Market forecasts and business case modeling for 3G and
wireless services in Europe
(Report from the 4th Workshop on Telecommunications Technoeconomics)
Dimitris Varoutas
Giovanni Gasbarrone
University of Athens
Department of Informatics and
Telecommunications, Panepistimiolopis,
Athens, GREECE
[email protected]
[email protected]
Dimitris Katsianis
Evangelos Karathanos
University of Athens, GR
University of Athens, GR
1. SUBJECT AREA – OBJECTIVES
Wireless services and applications are becoming more and more pervasive in the
business and everyday life. Wireless access wherever we need: Home, Car,
Office, Airport, Hotel as well as commercial areas. Bluetooth, Wireless Lan and
HiperLan2 are changing our wireless market view. Over the next years, about 70
licenses for UMTS (Universal Mobile Telecommunication System) spectrum will be
distributed in Europe, either through auctions or comparative hearings.
Now, more than ever, fixed and mobile operators are making critical decisions,
which will shape their business over the next ten years. The main challenge is to
maximize investment efficiency to provide wireless next-generation and mobile
data services.
The main topics covered in this paper are related to applications /services market
forecasts and evaluation issues. The scope of this paper is to provide current
trends and tools to evaluate the future wireless market evolution in Europe.
The market assumptions are based on the future scenario taking in consideration
the next generation wireless services. A smooth evolution is envisaged from 3G
mobile generation to next 4G wireless wave: a learning process from the
customers' side is highlighted and business visions are derived and crossed with
other sources (ITU). The model outputs are market figures to be used as a
starting point for evaluation. As a consequence this business evaluation tool may
provide a better understanding on the future market demand.
W-
Figure 1: Next generation technologies
A fundamental issue is to think long-term scenarios and to provide true market
projections for the mobile next generation wave. To this purpose, specific tools
and business models with a particular stress on the economics and revenues
drivers have been developed and introduced ([1],[2])
The use of simulators will facilitate the understanding of the initial situation and
its possible evolutions, as well the identification of the future economical
potentialities.
Consultants predict major trends in wireless and mobile markets (e.g. they
forecast mobile data growth and decreasing voice revenues). Available analysis
provide us with medium term forecasts covering GPRS and UMTS growth until
2005. Forecasts are based on past experience and trends estimation. Beyond
2005, only rough estimations are available.
2. STATE OF THE ART IN TECHNOECONOMICS
Several activities for technoeconomic evaluation of existing and emerging mobile
and fixed networks are spread across Europe. Here we described two of them as
presented in the 4th Workshop on Telecommunications Technoeconomics, which
organized from IST-TONIC project in Rennes, France during 14-15 May 2002 [3].
2.1 IST-TONIC Methodology
EU IST-TONIC [1] project is a precursor in the investigation of the economic side
of network deployments and the forecast of demand for mobile and fixed
services.
The techno-economic modeling was carried out using the TONIC tool, which has
been developed by the IST-TONIC project using the TERA tool [4] as the basis.
This tool is an implementation of the techno-economic modeling methodology
developed by a series of EU co-operation projects in the field. The tool has been
extensively used for several techno-economic studies [5][6][7] among major
European telecom organizations and academic institutes.
Operators
Components
Database
Suppliers
Cost Evolution
OA&M Class
Year n
Other
...
Revenues
Architectures
Geometrical Model
CashProfits
Flows
el
od
Fi
Profits
(NPV,
(NPV,IRR,
IRR,
Payback
Paybackperiod)
period)
ia
Services
Services
Decision
Decision
Index
Index
calculation
calculation
nc
User inputs
Year 2
Revenues
Investments
Year
1
Revenues
Investments
Cash Flows
Revenues
Investments
CashProfits
Flows
Investments
CashProfits
Flows
lM
Volume Class
na
Standardization
body
Operators
Market
Size
Surveys
Tariffs
Policy
Figure 2 – Techno-economic Methodology from IST-TONIC project [1]
The base of the model’s operation is a database, where the cost figures of the
various network components are reposited. These figures are constantly updated
with data gathered from the biggest European telecommunication companies. The
database outputs the cost evolution of the components over time. A dimensioning
model is used to calculate the number of network components as well as their
cost, for the set of services and the network architectures defined. Finally the
future market penetration of these services and the tariffs associated with them,
which have been calculated through market forecasts and benchmarking, are
inserted into the tool. All these data are forwarded into the financial model of the
tool that calculates revenues, investments, cash flows and other financial results
for the network architectures for each year of the study period. An analytical
description of the methodology and the tool can be found in [8].
2.2
Marketing Forecasting Model: Methodology assessments
The purpose of this market model is to construct a system that can provide with
preliminary market forecasts for a range of major telecommunication businesses.
The model is able to provide market forecasts for a range of wireless
telecommunication businesses including 3G, existing wireless as well as new
opportunities to form part of the overall business plan. The business model tool
provides good results based on the input information. However, high quality and
reliable results will require intervention from a skilled analyst to input and
interpret other factors such as likely competitive environment - therefore the user
will need to be highly skilled in understanding telecommunications markets
Figure 3: Marketing Forecasting Model [2]
The market model development involves several stages [2]:
 collection of basic macro economics data such as GDP and population
 understanding and calculating the relationships between different variables
e.g. GDP and wireless market figures (user, and revenues) ;
 collecting and interpreting benchmark competitive environment e.g. wireless
market share
 constructing a model to draw on the macro data to calculate forecast the
various elements of the revenue using the relationships and competitive
environment analysis
 Pricing reduction and volume increase follow the basic demand elasticity laws.
Therefore, higher customers' base will reflect an additional increase in
volumes and consequent additional revenues.
 Mobile e-commerce revenue is calculated according to statistical calculation on
country specific average revenue per user (ARPU). Higher confidence showed
by customers and better perception of the technology increases volume traffic
and size of transactions specific services.
 Operator revenues are extrapolated by using linear mathematical functions for
specific country mobile e-commerce revenues. The operative research
calculation follows basic assumptions (e.g. operator shares will smoothly
decrease over time as transport revenues decrease and reduction in margins
increase due to stronger competition).
3. APPROACH FOR MARKETING FORECASTS
MODELLING
3.1 Overview of next generation wireless marketing forecasts tools
The next generation wireless business case relies on a wide range of market
assumptions into the model as well as other analysis that is used to assist us in
forecasting process. The next generation wireless business model is based on a
number of modifications and extension to 3G marketing planning
The business model covers a wide range of areas including:








Demographic and macroeconomic forecast analysis in Europe (E.g. various
economic and social factors including population composition & GDP/PPI)
Wireless customers traffic profile forecasts (based on statistics evaluation)
(Voice and data ARPU)
Mobile E- Commerce (B2B, B2C, etc.)
Mobile games, gambling and entertainment
On-demand movies
Wholesale wireless services
Mobile Advertising content & distribution
Mobile Trading
3.2 Overview of 4G business case: market assumptions
The main market assumptions are the following:
 Mobile advertising will become more and more like information entertainment
services, this will reflects an increasing traffic through to web sites and
provide benefit to mobile operators trough IP services revenues.
 Direct advertising revenues will be generated in a significant size in the
medium term; the customer base growth follows 3G wave; non human users
will gain increasing market share according new social & economic behaviour .
 A learning process from the customers' side is highlighted and a consequent
market boost is forecasted
 Higher confidence gained by customers and better perception of the
technology increase volume traffic and size of e-commerce transactions
 The role of content providers and operators is to make alliances in marketing
services (co branding process) and to share voice & data traffic or revenues.
Multimedia terminal cost will be subsidised by traffic and services revenues.
 Mobile e-commerce users
The forecast of overall mobile e-commerce users is taken as due proportion of
mobile data users forecast available from statistical different sources, and
managed by specific forecasting routine software on the global mobile market.
The growth of mobile e-commerce in Europe is an average value measured
according to linear functions of Internet & mobile CAGR in European countries.
 Revenues estimation
We forecast mobile revenues by estimating the average revenue per
subscriber in western European countries, and then multiply that estimation
by the number of subscribers. Revenue per subscriber takes account of all
revenues lines (e-commerce, gambling, advertising & trading and other valueadded services).
4. RESULTS
4.1 Market Sizing: demand forecast
Historical data on wireless data and benchmarking analysis of over 200 different
countries have been used to estimate demand curves for a number of country
groupings.
There are a number of factors, which affect the levels of demand. Examples of
these include:

available investment by current and future operator(s)

fair interconnect regime

changing/alternative technology e.g. new wireless and radio technologies

price changes and price elasticity
The business model can be used to identify best-practice values, where possible,
based on all relevant international benchmarks, on the effect these factors will
have on the future demand for telecommunications services (e.g. a 50%
reduction in prices will result in a 20% increase in volume).
Euopean mobile market
180.000
160.000
140.000
4 G mobile
3G mobile
2G+ mobile
120.000
100.000
80.000
60.000
40.000
20.000
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
0
Figure 4: 3G and beyond European market
4.2
3G financial perspectives in Europe [6]
A detailed technoeconomic analysis of 3G market in Europe has been already
performed in ACTS-TERA and IST-TONIC project, based on TONIC tool. The
techno-economic prospects for a newcomer and especially for an incumbent
operator planning to deploy the UMTS technology are found to be quite positive
(Figure 5) according to this study [6].
With four operators sharing the market, the customer base appears sufficient to
achieve a positive NPV over the study period in all four cases. The IRR is higher
than the 10% discount rate, which shows that the investment is sound over this
period. Table 1 summarizes the economic results of the two basic scenarios (large
and small country) for both the incumbent and new entrant.
Table 1: Summary of the economic results for operators with 25% end market
share
NPV (M€)
IRR
Rest Value (M€)
Pay-back period
Number of customers
2009
Investments (M€)
Running costs (M€)
Incumbent
Small
Incumbent
Large
Greenfield
Small
Greenfield
Large
357
26%
8
6.8
1,100,000
4,961
29%
112
6.7
14,600,000
90
14%
28
8.3
800,000
1,992
17%
327
8.0
11,500,000
364
564
3,773
10,127
417
421
4,194
7,113
Incumbent
Small
Incumbent
Large
Greenfield
Small
Greenfield
Large
340
260
500
360
42
42
60
60
Investment
per
connected customer
(€)
ARPU per month over
the study period (€)
Specifically, the following elements were identified to have major consequences
on the profitability of this new business:
 Regulatory decisions to promote competition.
 Cost of licenses.
 Tariffs of voice and data services.
 Investment schedule.
NPV - IRR - Payback Period
6000
35
NPV
IRR
PayBackPeriod
5000
26
29
30
25
M Euros
4000
17
20
3000
14
15
1992
2000
6.8
6.7
8.3
8
1000
10
IRR (%)
Pay-back period (years)
4961
5
357
90
0
0
Incumbent S
Incumbent L
Greenfield S
Greenfield L
Figure 5 - NPV – IRR – Payback Period for incumbent and newcomers for L-arge
and S-mall European Countires
4.3
A case study in Greece
IST-TONIC methodology has applied in the case of Greece. Based on the official
data for the Greek market, announced by the operators (Figure 6), and assuming
a subscription penetration of 120% until 2012, we can estimate the demand for
mobile services in Greece (total population 11M).
Figure 6 – Number of Mobile Subscriptions in Greece
Based on these results and assuming that the percentage of subscribers holding
more than one mobile station starts from 0% and saturates to 33%, the
subscriber penetration has been estimated as well. For the estimation of both
demand curves a logistic model with four parameters [9][10] was applied. The
curves are illustrated in the diagram below.
Figure 7 – Mobile Subscriptions and Subscribers vs Year in Greece
The total subscriber penetration is split into three different mobile system
generations, namely GSM or 2G, GPRS or 2.5G and UMTS or 3G. When the period
of study starts in 2002 only GSM users are considered to be in the mobile market.
Their number will constantly decrease until 2012 when they will totally disappear.
The first GPRS users have been appeared in 2002. The saturation level for 2.5G is
40% for Greece and will be reached in 2007. Following that period there will be a
decline in the demand down to the level of 25% until 2012. As for the UMTS
users, they will appear at the end of 2003 and their number will increase to reach
a percentage of 75% of the total mobile market in 2012 when the case study
ends. A logistic model [9] was also applied to estimate the percentages for the
different system generations for the years 2002 – 2012. The results are
illustrated in the diagram below.
Figure 8 – Penetration Forecast for different Systems
Combining the results for the total mobile subscriber penetration and the market
share of each of the mobile systems, the penetration forecast for these systems
has been calculated.
Figure 9 – Mobile Subscriber Penetration Forecast
In order to achieve a better approach of the real market the subscribers have
been divided in business and residential users based on the network usage and
the services they use.
The following figure illustrates the investments, revenues and cash balance for
the basic scenario.
Figure 10 - Investments, Revenues, Cash Balance for a 3G operator in Greece
The biggest amount of the investments is required in the first two years in order
to install the UMTS BTSs in urban and suburban areas. Rural areas network
implementation in 2006-2007 will call for substantial investments. The lowest
point of the cash balance curve indicates the maximum need for funding. For the
operator of our study this amount is €1.137 billion. The significant slope of the
cash balance curve at the end of the period indicates good future earning
potential.
The techno-economic prospects for an incumbent operator planning to build and
operate a UMTS network in Greece are found to be encouraging, according to
specific assumptions and scenarios. A more detailed analysis of 3G economics in
Greece can be found in [6].
5. CONCLUSIONS
The technoeconomic analysis of 3G and 4G is mandatory for a 2G-like success
story across Europe. The economic figures for these kinds of services are quite
positive under specific circumstances. Tools and methodologies for market and
business case modeling (presented in 4th Workshop on Telecommunication
Technoeconomics) have been highlighted, in order to aware about this research
area.
ACKNOWLEDMENTS
The authors would like to thank all the partners of IST-TONIC project for their
useful support and discussions, as well as for the organization of the 4 th
Workshop on Telecommunications Technoeconomics, which gave the opportunity
to exchange ideas and to prepare this paper.
6. REFERENCES
[1]
[2]
http://www-nrc.nokia.com/tonic/
G. Gasbarrone, “Beyond third generation wireless communications The
European market Business Case modelling”, 4th Workshop on
Telecommunications Techno-Economics, Rennes – France, 14-15 May 2002
[3] http://www-nrc.nokia.com/tonic/workshop/index.html
[4] http://www.telenor.no/fou/prosjekter/tera/index.htm
[5] D. Katsianis et al, “The financial perspective of the mobile networks in
Europe”, IEEE Personal Commun. Mag., Dec. 2001 Vol 8, No 6, pp 58-64.
[6] D. Katsianis, et al.“3G economics in Greece from now to 2012 ” 4th
Workshop on Telecommunications Techno-Economics, Rennes – France, 1415 May 2002
[7] Th. Monath et al, “Economics of Ethernet based access networks for
broadband IP services”, ISSLS 2002, 14 –17 April, 2002, Seoul
[8] L.A. Ims, “Broadband Access Networks Introduction strategies and technoeconomic evaluation, Telecommunications Technology And Applications
Series, Chapman & Hall 1998, ISBN 0 412 828200
[9] K. Stordahl, L. Rand, "Long term forecasts for broadband demand",
Telektronikk, 95, (2/3), 1999.
[10] Kjell Stordahl, Leif Aarthun Ims, Marianne Moe, “Broadband market - the
driver for network evolution”, Proc Networks 2000, Toronto, Canada,
September 10-16, 2000.