Operator Economics

The Economics of Being a Mobile Operator2
Purpose and background
 The purpose of this
presentation is to support
Ericsson employees in creating
Customer Value
 Part 1, ”The Economics of
being a Mobile Operator”
creates an increased operator
business understanding
 Part 2, ”Translating benefits in
to Monetary Values” show how
Ericsson product and services
could improve operator
business
External sources rather than Ericsson internal
sources have been used for assessments
and forward looking statements

Agenda part 1
 The Economics of being
a Mobile Operator
– The Big Picture
– Revenues
– Operating Expenses
– Capital Expenditure
– Margins
– Cash Flow
– Challenges

The Big Picture
 Market size
 Overall business model
 Level of profitability
 Some definitions

The whole picture of an operator’s
business
 Knowledge of both the
revenue and the cost structure
is necessary to understand the
dynamics of a mobile operator
 Levels and trends for the main
revenue- and cost sources are
included in the presentation
REVENUES
CAPEX*
VALUE
OPEX**
Network
Frequencies
Buildings
Implementation
Terminals
Office and staff
Subsidies
Distribution
Customer care
Churn
Advertising
Commissions
Service offering
Tariffs
Subscription growthTraffic growth Competition
Subscriber retention
Quality
Brand
Market share
Interconnect and roaming
Network operation
Source: Ericsson analysis (2005)
* Capital Expenditure, CAPEX = Investments,
e.g. the mobile network. Visible as depreciation
and amortization in the Income Statement.
** Operating Expenses, OPEX = Running Costs,
e.g. salaries and selling expenses

Recouping the investment
 It usually takes 3-5 years to
generate positive EBITDA
margin, and 5-10 years to
become cash flow positive
when setting up a mobile
operation
 When setting up new
services, its margins can be
very high, if successful. The
typical pay back time is 0-4
years
time
time
EBITDAmargin(%)
0-4 yrs 5-10 yrs
0-3 yrs 3-5 yrs
New service
New service
Mobile operation
Mobile operationIndicative
Acc.freecash
flow
Indicative

Mobile operator margins are on
average high
Depreciation and
Amortization
Interest and
Taxes
Net
Income
Typical Income Statement
for a mobile operator
Revenue OPEX
15%
15%
10%
100% EBITDA Margin
~ 40%
EBIT Margin
~ 25%
Gross Margin=Revenues – Cost of Sales (e.g. airtime costs and terminals)
EBITDA=Earnings before interest, taxation, depreciation, and amortization
EBIT=Earnings before interest and taxation
15%
Cost of sales
Gross Margin
~ 85%
45%
Referred to as OPEX
Net Margin

Mobile Operator Revenues
 Size
 Categories
 Typical ratios
 Trends

Telecom is big business
Net Sales (BUSD 2004) comparison for selected companies
Source: Infinancials (2005 )
65 12
285285
101
194
Telecom Operators
67
20
52 29
2219

The largest operators by Net Sales
Top 20 represented >60% of global revenues 2004
Operators by Net Sales 2004 (billion USD)
78,4
73,9 71,3
64,6 63,9
45,0 42,8 41,1 40,8
35,0
31,0 30,5
27,4 27,2
23,3 20,7 20,3 19,5 17,6 16,2
0
10
20
30
40
50
60
70
80
90
DT
NTTexcl.
DoCoMo
Verizon
Vodafone
FT
DoCoMo
Telecom
Italia
Telefonica
SBC
excl.Cingular
BT
NewCingular
incl.AWE
AT&T
Sprint
Kddi
ChinaMobile
MCI
Bellsouth
excl.Cingular
China
Telecom
TIM
KPN
Sources: Infinancials (2005), Annual
reports (2005), Investment banks
(2005), Ericsson analysis (2005)
Based on our Operator Monitor,
which includes >40 operators and
>80% of global operator revenues.
Fixed
Full Service
Mobile

Revenue structure: Voice is still the
dominant revenue source
Estimated average revenue distribution for mobile
operators in W. Europe and the US (2004)
Source: Strategy Analytics (2004), Ericsson analysis (2005)
DATA
OUTGOING VOICE
ROAMING
INCOMING
23,2%
6,7%
4,3%
40,2%
17,3%
15,8%
74,8%
13,8%
2,6%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
WE US
Interconnect Roaming Voice Subscription Activation Data
Bucket
pricing
trend
 There are regional
differences but voice
represents the major
share of revenues
worldwide
 In some markets,
incoming call termination
is an important revenue
source, e.g. in WE.

Average revenue per user (ARPU)
A performance indicator to be used with caution
1999 2000 2001 2002 2003 2004
Early adopters
Early majority
Late majority
Average
Illustrative
ARPU
0
10
20
30
40
50
60
70
ARPU AMPU
Smart (Phi)
Wind (Ita)
KDDI (Jap)
Telefonica Mov
(Spa)
Average Margin per User
Q404 in USD
Source: Merril Lynch (2005), Ericsson analysis (2005)
ARPU can hide underlying trends and mislead
ARPU
ARPU does not take into account profitability
Dilution effect
Comparing apples with pears! Find out what is included in the ARPU.
End user fees and interconnect? What about terminal sales?

Revenue growth drives value
But what is driving revenues?
Value
growth
Revenue
growth
Performance
& margins
=
+
Subscriber
growth/mix
Traffic
growth
New
services
Fixed traffic
substitution
Termination
and roaming
Tariff
development
Competition
Regulatory
authorities
Capital +
Investors

0
10
20
30
40
50
60
70
80
1Q
02
2Q
02
3Q
02
4Q
02
1Q
03
2Q
03
3Q
03
4Q
03
1Q
04
2Q
04
3Q
04
4Q
04
MonthlyARPU(USD)
Japan China Russia Sweden US Brazil
Several reasons to great variations
in ARPU between markets
High ARPU when
 Early stage of market adoption
 Limited competition
 High GDP per capita and high telecom
share of pocket
 Innovation - services with consumer value
ARPU’s fall when
 reaching late adopter market segments
 competition increases - tariff pressure
 services become commodities
 increasing inactive subsciptions
 multiple subscriptions
 decreasing termination fees (regulatoy)
Strong underlying like-to-like traffic growth
and increased spending usually increases
ARPUs as markets start saturating
Saturation, increased usage
Competition
Innovation
Competition
Strong volume growth compansating price pressure
Low spend, dilution effect

Shifting from ARPU focus to CRM
and market segmentation
Which are the most valuable customers?
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Early Adopters
Early Majority
Late Majority
It is better to segment users based on attitudes, spending and behaviour than way
of paying bill (postpaid-prepaid) or who pays bill (consumer-business)
Indicative ARPU difference per user segment
€perAnnum
WE revenue per market segment

0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
0,4
0,45
1Q00
3Q00
1Q01
3Q01
1Q02
3Q02
1Q03
3Q03
1Q04
3Q04
USDperminute
Global Average USA Japan Sweden UK
US vs global
average
W. Europe
postpaid
USA
Development of Revenue per Minute
Competition is pressuring tariffs, driving usage
Sources: Credit Suisse First Boston (2004), EMC World Cellular Database (2004), Merril Lynch (2005), Ericsson analysis (2005)
 Competition has forced tariffs in the US to come down much lower than most other
markets. Usage is also much higher as a result of this.
 European price cuts have not reflected in the same increase in usage. The
increasing price pressure in Europe can still lead to a sharp increase in usage.

Increasing traffic is very profitable
~80% margin on incremental traffic
Illustrative example with per minute tariff
Provided available network
capacity:
 Very high operational
gearing with on average
~75% margin per
additional traffic minute
 On data the margin on
additional traffic is ~90%On own NW
~20% of traffic
~100% margin
To other mobile
~10% of traffic
~65% margin
To fixed
~25% of traffic
~95% margin
Incoming
~45% of traffic
~100% margin
Revenue /
Cost (€)
Revenue
Cost
Average
RPM
Average
CPM

Operator A
50% market
share
Operator B
25% market
share
Operator C
25% market
share
0.10
Fixed operator
0.01
0.08
0.08
0.01
0.10
0.10 0.10
Termination fees are a significant
part of revenues and margins
The mobile termination rate (MTR) is the price for interconnecting
operators for the provision of mobile termination service. Mobile
termination is an interconnect service between an MNO’s point of
interconnection and the mobile subscriber being called.
Illustrative
 Lower termination rates
enable lower tariffs
 Regulators are driving rates
towards cost based pricing
 Mobile interconnect rates in
average 15 times fixed rates
(2004) – how does that
compare to the difference in
the cost of call termination?
Sources: OVUM (2004), Ericsson analysis (2005)

Outgoing traffic
Mobile to fixed
Mobile to mobile
Incoming traffic
Fixed to mobile
Mobile to mobile
Illustration of traffic flows (based on Europe, 2004)  Mobile to fixed traffic flows at lower cost
than fixed to mobile, which results in a
good margin for mobile operators
 No termination fees on on-net traffic -
margins increase with market share
 The profile of outgoing call volumes
continue to shift towards mobile to
mobile traffic flows at higher cost than
mobile to fixed
Margins increase with market share
Traffic patterns affect profitability
Call termination
at lower cost

Few operators score high on both
size and share of data revenues
Trend of increasing data share of revenues everywhere
Sources: EMC (2005), Ericsson analysis (2005)
Data revenues in % and BUSD Q404
E-plus
T-mobile Czech Rep.
T-Mobile UK
Bouyges France
T-Mobile Germany
Orange UK
SK Telecom
China Mobile
KDDI
NTT DoCoMo
Smart
Globe
0
0,5
1
1,5
2
2,5
3
15 20 25 30 35 40 45 50
Data share of revenues (%)
Datarevenues(BUSD)
Operators with >15% data
share of revenues are included
Mainly SMS
Mobile data leaders
Trend
 Revenues from new
services vital for future
growth as voice gradually
becomes a commodity with
flat rate or bundled pricing
 Global trend of increased
share of revenues from
data services

Sources: OVUM(2005), Ericsson analysis (2005)
KDDI, Japan: Flat rate tariff on data
lead to a sharp increase in usage
Perceived cost control is key for usage of new services
 Increased take up and usage
make investments in capacity
necessary
 First mover advantage slightly
reducing churn and increased
portion of gross adds
 Increased take up of data
services has also resulted in
increased sales of premium
content
 Some cannibalisation effect on
voice usage from increased
usage av data communication
Freecashflow
time
CAPEX & NW OPEX
Premium Content
Higher data take up
Reduced churn & Increased Market share
Revenue cap from flat rate

 Landline voice use fell for the first time in 2002
in W. Europe, trend continued in 2003-2004.
 Mobile voice represents a larger share of
revenues, than traffic
 Tariffs and availability of fixed network
service influence.
 Portugal has >50% mobile share of voice
traffic. By ~2009, mobile is expected to
overtake fixed voice traffic in Europe.
Mobile phone users start impacting
fixed traffic trends
Source: Strategy Analytics (2004), Analysys (2004), Ericsson analysis (2005)
European example: ”True mobile penetration” Same trend in all markets, but from different levels

There is life after 90!
Still good growth in subscriptions in saturating markets
Penetration varies between age segments.
Youth penetration likely to grow and subscription
will be kept for life, leading to higher penetration
in older segments
Sources: Strategy Analytics (2003), Merril Lynch (2005), Ericsson analysis (2005)
80 85 90 95 100 105 110
3Q04
Penetration (%)
Ireland
Finland
Denmark
Netherlands
Austria
Spain
Taiwan
UK
Czech Rep
Norway
Greece
Hong Kong
Portugal
Israel
Italy
Sweden
Reasons for >90% penetration are:
 more than one SIM card per person
 m2m
 non active subscriptions
 other
Presently 16 countries with >90% penetration

Mobile Operator Operating Expenses
 Size
 Categories
 Typical ratios
 Trends

Business operation is increasingly
in focus
SUBSCRIBER ACQUISITION
(18.8%)
SUBSCRIBER MGMT (9.4%)
SUBSCRIBER RETENTION (7.9%)
G&A (6.8%)
MOBILE NETWORK
CALL TERMINATION (~20%)
ROAMING (~5,7%)
TRANSMISSION
POWER, SITE RENTAL
O&M, OTHER
OTHER
MARKETING & SALES (11.4%)
Commissions, Distribution (10.3%)
Terminal Subsidy (8.5%)
NETWORK
OPERATION
(20%)
DEPRECIATION
AIRTIME
FEES
(25.7%)
G&A, SUB MGT.
(16.2%)
SUBSCRIBER
ACQUISITION &
RETENTION
(38.1%)
CAPEX
BUSINESS
RELATED
54.3%
AIRTIME &
NETWORK
RELATED
45.7%
THE
“MINUTE
FACTORY”
OPEX~
60-65% of
revenues
CAPEX~
15% of
revenues
Recent
trend
Please note: This estimate is for
European mobile operators, and is to
serve as an OPEX structure example

0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Business related
Power
O&M
Transmission
Site rental
Other
 Network operation share of
OPEX estimated to have
increased
 Number of sites will typically
drive network OPEX
 Variations in the cost split as
transmission may CAPEX or
OPEX, and the cost of power,
labor and site rental is market
specific
Breakdown of network operations
cost is very company specific
Complexity+
3G/NGN
networks in
parallell with
2G/legacy

Subscriber acquisition cost (SAC) is
the most important EBITDA influencer
Investment: terminal, commission, SIM
card, distribution, advertising, selling)
Monthly ARPU: traffic,
subscription fee, other
CAPEX, monthly OPEX: capacity,
billing, customer care, other
Terminal revenue,
connection fee  Typical levels are 100-150€ in
Europe and 350-400 € in the US
 Average SAC may increases with
competition, change in bargaining
power towards terminal suppliers,
new feature rich terminals, (e.g. 3G)
with higher ASP, increased share of
postpaid gross additions
SAC

High spenders value may be eroded
by subsidies on contract extensions
Time for break-even
(months)
-300
-200
-100
0
100
200
300
NPV late adopter on prepaid NPV early adopter on postpaid
2 4 6 8 10 12 14 15 16 17 18 19 20 21 22 23 24 25 26 ........................................................................
Contract expiry vs. Subsidy value
“Late Adopter” (low spend)
 lower acquisition cost
 generates a positive NPV sooner
 generates a lower long term value
 Focus is shifting from acquiring
new subscribers to retaining the
most valuable customers
 The retention budget must be
spent in accordance with the
preferences of the targeted
customer segment
 Which subscriber is preferable
depends on the subscriber
lifetime (churn)
Scenario: Subscriber Lifetime Value
“Early Adopter” (high spend)
 subsidies on contract extension erodes value

0
100
200
300
400
500
600
700
800
900
15% 16% 17% 18% 19% 20% 21% 22% 23% 24%
Annual churn rate
Costofchurn(millionUSD)
W. Europe APAC USA
Even a small churn reduction has
very high value
 The cost of churn equals the
cost of replacing the subscriber
with a new (SAC)
 Important reasons for churn
are price, quality (coverage and
capacity) and brand. New
handset can trigger the decision
 Avoiding churn can have
higher value for a new service
than the NPV it adds to the
business
Example: Annual cost of churn for an
operator with 10 million subscribers

Changes in churn has a significant
impact on a company’s financials
 Operators with high churn
tend to have lower EBITDA
margins
 Churn rises with the
competitiveness in the
market, which also drives
the unit SAC
 Churn can be used as an
indicator of an emerging
profitability issue
Correlation between churn rate and EBITDA margin
for 92 operators worldwide in Q404
-20%
-10%
0%
10%
20%
30%
40%
50%
60%
70%
0,0% 0,5% 1,0% 1,5% 2,0% 2,5% 3,0% 3,5%
Monthly churn Q404
EBITDA%Q404

Regional churn development
Source: Merril Lynch, Ericsson analysis (2005)
Churn has been fairly stable, but may increase depending on
competition and changes in the handset replacement life
Monthly Churn (weighted averages)
0,0%
0,5%
1,0%
1,5%
2,0%
2,5%
3,0%
3,5%
4,0%
4,5%
5,0%
Q102 Q202 Q302 Q402 Q103 Q203 Q303 Q403 Q104 Q204 Q304 Q404
NAM
LAM
WE
China
Japan/Korea
Other APAC
CEMA
GLOBAL WEIGHTED AVERAGE
Sharp increase in churn in India,
Indonesia, Philippines (various reasons,
e.g. price wars, reaching low end
segments with less loyalty, heavy
promotions)
Flat rates for voice and data

Mobile Operator Capital Expenditure
 Size
 Categories
 Typical ratios
 Trends

CAPEX to Sales has decreased
to ~15%; but slight increase 2004
CAPEX to Sales vs. EBIT %
0%
5%
10%
15%
20%
25%
30%
35%
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Capex/Sales % EBIT %
Sources: Infinancials (2005), Annual
reports (2005), Investment banks
(2005), Ericsson analysis (2005)
Averages of the world’s top 44 operators, representing >80% of global revenues (fixed and mobile)

0%
10%
20%
30%
40%
50%
60%
2000 2001 2002 2003 2004E
Europe
North America
APAC
Latin America
Global Average
APAC and LA (growth markets)
show highest CAPEX ratio
Reasons for overall decrease of
the CAPEX ratio:
 operators shift from building coverage
to capacity
 price pressure
 compensation for previous over-
investment
 declining subscriber growth
There is growth of CAPEX in
absolute terms, and equipment
CAPEX growth may be higher
Source: UBS Warburg (2004), Ericsson analysis (2005)
CAPEX to Sales per region

~50-75 of mobile operator CAPEX
is spent on the network
Equipment for the mobile network and
other assets, e.g. frequency license,
cars and buildings
Installation and site establishment is
usually included
CAPEX depreciation shown as cost in
profit- and loss statement
 hardware ~5-10 yrs
 software ~3 yrs
 frequency license ~10-20 yrs
 buildings ~30 yrs
Mobile
network
CAPEX
Other
CAPEX
ACCESS NETWORK
CORE NETWORK
TRANSMISSION
NETWORK BUILD
SERVICE NETWORK
CAPEX~15%
of revenues
Illustrative

Mobile Operator Margins
 Size
 Categories
 Typical ratios
 Trends

On average, mobile business
shows good margins
Global Wireless Ebitda Margin
20%
25%
30%
35%
40%
45%
1Q99
3Q99
1Q00
3Q00
1Q01
3Q01
1Q02
3Q02
1Q03
3Q03
1Q04
-20%
-10%
0%
10%
20%
30%
40%
50%
2002 2003 2004E 2005E
EBITDA(%)
China Mobile China Unicom Vodafone Group
Telefonica Moviles TIM America Movil
EBITDA margin of some key Ericsson customers
Sources: UBS (2004), Ericsson analysis (2005)

Capital intensive industries enable
high margins
R2
= 0,818
0
2
4
6
8
10
12
14
16
18
0 2 4 6 8 10 12 14 16 18 20
EBIT margin %
Capex/sales%
Telecoms 04
Utilities 04
Energy 04
Basic Materials 04
Technology 04
Consumer, Cyclical 04 Industrial 04
Consumer, Non-Cyclical 04
Sources: Ericsson analysis (2005), UBS Warburg (2004)
Telecoms vs. other industries
 Telecom has been able
to deliver high margins,
demanding high capital
intensity
 Top line growth slows,
decreasing capex ratio
and potentially margins
 Industry needs to focus
on value creation to find
growth and maintain
margins
Trend*

Challenges
 Differentiation
 Growth
 Scale and operational
excellence

Different needs in different stages
Sources: Merril Lynch (2003), Ericsson analysis (2005)
Different
phases are
characterized
by different
business
needs, which
put different
requirements
on vendors
Investment Growth Maturity
Heavy expenditures
• New infrastructure
• Market investments
• Risk/opportunity analysis
• Early adopter strategy
Expansion
• Positive return
• Building brand
• Mass market channel
strategy
Best-in-class
• Economies of scale
• Cost effectiveness
• Maximize return
• Service differentiation
Business
Issues
Yearly Returns
Pioneers Early and Late
Majority / Laggards
Consumer
Adoption
Early Adopters /
Early Majority
Telecom
1999?
Telecom
2004?
Telecom
2009?
Cooperation / ConsolidationFragmentation

20%
25%
30%
35%
40%
45%
50%
55%
60%
-20% -10% 0% 10% 20% 30% 40% 50% 60%
Revenue growth in 2003 and 2004
EBITDAmarginin2003and2004
Growth of revenues is stagnating
Margins stable, but slightly down 2004
General decline of growth rates. EBITDA margins pressured in competitive market (USA, Japan) and
growth markets, e.g. China. Consolidation and operational excellence is likely to increase margins again.
Total market
China TelecomChina Mobile
Bell South
AT&T
KDDI
Telekom Italia
Deutsche
Telekom
KPN
Telefonica
France Telecom
VodafoneSBC
Verizon
Cingular
BT Group
DoCoMo
Sources: Infinancials, Annual reports, Investment banks, Ericsson analysis (2005)

BUSINESSCONCEPT
GROWTH
Source: Ericsson analysis
Operators are starting to explore
alternative growth strategies
NEWEXISTING
ORGANIC MERGERS & ACQUISITIONS
Operators enter related
business segments, e.g. by
triple play bundles
Mobile TV launched in several
markets
Most operators still show risk
aversion
DoCoMo is exploring growth in the
credit card and venture capital
businesses
Major consolidation in the US
market to grow business and ease
competitive pressure
Signs of increased activity from
multi-country operators, looking to
expand in EU, CEMA, LA and Asia
Increase usage and ARPU by tariff
schemes, data and enhanced voice
services
Focus shifting to subscriber retention,
and 2G to 3G migration
Fixed substitution initiatives by mobile
operators, convergence by integrated

Responding to growth stagnation
Increased focus on business issues
Pre-configured easy to use phones
Education at sales point
Defend mobile termination fees
Increase share of termination on own
and partner networks
Reduce SAC by lower subsidies and
commissions
Utilize scale to reduce cost for terminals and
thereby subsidies
Reduce churn (brand, tariffs, quality, services)
Selective retention efforts e.g. for subsidies on
contract extensions
General: Reduction of G&A and labor costs
Synergies from alliances and acquisitions
Operational excellence
Outsourcing and hosting
Network sharing
Vendor selection/Cost of ownership
Reduced complexity of systems
Fewer sites
Own sites and transmission
Billing
Customer Care
Airtime Fees
197 BUSD (25%)
Network Operation
157 BUSD (20%)
Marketing and Sales:
220 BUSD (28%)
CoS&OPEX:
786 BUSD
Other: 31 BUSD (4%)
Subscriber Acquisition
and Retention
Sales, A&P
Call termination on
outgoing calls
Roaming fees
G&A
181 BUSD (22%)
Site rental, transmission,
power, O&M
Various
Reduce bad debt
Improve charging systems
Agreements, alliances
SAC is the biggest EBITDA influencer and subsidies will be in focus when reducing costs

Agenda – part 2
 Translating Benefits in to
Monetary Values
– Total Cost of Ownership
– Revenue Generation
– Time To Market
– Quality Benefits
– Reduced Risk

The Economics of Being a Mobile Operator45 20
Low Total Cost of Ownership
– Equipment?
– Installation?
– Transmission?
– Services?
– Software?
– Training?
– Selling?
– Others?
What types of costs do
an operator face with
implementing this
solution?

Revenue Generation
– New sources of
revenue?
– Differentiated charging?
– Network rental
– Subscription Fees?
– More Airtime?
– New Data Customers?
– Site and Tower Rental?
– New Applications and
Services?
– Improved Services?
– Better Coverage?
– Transmission Rental?
What are some
expected sources
of revenue for this
solution (Both
existing and new)?

Steps in Rolling Out Solution
(TTM)
– Ordering/delivery?
– Installation?
– Training?
– Construction?
– Implementation?
– Billing?
– Upgrade network
– Testing?
– Support?
What are the various
things that have to
be done in order to
successfully
implement this
solution?

Quality Impact
– Higher Voice Quality?
– Higher Call
Connection?
– Less Dropped Calls?
– Better In-Service-
Performance?
– Improved MTBF?
– Reduced Downtime?
– Support?
– Capacity/Congestion?
– Customer Care
– Billing?
What quality concerns
does the operator have
related to this solution?

Reduced Risk/Security
– Reliability of the vendor
– Obsolescence of the
solution
– Large Capital
Expenditure
– Poor market knowledge
– Poor support for the
solution
– Lack of local support
– Future proof
– Lack of products
(terminals)?
– Financial costs
– Not right competence
What are some of the
business risks that the
operator faces by
deploying this
solution?

Operator Economics

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