Practical analysis and valuation of heterogeneous telecom services Case-based analysis

Contents of the lecture Introduction: –Heterogeneous vs homogeneous mobile services –Business environment Service platform model Valuation of service platforms Valuation theory Conceptual description of the valuation model Implementation Case: heterogeneous mobile services Conclusion

Introduction –Heterogeneous vs homogeneous mobile services Technical aspects Business aspect User and service usage aspects –Business environment Value chains Value networks

Your suggestion? 1.What is a service? 2.What is an enabling service? 3.Difference between heterogeneous and homogeneous services

Heterogeneous vs homogeneous services Value networks and constelations Service platform technology Users and usage scenarios

General business characteristics related to telecommunication projects Challenges with valuation of the heterogeneous service –Technological challenges Accelerated technological development generates insecurity Canibalisation of existing services –Market potential for services Acceptance in the market Pricing of heterogeneous services Uncertainty about the price / demand relations Uncertainty about the network effects and the critical mass –Several business actors – various incentives Investment decisions Valuation

Marketing & contract management Call Control – based services Instant messaging Streaming-based services Download-based services Group services Information services Service provisioning Network infrastructure operation Service platform operation Service and Enabling Service operation Service discovery, Service composition, Service brokering, Service mediation, QoS Management, A4C Management Infrastructure operation Design new services and enabling services, Improving service platform, Expand communication network, Set standards, Define Open Interfaces Technology development Firm’s Infrastructure Human Resource Management Procurement Figure. Excerpt of the value network configuration for the SPICE-FIRM. The activities are described in.

Figure 5. Interconnected Industry Structure - Sketch of the business actors and their roles in the Industry mediating the SPICE value network. They collaborate in the mediation process. Mediation is equal to the service, which is the set of collaborating enabling services and service mechanisms, provided by various business actors.

Figure 10. Branch analysis (Porter’s five forces)

Figure 9. Porter's diamond - national competition forces

Heterogeneous service model

How to model a heterogeneous service (technical modelling)? 1.Methodology? 2.Tools? 3.Pros and contras?

Model of heterogeneous service

How to model a heterogeneous service (business modelling)? 1.Purpose 2.Methodology? 3.Tools? 4.Pros and contras?

How to model user behaviour? 1.Why should we model user behaviour (Purpose)? 2.Methodologies ? 3.Tools?

Model user behaviour Modelling various user groups –Youth –Business persons on the move –Seniors –Tourists etc. Modelling various service scenarios –Work process support –Tourism –Health services

Valuation of heterogeneous services 1.How to valuate practically? 2.Discussion about various methodologies

Needed input for the valuation 1.Which input? 2.How to get it?

Cash Flow

Capital cost Discounting rate

The capital asset pricing model (CAPM)

E(r j )= r f +  E(r m ) – r f   j, E(r j ) = expected return on security, r f = risk-free rate, E(r m ) = Expected return on market portfolio,  j = systematic risk, measures the responsiveness of a security to movements in the market portfolio.

Classical approach – Capital Asset Pricing Model (CAPM [11]) A risk neutral approach – moving a risk from a denominator to a numerator Risk neutral approach – used in this work: The risk neutral approach can be modeled by using two techniques:  The replication portfolio calculations or  The risk-neutral probability techniques [14].

Valuation methods NPV Decision trees Real option analysis

Table 1. Key criteria for decision-making tools [5]. Cash flow based Risk adjusted Multi-periodCaptures flexibility Real option value  NPV / DCF  Decision trees  Economic profit  Earnings growth  Both real options and decision trees capture the mechanics of flexibility. However, only options adjust for risk.

Figure 2. Six levers of financial and real options [1].

Figure 3. Classifying real options (grow, defer or quit) [5]

How to model business scenarios? 1.What is a business scenario? 2.How to model the business scenario?

Table 5. Investment proposals for various business (growth) scenarios (based on calculations from appendix xx) Investment proposals for various business (growth) scenarios OPTIMISTIC SCENARIO - Service with extended functionality R&D efforts (Total costs) ,00 NOK Annual increase in revenue (after the year 3)15 % REALISTIC SCENARIO - Service with full functionality R&D efforts (Total costs) ,00 NOK Annual increase in revenue (after the year 3)5 % PESSIMISTIC SCENARIO - Service with basic functionality R&D efforts (Total costs) ,00 NOK Annual increase in revenue (after the year 3)1 %

1234 Step Compute Base Case Present Value (PV) without Flexibility, Using DCF Valuation Model Model the Uncertainty, Using Event Trees Identify and Incorporate Managerial Flexibilities, By Creating a Decision Tree Calculate Real-Option Present Value (ROA) Objectives  Compute base case present value without flexibility  Identify major uncertainties in each stage  Understand how those uncertainties affect the PV  Analyse the event tree to identify and incorporate managerial flexibility to respond to new information  Value the total project using a simple algebraic methodology Comments  Still no flexibility; this value should equal the value from Step 1  Exploiting estimate uncertainty  Incorporating flexibility transforms event trees, which transforms them into decision trees.  The flexibility continuously alters the risk characteristics of the project, and hence the cost of capital  ROA includes the base case present value without flexibility plus the option (flexibility) value  Under high uncertainty and managerial flexibility, option value will be substantial Output  Project’s PV without flexibility  Detailed event tree capturing the possible present values of the project  A detailed decision tree combining possible events and management responsibilities  ROA of the project and optimal action plan for the available real options Table 11. Four step process for Real Option analysis [14].

1234 Step Compute Base Case Present Value (PV) without Flexibility, Using DCF Valuation Model Model the Uncertainty, Using Event Trees Identify and Incorporate Managerial Flexibilities, By Creating a Decision Tree Calculate Real-Option Present Value (ROA) Tasks / Activities  Quantify three scenarios: o Optimistic o Realistic o Pessimistic  Calculate FCF  Estimate WACC  Calculate PV and set its development in time  Find PV (Investment)  Find NPV without flexibility  Understanding how PV develops in time for all three scenarios  Still without flexibility: Value through stochastic process  Identify uncertainties  Monte Carlo simulation for correlated uncertainty factors for each scenario  Exploiting estimate uncertainties  Produce event tree for each scenario  Combine event trees in main event tree  Identify available real options  Calculate option values for each node (start in the last time period)  For each node compare the real option value with the actual investment  Produce the decision tree  Valuate the company by use of risk neutral probabilities.  New base case without flexibility (without optimisation).  Identify optimal action plan for available real options.  The values of real options finds by subtracting NPV (base case) from ROA. Table 12. Tasks/Activities in four-step process for ROA analysis.

Table 15. Inputs and outputs from Monte Carlo simulations. Risk-free rent 0,0608 PV – realistic scenario ,77 Annual average standard deviation0,12 Realistic scenario Increase per time interval, u1,12750 Decrease per time interval, d0, Risk neutral probability of increase0, Risk neutral probability of decrease0, Figure 4. Sensitivity analysis of simulation variables for Monte Carlo simulation of realistic business scenario. Figure 5. Frequency chart for sales in the year 7 - based on 1000 simulations.

Figure 5. Quadranomial approach - value of the asset affected by two sources of uncertainty

Figure 6. Values of various options for R&D project.

Implementation Case: –PATS lab / SPICE project – prototype services

Conclusion –Heterogeneous vs homogeneous mobile services –Business environment Model of heterogeneous services Practical valuation of service platforms Practical valuation methods Conceptual description of the valuation model Case: Heterogeneous mobile services