Expert Dialogues
Mohsen HAMOUDIA
mohsen.hamoudia@francetelecom.com
Adjusting Forecasting Methods To the Needs
Of The Telecommunication Sector
Examining Forecasting Methodologies To Assist And Support Operators
In The Transition From
A Regulated Environment To Deregulated Markets
ITU - International Telecommunication Union
Market, Economics and Finance Unit
in cooperation with
IIF - International Institute of Forecasters
Geneva, Switzerland
25-26 October 2004
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Table of Contents
n Introduction
n A Changing Environment : From a Monopoly Situation to Liberalized
Markets
n Limitations of “Traditional” Forecasting Methods and Models
n Case Study from an Important Operator experience in International
Traffic : outlining the forecasting methods undertaken and how they
held up to the challenges of Telecom Deregulation in 1998
n Conclusion
2
A Changing Environment
From a Monopoly Situation to
Liberalized Markets
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (1/10)
In Europe, 1998 was a very important event because the European
Telecom Industry has been entirely deregulated. The main effects
and consequences were :
l Increasing number of operators, carriers and Internet
providers in the deregulated markets
l Increasing (and aggressive) competition and new
Alliances
l Explosion of new products and services
l Evolution of the Customer Choices and usages : From
Telecommunication to Communication
l Falling Prices and Falling Revenue
l Pressure on Settlement Rates on Bilateral Routes
4
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (2/10)
n The Telecom Deregulation level
From 1 – Regulated markets
to 5 – Fully Liberalized markets
5
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (3/10)
n Increasing and aggressive competition
Int'l Traffic by Carrier Type
Outgoing Int'l in Minutes (Billions)
140
120
100
New Carriers in Competitive
Markets
Existing Carriers in Competitive
Markets
Monopolies
80
60
40
20
0
1990
1992
1994
1996
6
1998
1999
2000
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (4/10)
n The International Carrier Boom
Number of Carriers
2805
3000
2500
2000
1760
1500
1000
586
500
367
0
1995
1997
1999
7
2000
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (5/10)
n A general overview of Worldwide Telecom Industry
Fixed Telephony
Data Services
Mobile
Internet
1460 bEuros
1162 bEuros
780 bEuros
67
145
83
161
123
62
573
529
203
448
1998
427
+10% / year
581
+ 5% / year
2002
2006
2005
1,2 billion of fixed lines
1,5 billion of mobiles
900 millions of Internet Access
Source : Idate
8
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (6/10)
n Explosion of new products and services
n
n
n
P2P Communications : + 40 %
Fixed Voice Calls : only + 18 %
Fixed Voice Share in the Global Call volumes falled
Monthly Number of communication by FT’s Customer
Structure of communications
Mail 1,8
mobile
voice
SMS
5,2
fixed
voice
Text
1,0
mobile
voice
fixed
voice
19,6
32,6
97%
49%
4%
Internet
SMS 11%
mobile
voice
42%
voice
Voice
+ 18%
fixed
voice
20,2
1997
3%
fixed
voice
51%
43%
2002
1997
Source : FT/DPS 2003
9
2002
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (7/10)
n Evolution of the Customer usages and Choices
France : Monthly Number of communication by Customer
200
Customer wants Communication
rather Telecommunication
160
140
Internet
120
SMS and mobile data
100
60
Communication
synchrone
80
Mobile voice
40
20
Fixed voice
0
1990
Fixed voice
1992
Mobile voice
1994
1996
SMS and mobile data
1998
2000
Minitel
2002
2004
Internet mail & IM
Communication
asynchrone
180
2006
2008
2010
Internet WEB &t P-to-P
Source : FT/DPS 2003
10
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (8/10)
n Evolution of the Customer usages in Enterprises
France : Number of communications by employee and by day
8
0,08
7
1,92
6
5
SMS
1,49
eMails
Mobile
4
3
Fixed Traffic
3,84
2
1
0
1998
1999
2000
2001
2002
2003
2004
2005
2006
Source : FT/DPS 2003
11
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (9/10)
n Falling Prices and Falling Revenue
Lowest Available Retail Price for Calls from
Germany
Australia
Poland
Turkey
2000
Austria
1997
UK
France
USA
0
0,5
1
DM/minute
12
1,5
2
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment (10/10)
n Price Evolution : France Telecom’s Prices for Fixed Voice Traffic
CAGR
(1997 – 2002)
100
90
80
Line rental (€/month)
70
Local call (€/100)
60
+ 5.0%
- 2.8%
National call (€/100)
-13.3%
50
International call (€/100)
40
-12.4%
Fixed to mobile (€/100)
30
Mobile to mobile (€/100)
20
- 9.5%
-16.9%
10
0
1994
1996
1998
2000
2002
13
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Changing Telecom Environment : Conclusion
The Modeling and Forecasting Techniques in the Telecom
Industry are significantly and highly
impacted by this
changing environment :
l It is necessary to Understand the real issues facing
Operators in a newly Liberalized & deregulated
environment
l These changes must lead the historical players
(incumbents) to “re-engineer”, adapt and reshape
their Forecasting processes and techniques to face
and challenge the new environment
l These market changes must drive “new” and more
suitable forecasting Techniques
14
Limitations of “Traditional” Forecasting
Methods and Models in the Context of
Competitive Markets
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Using inadequate Forecasting Model : an example
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Univariate B&J
Univariate B&J
Monopoly
situation
Transition
• Jan 1998 : Deregulation of
Telecom Market
• Traffic Forecast for 1998
accurate.
• Forecasting Model =
Univariate B&J for 1998
• Until early 1998 : Telecom
environment was stable.
• In 1998 : Some New players
entered the market
• 1999 : Deregulation of
Telecom Market has produced
its early effects
• Traffic Forecast for 1999 not
accurate.
• Forecasting Model =
Univariate B&J for 1999
• Starting 1999 : Telecom
environment was instable
because full competition
• In 1999 : Increase of the
number of New players in the
market
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Univariate B&J
Competitive
Market
• 2000 : Deregulation of Telecom
Market has produced its full effects
• Traffic Forecast for 2000 not
accurate et MAPE has shown an
increasing error.
• Forecasting Model = Univariate B&J
for 2000
• Very important change in the actual
traffic
• In 2000 : Telecom market was widely
opened and fully competitive
• In 2000 : Increase of the number of
New players in the market
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Adapting the Forecasting Model to the new context
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200
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Univariate B&J
Monopoly
situation
• Jan 1998 : Deregulation of
Telecom Market
• Traffic Forecast for 1998
accurate.
• Forecasting Model =
Univariate B&J for 1998
200
Univariate B&J with
Intervention Function
Hubbing & Refiling
Transition
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Forecast_D
Multivariate B&J
Transfer Function
Prices, Competition, LCR
Competitive
Market
• 1999 : Deregulation of Telecom
Market has produced its early effects
• 2000 : Deregulation of Telecom
Market has produced its full effects
• Traffic Forecast for 1999 accurate.
• Traffic Forecast for 2000
accurate et MAPE has shown a
stable error.
• Forecasting Model = Univariate B&J
with Intervention Function for 1999
• Until early 1998 : Telecom
environment was stable.
• Starting 1999 : Telecom
environment was instable because
full competition
• In 1998 : Some New players
entered the market
• In 1999 : Increase of the number of
New players in the market
17
• Forecasting Model = Multivariate
B&J for 2000
• The new model feets well the
changing trend of traffic
• In 2000 : Telecom market was
fully competitive
• In 2000 : Increase of the number
of New players in the market
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Selection of the Explanatory Variables
Main drivers in a Monopoly situation
The main drivers in a Monopoly Telecom
market are the Economy and the
Customer features :
Economy
Economy :
Demand
Forecast
Consumption, Price index, Investments ,
Foreign Trade …
Traffic
Revenues
Capacity
Users
Customers
…….
Customer :
demand, segmentation, price
elasticity by customer segment, ….
Customers
The main drivers in a Competitive Telecom
market are :
Economy
Customers needs and their perceived value,
detailed segmentation, …
Regulation interconnexion rules, offerings
Pricing Strategy adaptative pricing, yield
Main drvers in a Competitive Environment
Economy
Competitors
Substitute Products
Regulation
Innovation/Technology
management
Competition, market shares, players, …
Product substitution
Technology & Innovation
GNP, GDP, Income,
Customers
Demand
Forecast
Traffic
Revenues
Capacity
Users
Customers
…….
QoS (Quality of Services)
Company Developments
Company Goals
18
Pricing / Yield Management
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Main Forecasting Methods used Before the 1998 Liberalization
n An Example of a Previous Econometric Model used for the Global Outgoing IDD Traffic
Explanatory Variable
LOG(Price)
LOG(Time)*LOG(Price)
LOG(Foreign Trade)
AR(1)
R2
Adj. R2
Durbin-Watson
Coefficient
-0.471823
0.048264
0.477754
0.373937
0.984826
0.984320
2.369308
Stand. Error
0.013197
0.003987
0.001810
0.090575
t-Statistic
-35.75160
12.10482
263.9157
4.128461
Prob.
0.0000
0.0000
0.0000
0.0001
n Before 1998, this type of Econometric model has generally provided accurate forecasts :
l For Global Traffic
l For Main Customer Segments : Business and Residential
l For Main Geographical Segmentation : Europe, Asia, NA, …
n For regulated markets, this type of Econometric model could provide accurate forecasts :
l By country (Algeria, Viet-Nam, Cambodia, China, Saudi Arabia, Tunisia, …)
l By area : Middle East, North Africa, South America, …
19
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Main Forecasting Methods used Before the 1998 Deregulation
n An Example of Previous Forecasting Models by Geographical Segments for Global Outgoing IDD Traffic
Geographical Segments
Models/Methods used
Explanatory variables
NAFTA
USA-CANADA-MEXICO
Econometric
Multivariate ARIMA
Market model
Econometric
Univariate ARIMA
Market model
Econometric/Dynamic Reg.
Uni.ARIMA/H&W
Market model
Imports/Exports index
Call prices
communication consumption
Competition, Hubbing Refiling
Imports/Exports index
GNP/GDP - Call prices
communication consumption
Competition Hubbing Refiling
Imports/Exports index
GNP/GDP - Call prices
communication consumption
Imports/Exports index
GNP/GDP - Call prices
communication consumption
Econometric/Dynamic reg.
Uni. ARIMA/H&W
Market model
X11 Regression / H&W
Market model
Imports/Exports index
GNP/GDP - Call prices
Global investments in ME
Tourism index
GNP/GDP - Call prices
Western Europe
Japan/HongKong
Taiwan/S.Korea
South America
Middle East/Africa
Caribbean (ex. Martinique &
Guadeloupe)
Econometric
Uni/Multivar. ARIMA
Market model
20
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
The Forecasts Accuracy
n An Example of a Previous Econometric Model for the Global Outgoing IDD Traffic
21
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Enhancing the Modeling Process (1/4)
n The Econometric Modeling
• To enhance the quality of the forecast (accuracy)
• To have a better comprehension and understanding of the Market Structure :
Ø for example, how each explanatory variable drive the demand ?
• To learn the relationship between the dependent variable (to be forecasted) and
its environment : evaluation of the Economy, Price, Competition, … impacts on
the dependent variable (contribution)
• To assess and test and simulate some alternative scenarios and hypothesis :
Ø For example, what is the impact on mobile voice traffic of 15%
reduction of
price ?
• To catch the dynamic of the market environment (lagged explanatory variables)
Ø For example, when (after how many months or weeks) a 10%
reduction of
price will increase the demand ? This could allow the
operator to adapt the
periodicity of some actions through the time
(special offers, …)
22
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Enhancing the Modeling Process (2/4)
n Time series Modeling
• We can integrate in some Time Series Models the effects of :
Ø specific actions/events (dummy variables, intervention variable)
Ø Multivariate Time Series Analysis : including explanatory variables
(Transfer Function Modeling, i.e Box & Jenkins with Transfert function or
Kalman Filtering)
n Growth Curves/S-Curves
• These models are adequate for new product studies
Ø The Logistic (Local, Extended, …)
Ø Gompertz
Ø Exponential
23
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Enhancing the Modeling Process (3/4)
n A specific Model for each Customer Segment : by customer, by market, by
product, ...
For example :
• By Age
• By Income
• By Occupation
• By overall Spend
• By business sector
The benefit is to learn for example how
each Type of Customer reacts to the
Price, Economic, Competition …
variables
- For example, the Young Customer
has a high Price elasticity . The « High
Revenues » Customer has
a high
Economy
elasticity
than
Price
elasticity.
- This information could help the
operator for its Marketing strategy
(Packages for Young Customers,
Prepaid cards for…..)
24
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Enhancing the Modeling Process (4/4)
n The need of Information and Data in the Competitive markets
There is a very important need of onformation and data concerning « new » drivers to be
considered in a competitive market :
• Competition
• Innovation
• Pricing
• Regulation
• Customer attitudes and choices
• QoS
• Substitution Products
• Marketing
• Strategy
• Sales
How to collect them :
• Market intellingence
• Benchmark studies
• Consultancy sources : Ovum, IDC, Giga,
Yankee Group, Idate, Frost& Sullivan, ……
• Customer surveys / Trade Off studies
• Int’l Offices os Statistics : ITU, WB, IMF, EU,
• National Offices os Statistics : INSEE,
Census, …
• Other sources : Wefa, ….
ØIt is absolutely important to improve the « quality » of the Data to be
integrated in the forecasting models
ØIt is « vital » to track « new » information concerning the competitive market
25
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Limitations of traditional forecasting methods : Conclusion
The Forecasting Process (Modeling, Estimating, Accuracy) must be adapted
continuously to the changing environment :
l
The market changes must drive “new” and more adequate forecasting Techniques
(for example the Simultaneous Equation Models)
l
Telecom Forecasting Models must take into account :
l
l
More adequate and accurate explanatory variables
l
The dynamic of demand and supply : lagged variables
l
The Necessity of more detailed Demand Segmentation
l
The Players behaviour and Strategies (Alliances, …)
Using Econometric Models solely could lead to inconsistent and not accurate
Forecasts :
l
It is necessary to integrate in the Forecasting Process other contributions
outside the Econometric Model (see Case Study in 3 rd Part) : Learning from
Customer Surveys, Market Studies, Trade Off studies, … and experience
l
Integrating a flexible pricing strategy : stable Price elasticity ?
l
Learning from the experience of deregulated and competitive telecom markets :
UK, USA, …
l
Need for frequent re-forecasting and adaptative forecasts
l
Integrating new traffic routing strategies (LCR, hubbing, refiling,…)
26
A Case Study from an important Operator
Experience in the International Traffic
Outlining the Forecasting Methods undertaken and how
they held up to the Challenges of Liberalization in 1998
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Adoption of New Approaches and Forecasting Models
n Building a new approach for Incoming International Traffic (IDD Traffic)
Module
Forecast
Econometric Model
Routing :
Fragmentation
Routing :
- Concentration
- Repartition
Expected Results
Total Incoming Traffic to France
Total Traffic from origin country to France
by operator / carrier
Total Incoming Traffic to France
- by Route & by operator
- b y d e s t i n a t i o n o p e r a t o r/ c a r r i e r
28
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (1/9)
n Module 1 : Global Traffic between Origin country and France :
l “Traditionnal” Econometric Modelling & Estimation
l But with More suitable explanatory variables
Forecast
Econometric Model
Tran
sit
»
g
n
i
ubb
«H
Country A
Total Incoming Traffic to France
Estimation of GlobalTraffic
from Country A to France
France
n Transit & “ hubbed” traffics to country A are not included in the Global traffic
l They should be added outside the model
29
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (2/9)
n Information & Data Set :
l Annual Data from 1990 to 1998
l Traffic between 54 countries , i.e 9 years x 54 countries x 53 country-pairs
n Model Specification & Estimation
30
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (3/9)
n Actual & Predicted data
31
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (4/9)
n Module 2 : Fragmentation of the Incoming Traffic from Origin Country to France :
Routing :
Fragmentation
Total Traffic from origin country to France
by operator / carrier
OP1
CAR1 …..
Tran
sit
»
ng
i
b
ub
«H
Country A
Traffic to France by Route and by
Operator/Carrier
France
CAR2
OP2
n Transit & “ hubbed” traffics to country A by Route and by
Carrier/Operator must be added to the global Traffic
n Assumptions and hypothesis are defined for actual and future situation of players & market :
l Alliances and Partnership Policy
l Liberalization evolution and Telecom players behaviour in the origin country
32
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (5/9)
Detail
Resellers
Local Access
C's C
ORI2
ORI1
Resellers
Methodology
Local Access
n Fragmentation of Traffic in the Origin Country
Main categories of operators/carriers
considered (couldiffers from a country
to another country)
Int’l Traffic origination to
France
Traffic Concentration
chain in the Origin country
(Retail → wholesale)
Improbable Case
ORI1
Could happend but rarely
Traffic to be sent from the
origin country to France
ORI2
C's C
Traffic from origin Country A to France
Traffic to France (excluding hubbing)
Int’l Traffic from other countries
to A (‘hubbed’)
Total Int’l Traffic to France
From concentration
module in third country
To concentration &
Distribution
modules
33
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (6/9)
n Fragmentation of Traffic in the Origin Country
34
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (7/9)
n Module 3 : Traffic Concentration in the Origin Country & distribution in France
Routing :
- Concentration
- Distribution
OP1
Tra
nsi
t
ng
bbi
u
«H
Total Incoming Traffic to France
- by Route & by operator
- by destination operator/carrier
OP2
Route 1
»
Country A
OP1
Route 2
OP2
France
Route n
OP4
OP3
OP4
35
OP3
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (8/9)
n Concentration of Traffic to France by Route and by Carrier/Operator
Countries and
Operators/Carriers
Geostrategic Criterion
Possible Routes
Economic Criterion
Percentage of Traffic
Managed by LCR
Tariffs of Half-circuts
Int’l Leased Lines
Cost of End-to-End
Route
Traffic on the
Considered Route
interconnection Cost
In France
Cost of « Hubbing »
Route
Commutation Cost
36
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Forecasting the Int’l Incoming Traffic (9/9)
n Distribution of Int’l Incoming Traffic to France by Carrier/Operator
Operator
Traffic
Traffic on Operator bilateral route +
Traffic on « Third » party bilateral route +
End to End Traffic (if Affiliated)
Competitors
Traffic
Traffic on the Carrier’s bilateral route +
Traffic on « Third » party bilateral route +
End to End Traffic (if partnership)
37
Conclusion
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
Conclusion :
The Forecasting process (modeling, estimating, accuracy checking) must be adapted
continuously to the changing environment :
l
l
l
The market changes must drive “new” and more adequate forecasting Techniques
l
“Refresh” the forecasting model & approaches
l
Build alternative model & approaches when necessary
l
Use alternative scenarios to assess the demand & supply
Telecom Forecasting Models must take into account :
l
More adequate explanatory variables
l
The dynamic of demand and supply : lagged variables
l
The Necessity of Demand Segmentation
l
The Players behaviour and Strategies (Alliances, …)
l
The flexibility of pricing strategy
l
New traffic routing strategies (LCR, hubbing, refiling,…)
It is necessary and very useful :
l
to integrate in the Forecasting Process other contributions outside the Econometric Model :
Learning from Customer Surveys, Market Studies, Trade Off studies.
l
To learning from the experience of deregulated and competitive telecom markets : UK, USA,
Australia, Canada, …
l
To set-up and use a re-forecasting process
39
Adjusting Forecasting Methods To the Needs Of The Telecommunication Sector
THANK YOU FOR YOUR ATTENTION
mohsen.hamoudia@francetelecom.com
Tel :
Mobile :
Fax :
+ 33 1 56 66 34 50
+ 33 6 82 93 15 72
+ 33 1 56 66 53 83
40