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The Sub-Saharan Africa telecoms market: trends and forecasts 2017–2022 based on 3Q 2017 data

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Date: 20-Mar-2018
No. of pages: 43
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This report provides:


  • a 5-year forecast of more than 180 mobile and fixed KPIs for Sub-Saharan Africa, as a whole and for 11 key countries

  • an in-depth analysis of the trends, drivers and forecast assumptions for each type ofmobile and fixed service, and for the key countries

  • an overview of operator strategies and country-specific topics, in order to highlight similarities and differences by means of a cross-country comparison

  • a summary of results, key implications and recommendations for mobile and fixed operators.


Our forecasts are informed by on-the-ground regional market experts from our topic-led research programmes and our consulting division, as well as external interviews.

In addition to our robust set of historical data, our forecasts draw on a unique and in-house modelling tool, which applies a rigorous methodology (reconciliation of different sources, standard definitions, top-down and bottom-up modelling).

Geographical    

Regions modelled:


  • Sub-Saharan Africa (SSA)


Countries modelled individually


  • Cameroon

  • Côte d’Ivoire

  • Ghana

  • Kenya

  • Nigeria

  • Rwanda

  • South Africa

  • Sudan

  • Tanzania

  • Uganda

  • Zambia

The Sub-Saharan Africa telecoms market: trends and forecasts 2017–2022 based on 3Q 2017 data

Table of Contents

8.Executive summary
9.Telecoms revenue will grow at a CAGR of 2.7% during 2017–2022 to USD46.6 billion, amidst regulatory and macroeconomic challenges
10.The positive growth in telecoms retail revenue will be largely proportional to the economic growth across SSA, except in Ghana and Nigeria
11.Geographical coverage: we model 11 telecoms markets, which will account for 68.4% of SSA’s overall telecoms service revenue in 2022
12.Key trends, drivers and assumptions for the mobile and fixed markets
13.Key recommendations for telecoms operators
14.Regional forecasts and cross-country comparison
15.Market context: the 11 countries modelled provided 50.9% of the total population in SSA and 69.6% of its telecoms service revenue in 2017
16.Key mergers, acquisitions and market entries
17.Key drivers at a glance for each market in Sub-Saharan Africa
18.Market overview: mobile and fixed data services will drive revenue growth but mobile voice will continue to dominate
19.Mobile: 3G will become the predominant technology in SSA, while 4G will account for 13.7% of mobile connections in 2022
20.Mobile: the number of connections will increase in most countries, driven by improved coverage and competition, but growth will slow down
21.Mobile: spending on non-voice services will help to slow down the ARPU decline in most countries in SSA
22.Mobile: growth rates for SIM penetration will drop to single digits in most markets despite the sustained demand for mobile services
23.Fixed: wireless access will contribute the largest share of broadband revenue, but fibre will have the highest growth rate
24.Fixed: South Africa is a regional leader in the wired broadband market thanks to its developed infrastructure and level of competition
25.Fixed: increased popularity of wireless services will cause revenue to fall, while the growth of NGA will help to stabilise ASPU over the next 5 years
26.Fixed: fixed services in SSA generally offer poor quality at a high cost, and are not accessible to the majority of the region’s population
27.Business services: enterprise revenue is small, but growing more rapidly in Sub-Saharan Africa than in other regions
28.IoT: cellular M2M revenue growth is substantial, but connectivity revenue remains small
29.Individual country forecasts
30.Ghana: non-voice services, including mobile money, will help to boost revenue despite modest growth in the number of SIMs
31.Ghana: reluctance to acquire LTE spectrum will limit its adoption, and fixed broadband will remain unaffordable for most customers
32.Ghana: modest growth in the number of mobile connections but a growing demand for data and financial services will boost revenue
33.Ghana: the forecasts for the number of handset connections and the fixed broadband revenue have been revised
34.Kenya: the mobile market has potential for growth, while cable’s popularity and fibre deployments will support the fixed market
35.Kenya: the accelerated adoption of 4G will drive traffic growth; cable will maintain its dominance of the fixed broadband market
36.Kenya: there are solid growth prospects for mobile and fixed broadband adoption will benefit from better access
37.Kenya: there is a more optimistic outlook for fibre services thanks to recent deployments and stronger than expected uptake
38.Nigeria: difficult economic conditions will continue to impact the telecoms market in terms of investment and spend
39.Nigeria: increased 4G coverage and improved smartphone affordability will support the demand for data services
40.Nigeria: there is potential room for growth in the number of SIMs despite the crowded market and challenging operating conditions
41.Nigeria: projections for fixed broadband have been revised, taking into consideration new information that has become available
42.South Africa: service revenue will grow at a modest CAGR of 1.3% during 2017–2022, driven by handset data and fixed broadband
43.South Africa: there will be sustained growth for the mobile market but the fixed market will benefit from investment
44.South Africa: the open access model for LTE will delay the release of spectrum, while investment will help boost broadband coverage
45.South Africa: the forecast for mobile interconnect revenue is now more conservative in anticipation of a regime change
46.Tanzania: service revenue will reach TZS2.97 trillion in 2022, and more than 39.7% of this will be from mobile handset data
47.Tanzania: accelerated adoption of 4G services beyond urban centres will support data traffic and revenue growth
48.Tanzania: the mobile market offers growth opportunities despite competition while the fixed market will benefit from investment
49.Tanzania: mobile voice interconnect revenue will reduce  substantially due to a new aggressive termination rates glide path
50.Uganda: mobile handset data and fixed broadband services will drive service revenue growth to almost UGX3.29 trillion by 2022
51.Uganda: 4G services will be adopted slowly because of their unaffordability, limited coverage and low smartphone penetration
52.Uganda: the growth in the number of mobile subscribers resumed in 2017, but revenue is set to decline as wireless dominates
53.Uganda: there is an optimistic short-term outlook for fixed broadband adoption but a modest projection for postpaid uptake
54.Methodology
55.Our forecast model is supported by sound market knowledge
56.Examples of forecast input drivers
57.Key drivers at a glance table: methodology [1]
58.Key drivers at a glance table: methodology [2]
59.About the author and Analysys Mason
60.About the author
61.Analysys Mason’s consulting and research are uniquely positioned
62.Research from Analysys Mason
63.Consulting from Analysys Mason

List of Figures

Figure 1: Telecoms retail revenue by service type and total service revenue, Sub-Saharan Africa, 2012–2022
Figure 2: Growth in telecoms retail revenue and nominal GDP by country, Sub-Saharan Africa, 2016–2022
Figure 3: 4G/5G share of mobile connections and next-generation access (NGA) share of fixed broadband connections by country, Sub-Saharan Africa, 2016 and 2022
Figure 4: Summary of the key trends, drivers and assumptions for Sub-Saharan Africa
Figure 5: Metrics for the 11 countries modelled individually in Sub-Saharan Africa, 2017
Figure 6: Recent and upcoming market structure changes in Sub-Saharan Africa
Figure 7: Major forecast drivers: current situation (2016) and future trajectory (2017–2022), by country, Sub-Saharan Africa
Figure 8: Total fixed and mobile telecoms service revenue, Sub-Saharan Africa (USD billion), 2012–2022
Figure 9: Mobile connections by type, Sub-Saharan Africa (million), 2012–2022
Figure 10: Telecoms retail revenue and growth rate by service type, Sub-Saharan Africa, 2012–2022
Figure 11: Fixed connections by type, Sub-Saharan Africa (million), 2012–2022
Figure 12: Mobile connections by generation, Sub-Saharan Africa (million), 2012–2022
Figure 13: Mobile ARPU by type, Sub-Saharan Africa (USD per month), 2012–2022
Figure 14: Contract share of mobile connections (excluding IoT), Sub-Saharan Africa, 2012–2022
Figure 15: Mobile data traffic per connection, Sub-Saharan Africa (MB per month), 2012–2022
Figure 16a: Mobile penetration by country, Sub-Saharan Africa, 2012–2022
Figure 16b: Mobile penetration by country, Sub-Saharan Africa, 2012–2022
Figure 17a: Mobile ARPU by country, Sub-Saharan Africa, 2012–2022
Figure 17b: Mobile ARPU by country, Sub-Saharan Africa, 2012–2022
Figure 18: Broadband connections by technology, Sub-Saharan Africa (million), 2012–2022
Figure 19: Fixed retail revenue by service, Sub-Saharan Africa (USD billion), 2012–2022
Figure 20: NGA broadband household penetration and NGA share of broadband connections, Sub-Saharan Africa, 2012–2022
Figure 21: Fixed Internet traffic per broadband connection, Sub-Saharan Africa (GB per month), 2012–2022
Figure 22a: Fixed broadband household penetration by country, Sub-Saharan Africa, 2012–2022
Figure 22b: Fixed broadband household penetration by country, Sub-Saharan Africa, 2012–2022
Figure 23a: Fixed broadband access ASPU by country, Sub-Saharan Africa, 2012–2022
Figure 23b: Fixed broadband access ASPU by country, Sub-Saharan Africa, 2012–2022
Figure 24: Total market revenue from business services, Sub-Saharan Africa, 2012–2022
Figure 25: Total IoT value chain revenue by sector, Sub-Saharan Africa, 2013–2022
Figure 26: Total fixed and mobile telecoms service revenue, Ghana (GHS billion), 2012–2022
Figure 27: Mobile connections by type, Ghana (million), 2012–2022
Figure 28: Telecoms retail revenue and growth rate by service type, Ghana, 2012–2022
Figure 29: Fixed connections by type, Ghana (thousand), 2012–2022
Figure 30: 4G and contract share of mobile connections, Ghana, 2012–2022
Figure 31: Mobile ARPU, fixed voice ASPU and fixed broadband ASPU, Ghana (GHS per month), 2012–2022
Figure 32: Mobile data traffic per connection, Ghana (MB per month), 2012–2022
Figure 33: Broadband connections by technology, Ghana (thousand), 2012–2022
Figure 34: Total telecoms service revenue – current and previous forecasts, Ghana, 2012–2022
Figure 35: Total fixed and mobile telecoms service revenue, Kenya (KES billion), 2012–2022
Figure 36: Mobile connections by type, Kenya (million), 2012–2022
Figure 37: Telecoms retail revenue and growth rate by service type, Kenya, 2012–2022
Figure 38: Fixed connections by type, Kenya (thousand), 2012–2022
Figure 39: 4G and contract share of mobile connections, Kenya, 2012–2022
Figure 40: Mobile ARPU, fixed voice ASPU and fixed broadband ASPU, Kenya (KES per month), 2012–2022
Figure 41: Mobile data traffic per connection, Kenya (MB per month), 2012–2022
Figure 42: Broadband connections by technology, Kenya (thousand), 2012–2022
Figure 43: Total telecoms service revenue – current and previous forecasts, Kenya, 2012–2022
Figure 44: Total fixed and mobile telecoms service revenue, Nigeria (NGN trillion), 2012–2022
Figure 45: Mobile connections by type, Nigeria (million), 2012–2022
Figure 46: Telecoms retail revenue and growth rate by service type, Nigeria, 2012–2022
Figure 47: Fixed connections by type, Nigeria (thousand), 2012–2022
Figure 48: 4G and contract share of mobile connections, Nigeria, 2012–2022
Figure 49: Mobile ARPU, fixed voice ASPU and fixed broadband ASPU, Nigeria (NGN per month), 2012–2022
Figure 50: Mobile data traffic per connection, Nigeria (MB per month), 2012–2022
Figure 51: Broadband connections by technology, Nigeria (million), 2012–2022
Figure 52: Total telecoms service revenue – current and previous forecasts, Nigeria, 2012–2022
Figure 53: Total fixed and mobile telecoms service revenue, South Africa (ZAR billion), 2012–2022
Figure 54: Mobile connections by type, South Africa (million), 2012–2022
Figure 55: Telecoms retail revenue and growth rate by service type, South Africa, 2012–2022
Figure 56: Fixed connections by type, South Africa (million), 2012–2022
Figure 57: 4G and contract share of mobile connections, South Africa, 2012–2022
Figure 58: Mobile ARPU, fixed voice ASPU and fixed broadband ASPU, South Africa (ZAR per month), 2012–2022
Figure 59: Mobile data traffic per connection, South Africa (MB per month), 2012–2022
Figure 60: Broadband connections by technology, South Africa (million), 2012–2022
Figure 61: Total telecoms service revenue – current and previous forecasts, South Africa, 2012–2022
Figure 62: Total fixed and mobile telecoms service revenue, Tanzania (TZS trillion), 2012–2022
Figure 63: Mobile connections by type, Tanzania (million), 2012–2022
Figure 64: Telecoms retail revenue and growth rate by service type, Tanzania, 2012–2022
Figure 65: Fixed connections by type, Tanzania (thousand), 2012–2022
Figure 66: 4G and contract share of mobile connections, Tanzania, 2012–2022
Figure 67: Mobile ARPU, fixed voice ASPU and fixed broadband ASPU, Tanzania (TZS per month), 2012–2022
Figure 68: Mobile data traffic per connection, Tanzania (MB per month), 2012–2022
Figure 69: Broadband connections by technology, Tanzania (thousand), 2012–2022
Figure 70: Total telecoms service revenue – current and previous forecasts, Tanzania, 2012–2022
Figure 71: Total fixed and mobile telecoms service revenue, Uganda (UGX trillion), 2012–2022
Figure 72: Mobile connections by type, Uganda (million), 2012–2022
Figure 73: Telecoms retail revenue and growth rate by service type, Uganda, 2012–2022
Figure 74: Fixed connections by type, Uganda (thousand), 2012–2022
Figure 75: 4G and contract share of mobile connections, Uganda, 2012–2022
Figure 76: Mobile ARPU, fixed voice ASPU and fixed broadband ASPU, Uganda (UGX per month), 2012–2022
Figure 77: Mobile data traffic per connection, Uganda (MB per month), 2012–2022
Figure 78: Broadband connections by technology, Uganda (thousand), 2012–2022
Figure 79: Total telecoms service revenue – current and previous forecasts, Uganda, 2012–2022
Figure 80a: Methodology for attributing scores to each element in the key drivers table (current and future) and impact of high scores
Figure 80b: Methodology for attributing scores to each element in the key drivers table (current and future) and impact of high scores

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