
Termination
ASPU/ARPU (USD)
Revenue (USD million)
8
60
 Mobile non-voice services’ share of mobile revenue will
increase from 13% in 2010 to 21% in 2016.
 ASPU and ARPU will be flat in US dollar terms, but we
expect these values to decline in local currency terms
throughout the region as a result of price pressure.
 New users from previously underserved areas, who are
particularly price sensitive, will make up a growing proportion
of the mobile subscriber base, which will place downward
pressure on pricing.
26
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Mobile service usage and the number of outgoing voice minutes will
increase as the price per minute declines
Figure 15: Outgoing mobile voice minutes by country, Sub-Saharan Africa,
2010–2016 [Source: Analysys Mason, 2012]
600
 Nigeria is second only to South Africa in terms of outgoing
mobile voice traffic, although MoU in Nigeria is considerably
lower than in the rest of the region.
500
Minutes (billion)
 The total number of outgoing mobile minutes in the region
will grow at a CAGR of 14% during the forecast period, from
227 billion in 2010 to 504 billion in 2016.
 Most new mobile subscribers will be lower-income users,
who tend to be net receivers of calls.
400
 We expect to usage to increase among established
subscribers as the price per minute of mobile voice
services declines.
300
200
100
0
2010 2011 2012 2013 2014 2015 2016
Ghana
Kenya
Nigeria
South Africa
Sudan
Tanzania
Uganda
Rest of SSA
© Analysys Mason Limited 2012
27
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Fixed retail revenue in Sub-Saharan Africa will grow only slightly because
of the decline in fixed voice revenue
Figure 16: Fixed retail revenue by type, Sub-Saharan Africa, 2010–2016
[Source: Analysys Mason, 2012]
9
 Fixed voice revenue will decline at a CAGR of 6%. South
Africa and Kenya are the only countries in which more than
10% of retail revenue comes from fixed voice, and both are
experiencing revenue decline. Ghana and Sudan are both
forecast to experience growth in fixed voice revenue, albeit
from extremely low bases.
8
Retail revenue (USD billion)
 Fixed retail revenue will dip slightly during the forecast
period, but will generate approximately the same amount of
revenue in 2016 as in 2010: USD8.5 billion.
7
6
1
 Fixed broadband revenue will increase at a CAGR of 16%.
However, this is mostly a reflection of the situation in South
Africa, because fixed broadband is not a significant market in
most of the other countries in the region. PSTN infrastructure
tends to be limited to major urban centres, and is often of
poor quality, which limits the market for DSL services.
Fixed–wireless technologies, such as WiMAX, are not
subject to the same infrastructural challenges, and are used
to support fixed broadband services.
0
 The growth in revenue from business network services, at a
CAGR of 8%, is largely a function of economic growth.
5
4
3
2
2010
2011
2012
2013
2014
Business network services
Dial-up
Fixed broadband
Fixed voice
© Analysys Mason Limited 2012
2015
2016
28
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Fixed broadband subscriptions will drive growth in the fixed market in
Sub-Saharan Africa, while fixed voice subscriptions will be flat
Figure 17: Fixed line connections by country, Sub-Saharan Africa,
2010–2016 [Source: Analysys Mason, 2012]
25
 South Africa, the wealthiest of the countries modelled, has an
exaggerated effect on the overall Sub-Saharan Africa market
because it accounted for 31% of fixed voice lines in 2010
and 46% of fixed broadband subscriptions. Most other
countries in the region have very limited fixed network
infrastructure, which is limited to major urban centres.
20
Connections (million)
 The number of fixed connections (which include all copper,
cable, fixed wireless and fibre connections with at least one
voice or data service) in Sub-Saharan Africa will increase
from 17.3 million in 2010 to 22.2 million in 2016, at a CAGR
of 4%.
15
 Operators in the region are likely to make only limited
investments in fixed infrastructure outside their established
footprints, mainly to increase backbone and mobile backhaul
capacity.
10
 Overall, the number of fixed broadband subscriptions will
grow at a CAGR of 22% during 2010–2016.
5
 Fixed voice subscriptions will be flat in the region as a whole,
with the highest growth coming from Sudan.
0
2010 2011 2012 2013 2014 2015 2016
Ghana
Kenya
Nigeria
South Africa
Sudan
Tanzania
Uganda
Rest of SSA
© Analysys Mason Limited 2012
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Executive summary
Key implications
Market definition and methodology
Sub-Saharan Africa forecast
Country forecasts
About the authors and Analysys Mason
© Analysys Mason Limited 2012
29
30
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Ghana’s telecoms markets are highly competitive and growth is forecast
to track that in the region as a whole, except in the fixed voice market
Figure 18: Retail revenue by service type, Ghana, 2010–2016 [Source:
Analysys Mason, 2012]
Service type
Change
2010–2011
CAGR
2011–2016
Fixed voice
–6.7%
2.1%
1.2
Fixed broadband
18.5%
11.6%
1.0
Business network services
7.5%
4.8%
Mobile voice
12.6%
6.5%
Mobile messaging
24.1%
10.6%
Mobile handset data
98.5%
27.4%
Mobile broadband
34.7%
44.3%
Total
14.4%
8.2%
1.6
1.4
Retail revenue (USD billion)
Figure 19: Growth rates of retail revenue by service type, Ghana, 2010–2016
[Source: Analysys Mason, 2012]
0.8
0.6
0.4
0.2
0.0
2010 2011 2012 2013 2014 2015 2016
Business network services
Fixed broadband
Mobile handset data
Mobile messaging
© Analysys Mason Limited 2012
Dial-up
Fixed voice
Mobile broadband
Mobile voice
Figure 20: Ghanaian population, GDP and GDP per capita, 2010 [Source:
Analysys Mason, 2012]
Population
24 515 000
GDP (USD billion)
32
GDP per capita (USD)
1303
31
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Ghana’s mobile market will benefit from additional spectrum and more
competition
Mobile market
Fixed market
 More spectrum will become available during the forecast
period to relieve congestion and better support mobile data
services. Ghana’s telecoms regulator says that digital
dividend spectrum will be released in 2013 – earlier than the
original target of 2014 – but we do not anticipate that LTE will
become available before 2015. The regulator may also
revoke unused licences and re-allocate the spectrum
released.
 The fixed voice market will stabilise and show slight growth,
as Airtel and Vodafone compete against fixed–wireless
operators.
 Dilution of ARPU will continue, and increasing usage will
not be able to offset the decline in prices. The rate of ARPU
decline will accelerate as more low-income subscribers adopt
mobile services.
 Globacom (Glo) was due to launch services in Ghana in
January 2012 and will be aggressive on price in order to gain
market share quickly. It has already begun a campaign to
allow people to reserve Glo phone numbers, and has painted
some low-income neighbourhoods green as a marketing ploy.
 SIM penetration is expected to reach 100% by population in
2016. However, multiple-SIM usage is high in Ghana (each
user has about 1.8 SIMs), so the actual penetration rate is 54%.
 The government is proposing tax incentives and tax holidays
for network operators that are willing and able to deploy voice
and data services in rural Ghana.
© Analysys Mason Limited 2012
 The fixed broadband market will continue to be limited
because of low PC penetration and lack of widespread
suitable fixed network infrastructure.
32
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Kenya’s telecoms market is more balanced than most in the region, and
will outpace the region as a whole in mobile voice and broadband growth
Figure 21: Retail revenue by service type, Kenya, 2010–2016 [Source:
Analysys Mason, 2012]
Service type
2.5
Retail revenue (USD billion)
Figure 22: Growth rates of retail revenue by service type, Kenya, 2010–2016
[Source: Analysys Mason, 2012]
Change
2010–2011
CAGR
2011–2016
5.3%
–1.2%
Fixed broadband
30.1%
13.1%
Business network services
10.3%
10.1%
Mobile voice
21.4%
12.1%
Mobile messaging
14.1%
8.8%
Mobile handset data
43.1%
15.3%
Mobile broadband
76.3%
27.0%
Total
20.9%
10.9%
Fixed voice
2.0
1.5
1.0
0.5
0.0
2010 2011 2012 2013 2014 2015 2016
Business network services
Fixed broadband
Mobile handset data
Mobile messaging
© Analysys Mason Limited 2012
Dial-up
Fixed voice
Mobile broadband
Mobile voice
Figure 23: Kenyan population, GDP and GDP per capita, 2010 [Source:
Analysys Mason, 2012]
Population
41 405 000
GDP (USD billion)
32
GDP per capita (USD)
786
33
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Kenya should gain more-affordable mobile services and more options
for fixed services
Mobile market
Fixed market
 The decline in the price per minute of mobile calls will slow
after MTR reductions are halted. Airtel and Essar Telecom
Kenya (yu) will continue to put downward pressure on pricing
with their high volume/low price strategies.
 In 2010, the Kenyan government sold off Kenya Power and
Lighting Company (KPLC), which soon signed infrastructuresharing agreements with Jamii Telecommunications,
Safaricom and Wananchi Group. These three operators now
have access to KPLC’s fibre network (which runs alongside
the national electrical grid), and this has opened up the
broadband market.
 Growth in penetration will slow as the cities become saturated,
given that 70% of the population lives in rural areas.
 Growth in the usage of handset data services will be driven
by the increasing availability of 3G and, eventually, LTE:
 Safaricom has offered 3G since 2008, Orange launched
3G in 2011 and HSPA+ in Nairobi in September 2011, and
Airtel plans to launch 3G in March 2012
 the Kenyan regulator has proposed a wholesale model for
roll-out of LTE, which is expected to be available in some
parts of the country in 2012. However, we do not expect
commercial services to be available until 2013
 Kenya's Ministry of Information and Communication is
drafting regulations to address last-mile Internet
connectivity across the country.
© Analysys Mason Limited 2012
 The national fibre backbone is now managed by a
consortium, rather than Orange, which should lead to lower
broadband costs.
 Operators are now looking to fixed services in order to
reduce their reliance on mobile voice. For example:
 Airtel Kenya has an agreement with AccessKenya to
provide fixed voice service over AccessKenya’s fibre-optic
network
 Orange Kenya plans to launch triple-play services in the
second half of 2012, and to seek funds by mid-2012 to
invest in data and cloud computing services
 Safaricom plans to build its own fibre-optic network in
order to capture a larger share of the data market.
34
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Nigeria is the largest mobile market in the region, and will experience
faster-than-average growth in mobile non-messaging data revenue
Figure 24: Retail revenue by service type, Nigeria, 2010–2016 [Source:
Analysys Mason, 2012]
Service type
Change
2010–2011
CAGR
2011–2016
–30.6%
–8.9%
Fixed broadband
71.4%
23.6%
Business network services
23.9%
8.7%
Mobile voice
17.5%
8.8%
8
Mobile messaging
34.3%
13.1%
6
Mobile handset data
70.0%
22.8%
4
Mobile broadband
218.6%
29.9%
2
Total
16.5%
9.2%
18
16
Retail revenue (USD billion)
Figure 25: Growth rates of retail revenue by service type, Nigeria, 2010–2016
[Source: Analysys Mason, 2012]
Fixed voice
14
12
10
0
2010 2011 2012 2013 2014 2015 2016
Business network services
Fixed broadband
Mobile handset data
Mobile messaging
© Analysys Mason Limited 2012
Dial-up
Fixed voice
Mobile broadband
Mobile voice
Figure 26: Nigerian population, GDP and GDP per capita, 2010 [Source:
Analysys Mason, 2012]
Population
153 700 000
GDP (USD billion)
253
GDP per capita (USD)
1664
35
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Nigeria will become increasingly focused on mobile services,
as traditional wireline markets continue to decline
Mobile market
Fixed market
 A large proportion of Nigeria’s population (41–42% in 2010) is
aged 14 years and under. This will reduce the level of mobile
penetration that operators can achieve in the market.
 The incumbent, Nigeria Telecommunications (NITEL), has
been unable to adequately address its network quality and
coverage issues, so most operators do not use the PSTN to
deliver services. Operators have instead turned to fixed
wireless technologies to deliver voice services.
 We expect that dilution of ARPU will continue in the long term,
and increasing usage will not be able to offset the price decline.
 The government has proposed an open-access broadband
policy that separates passive, active and retail layers. The
Ministry of Communication Technology said that it would
accelerate the roll-out of broadband infrastructure in order
to increase broadband penetration to 12% by 2015.
 Data prices are likely to be eroded because of new
international connectivity. Competition from WiMAX and
HSPA networks is intensifying.
 The transition from analogue to digital broadcasting, which is
set to begin in 2012, will make more spectrum available. This
will provide better support for mobile data services.
 Network coverage will increase, but not dramatically. For
example, MTN Nigeria increased its coverage from 84.6% in
2010 to 85% in November 2011. The new entrant Etisalat is
planning to increase its population coverage from about 70%
to 80% over the next five years.
© Analysys Mason Limited 2012
 WLL-based voice will be the main ‘fixed’ voice technology.
Growth in WLL will be driven by demand from the business
sector, which will value the fixed aspect of the service. In the
residential segment, WLL will be under increasing pressure
from mobile voice, and residential WLL take-up will remain
modest in the forecast period.
 The development of the broadband market has been
hampered by poor infrastructure and unreliable power supply.
The PSTN network in Nigeria has limited coverage, so xDSL
and FTTx will account for a minor proportion of the overall
broadband market and will mainly serve business customers.
PC penetration also remains below 3%.
36
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
South Africa has the most-mature telecoms market in the region and
accounts for much of its revenue, but it will have lower growth rates
Figure 27: Retail revenue by service type, South Africa, 2010–2016 [Source:
Analysys Mason, 2012]
Service type
25
Retail revenue (USD billion)
Figure 28: Growth rates of retail revenue by service type, South Africa,
2010–2016 [Source: Analysys Mason, 2012]
Change
2010–2011
CAGR
2011–2016
Fixed voice
–6.1%
–5.7%
Fixed broadband
15.8%
5.0%
Business network services
5.4%
6.2%
Mobile voice
6.0%
4.2%
Mobile messaging
8.5%
9.0%
Mobile handset data
26.8%
12.6%
Mobile broadband
84.6%
14.2%
7.9%
4.8%
20
15
10
5
Total
0
2010 2011 2012 2013 2014 2015 2016
Business network services
Fixed broadband
Mobile handset data
Mobile messaging
© Analysys Mason Limited 2012
Dial-up
Fixed voice
Mobile broadband
Mobile voice
Figure 29: South African population, GDP and GDP per capita, 2010
[Source: Analysys Mason, 2012]
Population
49 055 000
GDP (USD billion)
365
GDP per capita (USD)
7446
37
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
South Africa should experience greater mobile data usage and greater
fibre availability
Mobile market
Fixed market
 Vodacom, MTN and Cell C all have advanced HSPA+ mobile
networks and have been pricing mobile broadband services
aggressively.
 Local loop unbundling issues should be resolved in 2012.
This will affect fixed broadband more than fixed voice. MWEB
has launched a social media campaign to pressurise
Telkom SA into separating voice and data services and to
provide ‘naked ADSL’.
 We expect Cell C and 8ta to continue to be aggressive on
price, and that 8ta will also offer fixed–mobile bundles.
Operators have not yet reduced prices, despite the
introduction of lower MTRs.
 Awards of 800MHz and 2.6GHz spectrum for LTE are
planned for 2012, including awards to at least two, and
possibly three, new operators and to two wholesale mobile
broadband operators. However, operators are only expected
to launch LTE services in urban centers. Cell C, 8ta and MTN
are currently running LTE trials.
 MTN and Vodacom announced spending plans in late 2011.
Vodacom will focus on improving network stability and
upgrading, while MTN plans to increase the number of 3G
base stations to help to support its goal of doubling its data
revenue over the next four years.
 ACE and WACS cables, which are planned to come online in
2012, will help to reduce broadband costs. Increasing the
number of wholesale capacity providers (backbone and
metro) will also help to reduce these costs.
© Analysys Mason Limited 2012
 Operators are moving to increase fixed broadband speeds.
For example:
 Internet Solutions is currently running trials of a
fibre-to-the-home (FTTH) network solution
 Telkom SA plans to increase its broadband speeds to
40Mbps by 2015 and to raise introductory speeds to
2Mbps.
 MTN is investing in and expanding partnerships for fibre
connectivity, including agreements with Metrofibre Networx,
Neotel and Telkom SA. Other operators with networks that
may allow for deployment of fibre-based services to
enterprises and consumers include Dark Fibre Africa,
BWIRED and Dartcom.
38
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Sudan’s telecoms market is in an earlier stage of development than most
others in the region, so has higher growth rates than the region overall
Retail revenue (USD million)
Figure 30: Retail revenue by service type, Sudan, 2010–2016 [Source:
Analysys Mason, 2012]
Figure 31: Growth rates of retail revenue by service type, Sudan, 2010–2016
[Source: Analysys Mason, 2012]
3000
Service type
2500
Fixed voice
Change
2010–2011
CAGR
2011–2016
–0.5%
10.7%
–32.0%
24.6%
7.7%
2.1%
Mobile voice
13.5%
6.6%
Mobile messaging
51.8%
20.4%
Mobile handset data
97.4%
50.6%
Mobile broadband
34.9%
20.8%
Total
15.8%
10.4%
Fixed broadband
2000
Business network services
1500
1000
500
0
2010 2011 2012 2013 2014 2015 2016
Business network services Dial-up
Fixed broadband
Fixed voice
Handset data
Mobile broadband
Messaging
Mobile voice
© Analysys Mason Limited 2012
Figure 32: Sudanese population, GDP and GDP per capita, 2010 [Source:
Analysys Mason, 2012]
Population
43 740 000
GDP (USD billion)
66
GDP per capita (USD)
1520
39
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Sudan will benefit from greater mobile network coverage and continued
growth in services based on fixed–wireless technology
Mobile market
Fixed market
 No new licences are anticipated (at least in the north). Canar
Telecommunication wants one, but the regulator has not
indicated that there will be any awards.
 The PSTN network in Sudan has very limited coverage and
is available only in the main cities. As a result, we expect the
trend towards fixed–mobile substitution of voice services to
continue.
 All operators are currently rolling out mobile networks in
populated regions that have previously had poor network
coverage (such as Darfur).
 DSL is the only mode of access to fixed broadband in Sudan,
and is limited to the main cities.
 Much of the growth will come from low-value subscribers as
services become affordable, but strong growth from business
segments should be expected.
 VoIP is illegal. FWT is becoming the dominant access
technology and accounted for 84% of Thabit’s fixed lines
in 2010.
 As penetration increases, ARPU will quickly be eroded
because of the adoption of mobile services by low-income
subscribers. In the short term, we assume that market
competition will force a downward movement in unit prices
that will not be compensated for by a commensurate
increase in usage. However, in the long term, dilution of
ARPU will continue, and increasing usage will not be able to
offset the decline in prices.
 Given the poor infrastructure, the low penetration and the
trend towards fixed–mobile substitution, it is unlikely that
either MTN or Zain will enter the fixed market.
© Analysys Mason Limited 2012
 Growth in the number of fixed–wireless subscribers has
arrested the decline in fixed-line numbers.
40
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Tanzania’s mobile market is extremely competitive, unlike its fixed market,
but the country’s growth rates will lag those for the region overall
Retail revenue (USD billion)
Figure 33: Retail revenue by service type, Tanzania, 2010–2016 [Source:
Analysys Mason, 2012]
Figure 34: Growth rates of retail revenue by service type, Tanzania,
2010–2016 [Source: Analysys Mason, 2012]
1.4
Service type
1.2
Fixed voice
1.0
0.8
0.6
0.4
0.2
0.0
2010 2011 2012 2013 2014 2015 2016
Business network services
Fixed broadband
Mobile handset data
Mobile messaging
© Analysys Mason Limited 2012
Dial-up
Fixed voice
Mobile broadband
Mobile voice
Change
2010–2011
CAGR
2011–2016
3.0%
0.1%
Fixed broadband
15.5%
14.6%
Business network services
14.1%
10.6%
Mobile voice
21.1%
8.3%
Mobile messaging
18.3%
8.8%
Mobile handset data
40.5%
14.3%
Mobile broadband
31.5%
14.4%
Total
20.3%
8.4%
Figure 35: Tanzanian population, GDP and GDP per capita, 2010 [Source:
Analysys Mason, 2012]
Population
45 715 000
GDP (USD billion)
23
GDP per capita (USD)
521
41
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Mobile data services in Tanzania should grow as costs decline, while the
fixed market will continue to be challenging
Mobile market
Fixed market
 Tanzania’s 74% rural population limits penetration growth,
although the government plans to expand the national
backbone network to help to address this. The Tanzania
Communication Regulatory Authority (TCRA) is promising to
improve telecoms access in rural areas under the Ministry of
Science and Technology’s ‘Equal Opportunity Trust Fund’.
 Tanzania’s predominantly rural population limits the
addressable market for fixed services, as there is little fixed
infrastructure outside the cities. We expect this situation to
remain unchanged throughout the forecast period.
 A relatively high proportion of revenue comes from non-voice
services (nearly all from messaging). 3G services have been
available since 2007, but mostly in cities.
 Rural NetCo is rolling out a rural 3G network based on
W-CDMA. An Ericsson initiative to develop a multi-operator
core network (MOCN) is driving this effort.
 Broadband services are currently unaffordable for most of the
population. As in other countries, we expect that the advent
of more cables and fibre access will reduce broadband
pricing and drive an increase in take-up. However, the
incumbent fixed operator, Tanzania Telecommunications
Company (TTCL), manages the network, which raises some
concerns about how effective the network will be in reducing
broadband costs.
© Analysys Mason Limited 2012
42
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Uganda’s telecoms market is the most dependent on mobile of those in the
countries modelled, and its growth will outpace the region in most areas
Retail revenue (USD billion)
Figure 36: Retail revenue by service type, Uganda, 2010–2016 [Source:
Analysys Mason, 2012]
Figure 37: Growth rates of retail revenue by service type, Uganda,
2010–2016 [Source: Analysys Mason, 2012]
1.4
Service type
1.2
1.0
0.8
0.6
0.4
0.2
0.0
2010 2011 2012 2013 2014 2015 2016
Business network services
Fixed broadband
Mobile handset data
Mobile messaging
© Analysys Mason Limited 2012
Dial-up
Fixed voice
Mobile broadband
Mobile voice
Change
2010–2011
CAGR
2011–2016
Fixed voice
10.8%
–1.3%
Fixed broadband
57.0%
36.1%
Business network services
15.6%
11.1%
Mobile voice
19.9%
10.6%
Mobile messaging
22.6%
12.8%
Mobile handset data
29.1%
14.4%
Mobile broadband
56.6%
26.5%
Total
20.5%
11.1%
Figure 38: Ugandan population, GDP and GDP per capita, 2010 [Source:
Analysys Mason, 2012]
Population
34 345 000
GDP (USD billion)
18
GDP per capita (USD)
523
43
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Consolidation in Uganda should help to rationalise mobile pricing, and the
market overall will benefit from continued fibre deployments
Mobile market
Fixed market
 Mobile SIM penetration will increase quickly in the medium
term – to about 67% of the population by 2014 – and will then
reach saturation because of the high proportion of the
population that lives in rural areas (about 87%) and low GDP
per capita. Kampala and the most-populated 90 cities and
towns account for only 4% and 13%, respectively, of the total
population.
 Infrastructure issues and the low penetration rate for PCs
(the average number of PCs per household stood at 0.16 in
2009) will limit the expansion of broadband services.
 Consolidation will sustain the level of ARPU in the market in
the medium term, as well as limit the increase of multiple-SIM
usage.
 Mobile operators should be in a position to attract a large
share of the broadband subscribers because of the poor
quality of fixed lines and the low level of fixed teledensity in
Uganda.
 The Uganda Communications Commission began a review of
interconnection rates in November 2011, which it is expected
to complete in early 2012. In other emerging countries,
operators have passed on interconnection cost savings to
end users, which has resulted in an increase in mobile
penetration.
© Analysys Mason Limited 2012
 As of October 2011, more than 1500km of fibre had been
deployed in the first two implementation phases of the
National Data Transmission Backbone Infrastructure project.
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
Executive summary
Key implications
Market definition and methodology
Sub-Saharan Africa forecast
Country forecasts
About the authors and Analysys Mason
© Analysys Mason Limited 2012
44
The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
45
About the authors
Roz Roseboro (Principal Analyst) is the lead analyst for Analysys Mason’s The Middle East and Africa research programme. Her
primary areas of specialisation are market drivers in growth markets and understanding the opportunities for operators and vendors in
these markets. She also specialises in professional services needed to deliver infrastructure services and in network equipment
manufacturers. Roz has nearly 20 years’ experience in market research, marketing and product management. She spent five years at
RHK, where she ran the Switching and Routing programme, and later the Business Communication Services programme. She spent
nine years at Motorola, working in IT product development and radio and mobile phone product management. Roz holds a BA in
English from the University of Massachusetts, Amherst and an MBA in Marketing, Management and International Business from the
J.L. Kellogg Graduate School of Management at Northwestern University.
William Hare (Analyst) joined Analysys Mason’s Consulting division in 2007, before transferring to the Research division in 2010. He
works primarily on Analysys Mason’s consumer services research, as well as contributing to the modelling behind the Telecoms
Market Matrix, wireless traffic forecasting and the Connected Consumer survey. His primary specialisations include business and
market modelling and data analysis, for both the mobile and fixed telecoms markets. He read mathematics at the University of
Cambridge.
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
46
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The Sub-Saharan Africa telecoms market: trends and forecasts 2011–2016
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