Measuring ICT Sector PerformanceDr. Christoph Stork

Research ICT Africa

Year ProjectAfrican

Countries2003

2004

2005

2006

2007

2009

ICT Sector Performance Review 7

Household e-Access & e-Usage Survey 10

SME e-Access & e-Usage Survey 15

ICT Sector Performance Review 17

Household e-Access & e-Usage Survey 17

ICT Sector Performance Review 18

ICT Sector Performance

ToolsSupply Side:

Annual reports from Operators

OECD Price Baskets

National Accounts

Demand SideUser Surveys (Household, SMEs, Institutions)

Telecom Regulatory Environment Survey (TRE)

Impact of regulatory interventionsDemand Side Supply Side

Access

UsageUsage

Affordability

Operator Performance

Operator Performance

Operator Performance

Operator Performance

Economy

Ownership(rural urban, gender, income)

Subscribers

Expenditure (total, share of disposable income)

Average revenue per user (ARPU)

No of SMS send and minutes called

Minutes of Use (MOU)

Price elasticityWTP

OECD Price basketsARPU/MOUInvestment

EBITDA MarginReturn on Equity

Revenue

Business Survey GDP contribution and employment

National accounts GDP contribution and

employment

Tool: SurveysUntapped demand: WTP of non-usersIncome elasticity of demand of usersMultiple SIM card ownershipInternet adoption: with focus on mobile internetMobile money transfer adoption and m-bankingEmployment generation and GDP contribution of SMEs and informal operatorsICT access function of public institution

Nationally Representative Surveys

2007/2008

Current market in

US$ million

Monthly untapped

market in US$ million

Untapped market as

percentage of current market

Nigeria*South Africa

NamibiaMozambique

BotswanaKenya

Zambia*SenegalGhana

Côte d'IvoireCameroonTanzania

BeninBurkina Faso

Ethiopia

686.54 65.25 9.5%

320.49 36.27 11.3%7.14 1.35 19%30.47 6.7 22%6.67 1.47 22.1%

112.11 25.69 22.9%25.96 8.2 31.6%27.54 11.33 41.2%78.23 38.4 49.1%63.13 31.44 49.8%21.29 13.14 61.7%30.79 21.42 69.6%11.38 8.26 72.6%10.77 13.71 127.3%5.29 25.68 485.7%

Willingness and ability to spend on communication of none-users exceeds current market in some countries

AFRICANS are price sensitive and will talk more if prices are lowered

Mobile Expenditure and WTP

Namibia’s digital divide at a household level (RIA 2004 & 2007 surveys)

! ! ! !! ! ! !! ! ! !! ! ! !! ! ! !! ! ! !

Households with

working...

NamibiaNamibiaNamibia UrbanUrbanUrban RuralRuralRuralUrban Rural Difference

Urban Rural Difference

Urban Rural Difference

Households with

working... 2004 2007 2004 2007 2004 2007 2004 2007

Electricity 34% 47% 78% 81% 6% 24% 72% 57%

Fixed-line 13% 17% 31% 32% 2% 8% 29% 24%

Radio 77% 73% 88% 82% 70% 66% 18% 16%

TV 31% 38% 71% 72% 5% 15% 66% 57%

Computer 5% 11% 11% 23% 0.4% 4% 11% 19%

Internet 2% 3% 4% 7% 0.0% 1% 4% 6%

Tool: OECD Mobile Basket Methodology

OECD Basket Methodology

Comparing Countries

Comparing Operators

Comparing Products

Comparing CountriesComparing cheapest product available from

dominant operators

cheapest operator

most expensive operator

Comparing the difference between cheapest in country - cheapest from dominant operators

cheapest in country - cheapest from most expensive operator

GhanaTanzania

KenyaNigeria

Ethiopia*Rwanda

BeninBotswana

TunisiaNamibiaSenegalUgandaZambia

Côte d’IvoireMozambique

South AfricaCameroon

Burkina Faso 11.048.59

7.647.4576.576.336.12

5.065.065.044.92

3.743.743.633.352.93

2.29 GhanaTanzania

KenyaNigeria

Ethiopia*Rwanda

BeninBotswana

TunisiaNamibiaSenegalUgandaZambia

Côte d’IvoireMozambique

South AfricaCameroon

Burkina Faso 12.549.3

7.647.458.15

6.66.95

6.128.96

5.065.04

7.56.87

3.747.76

5.937.26

3.04

Cheapest operator Dominant operator

GhanaTanzania

KenyaNigeria

Ethiopia*Rwanda

BeninBotswana

TunisiaNamibiaSenegalUgandaZambia

Côte d’IvoireMozambique

South AfricaCameroon

Burkina Faso 12.549.3

10.368.32

9.548.18

7.047.52

8.965.36

6.668.81

6.873.74

7.765.93

7.263.15

Most expensive operator

Cheapest Prepaid product in country in US$ Low OECD user basket

Example: Towards Cost based

Mobile Termination RatesNamibia, Kenya, South Africa

Cost based Mobile Termination rates

Economics:

Increased Competition

Lower Retail Prices

More Investment

Better Sector Performance

Dominant Operators Argue:

Higher retail prices

Lower Profits

Less investment

Cheapest product available of incumbent (MTC) in Namibia

Low User Medium User High User

106

3636

146

5050

179

119

79

296

174

83

N$/

ZAR

Sep 2005 Dec 2008 May 2010 May 2010 (2005 prices)

Performance of incumbent mobile operator in Namibia: MTC

2005 2006 2007 2008 2009

Subscribers 403,743 555,501 743,509 1,008,658 1,283,530

EBITDA Margin 61% 60.2% 52.2% 50.9% 53.8%

After tax Profit million N$ 292.9 337.2 339.6 356.2 387.5

Dividend paid in million N$ 110 80 245 221 370

Base Stations 250 (2004)

763

Investments announced into 4G LTE and WACS (N$400 million)

Regulation of Market Entry

Scarce Resources

Interconnection & facilities leasing

Tariff Regulation

Regulation of Anti-Competitive Practices

Universal Service Obligation (USO)

QoS Regulation

Average

-2 -1 0 1 2

-0.5

-0.3

-0.6

-0.6

-0.7

-0.2

-0.3

-0.2

-1.2

-1.1

-1.7

-1.4

-1.1

-0.8

-0.9

2006 2009

Telecommunication Regulatory Environment (TRE)

Example Kenya

August 2010: Most innovate Interconnection ruling in Africa:

Cost based termination rates (pure LRIC)

Off-net=On-Net prices for Dominate operator

Fair commercial agreement on SMS and money transfer interconnection or else...

Safaricom Zain Orange

52.6

67

11.3

54.2

66.8

9.9

55.2

66.6

8.9

OECD Low OECD Medium OECD High

Immediate price drop in %

Lower cross-nettariffs hitVodacomOperator's reuentte takes RB00m knockTHABISO MOCHIKOInformation Technology EditorTHE voluntary reduction in inter-connectlon rates to 89c fromR1,25 in March has wiped R800moff Vodacom's revenue for the si,xmonths to September.

The termination rates - whichoperators pay to carry each other'scalls - have been blamed for highretail tariffs paid by consumers.

Further reductions will startfrom next March until 2013, whenthe rate will fall ro 40c.

This has put Vodacom's localbusiness under intense pressure toCut costs, the company says.

Vodacom said yesterday it lostR800m in services revenue andR260m in earnings before inter-est, tax, depreciation and amorti-sation (Ebitda).

It expects a further Rl50m-R200m reduction in Ebitda ifsmall operators such as Cell C and8ta are given permission to chargeabove new termination rates,which will be 73c (peak hours) and65c (off-peak) from March.

This will be followed by a

peak in March 2012, a processcalled a glide path.

Chief financial officer RobShuter said Vodacom will continuelooking for ways to offset theexpected reduction in earnings.

Vodacom's services revenuerose 4,4o/o to R26,09bn while totalrevenue rose 5,17o to R29,5bn.However, a 41,1o/o growth in datarevenue offset the terminationrate effect on services revenue.

Ebitda rose 2,8o/o to Rg,8bn.Richard Hurst, senior analvst

of emerging markets at advisoryfirm Ovum, said the effect on earn-ings is a concern, and shows howmuch traffic is moving over Voda-com's network.

CEO Pieter Uys said althoughthe termination rate is affectingearnings and the group is on acost-reduction drive, retrench-ments are not on the radar.

"Unless there is a total disruD-tion in the market, retrenchmentswill not be on the agenda."

Vodacom's share price closedat R68,49.mochikot@bdfm.co,za

Q5lt t / Z" ' io (Svte) 'nccs uaT?Il]?"Tyfryg,!9.aaco1 CEO.P|eter Uys speaks at Voi-a.ini'r-t.ioq'rrrters in Midrand yesterday. He Said thatafthough the termination rate is affecting earnings, retrenchments are not on the ia;;; ;l;iilpu'x,ii'y ul'r<carHo

alm?$-*arEE= *= #;;ifFi=gi*E:',= E=BiE =a:c;i*e * A;+gaalir*rcE;es FFg;$i*i:EiriiE Hi[ei;s;; [e[er FsEiE;egEE*i11l1 fi-'E.E+flEEg*BlEE A

Example South Africa

Vodacom Interim ResultsVodacom South

AfricaSeptember

2009September

2010Subscribers in million

ARPU ZARMOU

APRU/MOUOperating Profit Rm

Revenue Rm

28.2 23.87125 16278 1051.6 1.54

6,841 7,170

24,371 25,697

ConclusionAssessing sector performance requires a set of tools

Combination of demand side and supply side data is crucial to:

Measure regulatory impact

Monitor policy objectives

Protect consumer interests

Provide policy advice