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Techno Economic Methodology for the Evaluation of Telecommunication - - PowerPoint PPT Presentation

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Techno Economic Methodology for the Evaluation of Telecommunication Investment Projects. Sensitivity and Risk Analysis Incorporation Dimitris Katsianis University of Athens Dept of Informatics & Telecommunications email:dkats@di.uoa.gr

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Techno Economic Methodology for the Evaluation of Telecommunication Investment Projects. Sensitivity and Risk Analysis Incorporation Dimitris Katsianis

University of Athens Dept of Informatics & Telecommunications email:dkats@di.uoa.gr International Telecommunication Union- Telecommunication Development Bureau

Market, Economics & Finance Unit Expert Dialogues: 28-29 October 2004 Geneva, Switzerland

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

The challenge

Market

Strategy Technology

Demand Willingness to pay User behaviour Where? When? How? Technology variety Open provisioning Service integration

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Consolidation of Results and Guidelines for deployment scenarios

Information gathering / exchange Common framework Network Studies Guidelines Projects and field trials Other Sources Common conclusions

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Volume Class OA&M Class Cost Evolution Components Database

Operators Suppliers Standardization body Other Market Size Tariffs Policy User inputs Operators Surveys

Decision Index calculation

(NPV, IRR, Payback period)

Decision Index calculation

(NPV, IRR, Payback period)

Financial Model Revenues Cash Flows Profits Investments

Year n Year n

Revenues Cash Flows Profits Investments . . . . . . Revenues Cash Flows Profits Investments

Year 2 Year 2

Revenues Cash Flows Profits Investments

Year 1 Year 1 Radio Model Architectures Services Services Real Options Game Theory

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Steps in Network Evaluation

– Definition of service basket – Network scenarios – First Simulations – Main Financial results – Sensitivity and Risk Analysis – Evaluation Recommendation and Guidelines

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

The TONIC Tool

  • Based on Office 2000 platform

– Excel & Access

  • Automatic sensitivity analysis
  • Compatibility with Risk Analysis

Tool(s)

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

The TONIC tool & its database

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Cost model

  • P(0), the price in the reference year 0
  • nr(0), the relative accumulated volume in year 0,
  • ∆T , the time for the accumulated volume to grow

from 10 % to 90 %,

  • K , the learning curve coefficient.

( ) ( ) ( )

K t T r n e r n P t P ⋅               −               ⋅ ∆ ⋅ − − − + ⋅ − ⋅ =

                                   

2 log 1 9 ln 2 1 1 ln 1 1

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Relative cost evolution as a function of ∆ T

with nr(0)=0.001

DT 1,00 0,80 0,60 0,40 0,20 2 4 6 8 10 2 8 14 20 year

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

“Ecosys” project

WP0 - Project Management and Coordination WP1 Market dynamics WP2 Techno-Economic methodology development WP3 Tool development for T-E modelling WP7 Dissemination and Exploitation WP4 Broadband for all - Economics of new networks and services WP5 Mobile and wireless network economics beyond 3G WP6 Convergence

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

The new Tool “Ecosys”

  • Based on Office 2002 platform

– Multiplayer environments – Real Options implementatio – New demand models – …..

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Main Financial Results

  • Net Present Value, NPV
  • Internal Rate of Return, IRR
  • Payback Period
  • Financial indicators

– Investments – Running Costs – Revenues – Cash Flows – Depreciation – Profits – Taxes – Retained Cash Flows – Cash Balance – Rest Value

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Scalability of the tool

  • Sensitivity Analysis
  • Risk Analysis
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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Sensitivity Analysis

  • What if…?
  • Approach

– select the most critical input parameters – establish boundaries for their variation with a « 95% confidence interval »

  • Results

– impact on NPV

  • at boundary input parameter values: new NPV
  • sensitivity factor: how NPV varies (slope at base value)

– impact on IRR

  • at boundary input parameter values: new IRR
  • sensitivity factor: slope at base value, although variation usually non

linear

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Risk Analysis

  • Input:

– Uncertainty in market parameters

  • Market size
  • Market share
  • Broadband services characteristics

– Uncertainty in Cost parameters

  • Cost units
  • Cost evolution
  • Area characteristics
  • Outputs:

– Probability measures for a reduced set of parameters

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Method

Project setting

for every decision vector

perform simulation store result

risk profile

compare results* make decision

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

0,68 0,74 0,80 0,86 0,92

Component Price Service Penetration

1,09 1,54 2,00 2,46 2,91

Revenue per customer

0,55 0,78 1,00 1,23 1,45 Frequency Chart kE ,000 ,007 ,013 ,020 ,027 67,25 134,5 201,7 269

  • 3000
  • 1000

1000 3000 5000 10 000 Trials 52 Outliers

NPV

Probability Frequency

  • Statistical Variation of the input

parameters

  • Using Monte Carlo Simulation
  • Results: probability distribution,

risk profile of the business case

  • Extended basis for investment

decisions

Risk Analysis

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Risk Analysis - NPV

Frequency Chart

Certainty is 82,10% from 0 to +Infinity ,000 ,010 ,019 ,029 ,038 9,5 19 28,5 38

  • 317.277.492
  • 86.334.971

144.607.551 375.550.072 606.492.594

1.000 Trials 988 Displayed Forecast: NPV

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Requirements for a T-E study

– Services Scenarios

  • Dimensioning

– Commercial Network Architectures .

  • For these services
  • Database
  • Serving areas

– T-E Model Constructions

  • Study period (years?)

– Potential market – Market Shares (e.g operator) – Pricing – – Runs Runs-

  • Results

Results – – Sensitivity and Risk Analysis Sensitivity and Risk Analysis – – Evaluation of the results Evaluation of the results – – Recommendation and Recommendation and Guidelines Guidelines -

  • C

Commercial

  • mmercial viability

viability

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Example case Location base Service LBS

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University of Athens Dept of I nform atics & Telecom m unications

Blend of …cases

Business Profile Tariff Model Terminals Countries Positioning

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Country Types:

Country Type Large Small Description Area size 370,000 132,000 Size of surface area of the country (km2) Area dense 185 7 Size of dense urban area (km2) . Area urban 2,960 4,000 Size of urban area (km2) Area suburban 37,000 10,956 Size of suburban area (km2. Area rural 303,400 109,956 Size of rural area ( km2). Population dense 50,000 10,000 Number of inhabitants in dense urban area per km2 Population urban 4,000 1,216 Number of inhabitants in urban area per km2 Population suburban 1,000 174 Number of inhabitants in suburban area per km2 Population rural 40 35 Number of inhabitants in rural area per square km (during busy hour) Total Population 65,000,000 11,000,000 Total population

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Tariff and revenue forecasts

– Services a) LBS services b) M-Guide Service

– Study Period: 7 years

7 Nr of main Services 0.50 End Price per Query (€) (2009) 1.00 Start Price per Query (€)(2004) 0.2 Nr of Queries per day (2004)

Value

Parameters

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Demand models

2 ,0 0 0 ,0 0 0 4 ,0 0 0 ,0 0 0 6 ,0 0 0 ,0 0 0 8 ,0 0 0 ,0 0 0 10,000,000 12,000,000 2 0 0 3 2004 2005 2006 2 0 0 7 2008 2009

Mobile_Users Local_users_LBS LBS_MGUI DE_users Local_users_GPRS

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Main Financial Indexes

NPV - IRR - Payback Period

2 6 3 36

3 3 .8 39.8 5 .2 5.4 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 0

Large Small

M Euros

5 10 15 20 25 30 35 40 45 IRR (%) Pay-back period (years) NPV IRR PayBackPeriod

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Main results

Net present value Internal rate of return Payback period Small 35.7 M€ 33.8% 5.4 years 36 M€ Maximum Finance need

  • 100
  • 50

50 100 150 2003 2004 2005 2006 2007 2008 2009

M Euros

Revenues SC Investments SC Running Costs SC Cash Balance SC

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University of Athens Dept of I nform atics & Telecom m unications

Cash Balances Large and Small Country

  • 300
  • 200
  • 100

100 200 300 400 500 600 2003 2004 2005 2006 2007 2008 2009

M Euros

Cash Balance SC Cash Flows SC Cash Balance LC Cash Flows LC

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Operational Expenditures (OPEX) SC

10 20 30 40 50 60 2003 2004 2005 2006 2 0 0 7 2008 2009

Other Cost ( Content) Em ployees Marketing Subsidization GPS Term inals

12% 37% 43% 8%

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Revenues LC

100 200 300 400 500 600 700 800 900 2 0 0 3 2004 2005 2006 2007 2 0 0 8 2009

Advertising LBS Roam ers LBS Local MGuide Roamers MGuide Local

3% 6% 66% 14% 11%

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

NPV sensitivity ranges (single parameter change)

  • 40.000
  • 20.000

0.000 20.000 40.000 60.000 80.000 100.000

Tariff Market Share Local users percentage other LBS LBS percentage Mobile Penetration Marketing Content Profit Advertising Revenues LBS Roamers percentage GPS Terminal Subs

Change in NPV in MEURO (compared to base case : 35.7 MEURO)

Low value High value

Sensitivity Analysis

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University of Athens Dept of I nform atics & Telecom m unications

Frequency Chart kE ,000 ,007 ,013 ,020 ,027 67,25 134,5 201,7 269

  • 3000
  • 1000

1000 3000 5000 10 000 Trials 52 Outliers

NPV

Probability Frequency

  • Statistical Variation of the input

parameters

  • Using Monte Carlo Simulation
  • Results: probability distribution,

risk profile of the business case

  • Extended basis for investment

decisions

Risk Analysis

0.4 0.9 1.4 1.8 2.3

Marketingmultiplier

  • 0.5
0.3 1.0 1.8 2.5

MarketShareMult

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University of Athens Dept of I nform atics & Telecom m unications

Risk Analysis - NPV

Frequency Chart

Certainty is 69.22% from 0 to +Infinity .000 .006 .012 .018 .024 60.75 121.5 182.2 243

  • 83,463,974
  • 30,140,537

23,182,901 76,506,339 129,829,777

10,000 Trials 9,845 Displayed Forecast: NPV

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University of Athens Dept of I nform atics & Telecom m unications

Risk Analysis – NPV (2)

Frequency Chart

Certainty is 33.97% from 35,698,326 to +Infinity .000 .006 .012 .018 .024 60.75 121.5 182.2 243

  • 83,463,974
  • 30,140,537

23,182,901 76,506,339 129,829,777

10,000 Trials 9,845 Displayed Forecast: NPV

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28-29 Oct 2004 Geneva Expert Dialogues –ITU-D

University of Athens Dept of I nform atics & Telecom m unications

Conclusions LBS Case

  • Acceptable business opportunities
  • LBS can still be an attractive opportunity for

companies with or without telecom background

  • Payback period of 5 to 6 years, with a yearly ARPU of
  • ver than 27€ for more enthusiastic testbeds
  • Worst-case scenario

– Risk analysis evaluation shows that almost 30% of the project cases could have significant profits and 70% of them remain positive – The uncertainty level is high mainly relating to the LBS penetration and market share

  • One-year delay of this project could be reasonable in
  • rder to answer some critical questions
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Time for Questions & Answers d.katsianis@di.uoa.gr