© Mark Gaynor 11/05/08 - IPAM1 Real Option Framework to Value Network Architecture and Network...

© Mark Gaynor 11/05/08 - IPAM 1

Real Option Framework to Value Network Architecture

and Network Neutrality

Mark GaynorBoston University

Saint Louis University (summer 2009)[email protected]

Real Option Framework to Value Network Architecture

and Network Neutrality

Mark GaynorBoston University

Saint Louis University (summer 2009)[email protected]

Workshop III: Beyond Internet MRA: Networks of Networks

Institute for Pure and Applied Mathematics (IPAM)

Workshop III: Beyond Internet MRA: Networks of Networks

Institute for Pure and Applied Mathematics (IPAM)

mailto:[email protected]

mailto:[email protected]


MotivationMotivation What is the value of:

end-2-end architecture Efficient centralized Vs flexible distributed architectures Network Neutrality

It depends on market uncertainty! It is important to know what users want

If you know and others don’t, then you can win big if market uncertainty is high

What is the value of: end-2-end architecture Efficient centralized Vs flexible distributed architectures Network Neutrality

It depends on market uncertainty! It is important to know what users want

If you know and others don’t, then you can win big if market uncertainty is high


Talk OutlineTalk Outline Real Options Approach Market Uncertainty Network Architecture A simple real options model What is network neutrality Model applied to network neutrality

Link the excepted ARPU to market uncertainty

Real Options Approach Market Uncertainty Network Architecture A simple real options model What is network neutrality Model applied to network neutrality

Link the excepted ARPU to market uncertainty


Traditional networks metricsTraditional networks metrics

What are traditional methodologies good for If I know what users want

What if we don’t understand what users want? What services, with what features? How much will they pay for them? Does uncertainty imply more value to network neutrality

Real options value uncertainty and choice

What are traditional methodologies good for If I know what users want

What if we don’t understand what users want? What services, with what features? How much will they pay for them? Does uncertainty imply more value to network neutrality

Real options value uncertainty and choice


Why “real options”Why “real options”

Options theory models uncertainty, flexibility and choice Options illustrate how to limit risk, without capping gain –

a good design principle Real options extends the theory of options to non-financial

assets Building IT infrastructure, modularity in computer systems,

modularity and staged development of IT standards Real options illustrate when flexibility is worth more than

efficiency

Options theory models uncertainty, flexibility and choice Options illustrate how to limit risk, without capping gain –

a good design principle Real options extends the theory of options to non-financial

assets Building IT infrastructure, modularity in computer systems,

modularity and staged development of IT standards Real options illustrate when flexibility is worth more than

efficiency


Options and Real OptionsOptions and Real Options

Classic call option Pay something today, to buy a

stock in the future, at today’s price

This limits risk, without capping gain, unlike owning the stock

Real Options Pharmaceutical development,

power plants,…..

Limit loss without capping gain

Classic call option Pay something today, to buy a

stock in the future, at today’s price

This limits risk, without capping gain, unlike owning the stock

Real Options Pharmaceutical development,

power plants,…..

Limit loss without capping gain Stock Price

Option Pay

-out

Strike price

Excess risk ofstock

ownership

0

Stock Profit

Option pay-out

Profit/Loss fromStock sale


Management Structure and Experimentation

Management Structure and Experimentation

What is Experimentation Features in devices and services

Distributed management structure is easy to experiment with Don’t need permission Don’t need to change network infrastructure A bad experiment only affects a few users

Centralized management makes experimentation hard Need to change network infrastructure Need to ask permission Many users affected with bad experiment

What is Experimentation Features in devices and services

Distributed management structure is easy to experiment with Don’t need permission Don’t need to change network infrastructure A bad experiment only affects a few users

Centralized management makes experimentation hard Need to change network infrastructure Need to ask permission Many users affected with bad experiment


Distributed Vs Centralized Wireless Music Service

Distributed Vs Centralized Wireless Music Service

Alice’s Home PC

Alice

Bob’s Home PC

InternetAlice’s favorite

song

Bob’s favorite

song

Distributed(end-2-end)

Bob

Centralized managementPeople, Equipment and Data centralized managedEfficient use of resourcesKnow users and usageConsistency of environmentHard to changeIn-flexible for new applications

Distributed managementP,E,D locally managedEasy to experiment withUser control Small scale non-intrusive experimentation possiblePoor use of resources

Hard to know users and what they are doing

Centralized AliceBob

Centralized Music Server PC

InternetAlice’s favorite

song

Bob’s favorite

song

Alice’s Home PC

Bob’s Home PC


Market UncertaintyMarket Uncertainty

Market uncertainty is the inability to predict what uses want

How to measure it: Tushman and MacCormack Tushman: how well have historical predictions about

market been MacCormack: Emergence of dominate design Gaynor and Bradner: measure changes in standards,

stable feature sets The value of the best of many experiments is

related to the market uncertainty

Market uncertainty is the inability to predict what uses want

How to measure it: Tushman and MacCormack Tushman: how well have historical predictions about

market been MacCormack: Emergence of dominate design Gaynor and Bradner: measure changes in standards,

stable feature sets The value of the best of many experiments is

related to the market uncertainty


Best of Many Attempts to Meet the Market(When is experimentation worthwhile?

When market uncertainty is high)

Best of Many Attempts to Meet the Market(When is experimentation worthwhile?

When market uncertainty is high)

Each attempt is an implementation with a particular feature set Extreme order statistics – Value of best of many attempts High market uncertainty => someone wins big (maybe you), low market

uncertainty => no big winners because its easy to satisfy users

Each attempt is an implementation with a particular feature set Extreme order statistics – Value of best of many attempts High market uncertainty => someone wins big (maybe you), low market

uncertainty => no big winners because its easy to satisfy users

Normal Density Function

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

-3 -2 -1 0 1 2 3

Experiment Value

Probability

S.D=1

s.d.

34.13% 13.59

%13.59

%

34.13%

2%2%

E(X) = V = MeanU10

U100


00.20.40.60.8

11.21.41.61.8

-3 -2 -1 0 1 2 3

Experiment Value

Probability

S.D=1

S.D=.25

Ux = V + s.d * Q(x) Q(x) is number of s.d.’s from the mean

of the best experiment

High market uncertainty implies

value in giving users more choices


DefinitionsDefinitions MU = Market uncertainty X is a random variable denoting the value of one choice the user has for a

service E(X) = V, s.d(X) = MU

CP(A) cost to provide the service with architecture A F – is for flexible and expensive architecture C – is for controlled and efficient architecture

VS(A) net value of service provided with A Assumptions – flexible networks allow users more choices, but cost more

CP(F) > CP(C) – we call this the Business and Technical Advantages of controlled (centralized) architecture

BTA = CP(F) - CP(C)

MU = Market uncertainty X is a random variable denoting the value of one choice the user has for a

service E(X) = V, s.d(X) = MU

CP(A) cost to provide the service with architecture A F – is for flexible and expensive architecture C – is for controlled and efficient architecture

VS(A) net value of service provided with A Assumptions – flexible networks allow users more choices, but cost more

CP(F) > CP(C) – we call this the Business and Technical Advantages of controlled (centralized) architecture

BTA = CP(F) - CP(C)


ModelModel

Value of controlled architecture VS(C) = V - CP(C) We assume only one choice for users

Value of flexible architecture at the ed VS(F) = V - CP(F) + Q(x)*MU We assume x choices for users

Flexible networks are more valuable when VS(F) - VS(C) > 0 Which implies: Q(y)*MU > BTA This means the value of experimentation is greater then the

advantages of controlled/centralized architecture

Value of controlled architecture VS(C) = V - CP(C) We assume only one choice for users

Value of flexible architecture at the ed VS(F) = V - CP(F) + Q(x)*MU We assume x choices for users

Flexible networks are more valuable when VS(F) - VS(C) > 0 Which implies: Q(y)*MU > BTA This means the value of experimentation is greater then the

advantages of controlled/centralized architecture

Link to market uncertainty


ResultsResults

1 5 9 13 171

140

5

10

15

20

25

30

35

Value

MU

# trials

Effects of MU on the Value of Experimentation

0-5 5-10

10-15 15-20

20-25 25-30

30-35

1 4 710

13 1619

2225

1-E

6-E

11-E

16-E0

10

20

30

40

50

60

70

Market Uncertainty

Cost Differential

Market Uncertainty Vs Cost Differential

60-70

50-60

40-50

30-40

20-30

10-20

0-10

Q(x)*MU Q(y)*MU = Cost Differential


Learning and evolution Learning and evolution


00.20.4

0.60.8

11.2

1.41.61.8

-3 -2 -1 0 1 2 3

Experiment Value

Probability

S.D=1

S.D=.25

1 3 5 7 9 1 Generation

4 Generations

7 Generations

10 Generations

0

1

2

3

4

5

6

7

MU

Cost-Diff

MU Vs Cost-DiffFor 10 Experiements, GenFactor = 1/n

6-7

5-6

4-5

3-4

2-3

1-2

0-1

1 3 5 7 9 1 Generation

4 Generations

7 Generations

10 Generations

0

1

2

3

4

5

6

7

MU

Cost-Diff

MU Vs Cost-Diff10 Experiments, GenFactor = 1/2

6-7

5-6

4-5

3-4

2-3

1-2

0-1


Email Case StudyEmail Case Study

Different ways to manage email Centralized web-based (hotmail) compared to

distributed ISP (PoP) Shift to centralized in 1996

Low MU because of dominate design, stable standards

Market uncertainty is likely cause of this shift Technology or regulation can’t explain this

shift

Different ways to manage email Centralized web-based (hotmail) compared to

distributed ISP (PoP) Shift to centralized in 1996

Low MU because of dominate design, stable standards

Market uncertainty is likely cause of this shift Technology or regulation can’t explain this

shift


Voice Case StudyVoice Case Study

Distributed PBX compared to centralized Centrex Shift to centralized in 1996

Low MU because good market predictions, stable feature set Market uncertainty is likely cause of this shift Technology or regulation can’t explain this shift

Distributed PBX compared to centralized Centrex Shift to centralized in 1996

Low MU because good market predictions, stable feature set Market uncertainty is likely cause of this shift Technology or regulation can’t explain this shift


Network NeutralityNetwork Neutrality

Users can use their bandwidth for anything they want, in any way they want (Tim Berners Lee)

The network does not bias traffic to and from users based on its content, source, or destination

Does not bias traffic to the disadvantage of the end user

A network service provider offering VoIP can not give lower QoS to a competing VoIP service provider in a neutral network

Users can use their bandwidth for anything they want, in any way they want (Tim Berners Lee)

The network does not bias traffic to and from users based on its content, source, or destination

Does not bias traffic to the disadvantage of the end user

A network service provider offering VoIP can not give lower QoS to a competing VoIP service provider in a neutral network


Network Neutrality or NotNetwork Neutrality or Not

Some say neutrality will not promote investment in network infrastructure

Some say non-neutrality will not promote innovation in devices, applications, and services

How does uncertainty fit into this

Some say neutrality will not promote investment in network infrastructure

Some say non-neutrality will not promote innovation in devices, applications, and services

How does uncertainty fit into this


Openness in 700MHz SpectrumOpenness in 700MHz Spectrum Google wanted in the 700MHz C block:

“Open applications: consumers should be able to download and utilize any software applications, content, or services they desire;

Open devices: consumers should be able to utilize a handheld communications device with whatever wireless network they prefer;

Open services: third parties (resellers) should be able to acquire wireless services from a 700 MHz licensee on a wholesale basis, based on reasonably nondiscriminatory commercial terms; and

Open networks: third parties (like internet service providers) should be able to interconnect at a technically feasible point in a 700 MHz licensee's wireless network. “ - http://googlepublicpolicy.blogspot.com/2007/07/promise-of-open-platforms-in-upcoming.html

FCC wants: Any device and application

Carriers want their devices, applications, services, and no wholesale network pricing!

Google wanted in the 700MHz C block: “Open applications: consumers should be able to download and utilize any software

applications, content, or services they desire; Open devices: consumers should be able to utilize a handheld communications

device with whatever wireless network they prefer; Open services: third parties (resellers) should be able to acquire wireless services

from a 700 MHz licensee on a wholesale basis, based on reasonably nondiscriminatory commercial terms; and

Open networks: third parties (like internet service providers) should be able to interconnect at a technically feasible point in a 700 MHz licensee's wireless network. “ - http://googlepublicpolicy.blogspot.com/2007/07/promise-of-open-platforms-in-upcoming.html

FCC wants: Any device and application

Carriers want their devices, applications, services, and no wholesale network pricing!


Architecture Vs NeutralityArchitecture Vs Neutrality

Centralized networks such as the PSTN and Cellular are easy to control and do not promote network neutrality But, then can be neutral if the central manager allows it

Distributed networks such as the Internet promote neutral network But, it is possible for ISPs to bias traffic

The PSTN has grown more distributed, and the Internet has become more centralized

Centralized networks such as the PSTN and Cellular are easy to control and do not promote network neutrality But, then can be neutral if the central manager allows it

Distributed networks such as the Internet promote neutral network But, it is possible for ISPs to bias traffic

The PSTN has grown more distributed, and the Internet has become more centralized


End-2-end Vs NeutralityEnd-2-end Vs Neutrality

True e-2-e networks are by definition neutral The “old Internet” was e-2-e The “new Internet” is not e-2-e

The ISP may filter and bias traffic to and from users The ISP may filter and bias traffic to and from other

ISPs

True e-2-e networks are by definition neutral The “old Internet” was e-2-e The “new Internet” is not e-2-e

The ISP may filter and bias traffic to and from users The ISP may filter and bias traffic to and from other

ISPs


Continuum of Network ArchitectureContinuum of Network Architecture

Most flexible withleast control

and accountability

Most efficient, withmost control

and accountability

VerySmart

PSTNPBX

Centrex

MPLS, NATsIPv6

SmartVery dumbVery smart

Very dumb

Smart

Internet


Neutrality Model - Assumptions and Notation

Neutrality Model - Assumptions and Notation

A neutral network has a single provider for all transport, content, and services

A non-neutral network has a single transport provider and many content/service providers

The Transport provider offers a service bundle (voice, video, email) including transport and its pick of content/services

The costs of a neutral and non-neutral network is the same to build and manage We believe the non-neutral network is more expensive, which

strengthens our argument The network has N users

A neutral network has a single provider for all transport, content, and services

A non-neutral network has a single transport provider and many content/service providers

The Transport provider offers a service bundle (voice, video, email) including transport and its pick of content/services

The costs of a neutral and non-neutral network is the same to build and manage We believe the non-neutral network is more expensive, which

strengthens our argument The network has N users


Neutrality ModelNeutrality Model R(SCP) = total revenue from customers for services and content to the provider(s)

Sum of revenue for all non-transport services and content. R(TSP) = total revenue from customers for transport service to the transport

provider We assume the value of R(TSP) is proportional to the value of R(SCP), the more the

services and content is worth, the more the pathway to these services and content is valued by users

Let “P” be this proportionality constant, then: R(TSP) = “P” * R(SCP)

This is similar to metered pricing that charges by byte, however in this case the “network tax” is related to the value of the service to the user, not the network resources consumed by the service

In this simple model the total value of the network is just R(SCP) + R(TSP) V(Total) = R(SCP) * (1 + “P”) – Total value of the network infrastructure.

V(Total) has two components, the transport service (i.e. R(SCP) * “P”) and the service component (i.e. R(SCP))

R(SCP) = total revenue from customers for services and content to the provider(s) Sum of revenue for all non-transport services and content.

R(TSP) = total revenue from customers for transport service to the transport provider We assume the value of R(TSP) is proportional to the value of R(SCP), the more the

services and content is worth, the more the pathway to these services and content is valued by users

Let “P” be this proportionality constant, then: R(TSP) = “P” * R(SCP)

This is similar to metered pricing that charges by byte, however in this case the “network tax” is related to the value of the service to the user, not the network resources consumed by the service

In this simple model the total value of the network is just R(SCP) + R(TSP) V(Total) = R(SCP) * (1 + “P”) – Total value of the network infrastructure.

V(Total) has two components, the transport service (i.e. R(SCP) * “P”) and the service component (i.e. R(SCP))


Expected Average Revenue Per User (ARPU)

Expected Average Revenue Per User (ARPU)

Users will pay more for what they like better! Nobody really knows what users want for content

and services Nobody knows what users will pay for what

content There is a limit! Price to get 50% of users in uncertain markets =

Average Price (AP)

Users will pay more for what they like better! Nobody really knows what users want for content

and services Nobody knows what users will pay for what

content There is a limit! Price to get 50% of users in uncertain markets =

Average Price (AP)



00.050.1

0.150.2

0.250.3

0.350.4

0.45

-3 -2 -1 0 1 2 3

Experiment Value

Probability

S.D=1

1s.d.

13%

34%

2%2%Mean

34%

13%

U100U10U2 U1000Us er Value

100

Users thatvalue service

far less than average


a bit less than average


a bit more than average


far more than average

AP

Market Segmentation of Users


-25

-20

-15

-10

-5

0

5

10

15

20

25

0 20 40 60 80 100

Experiment Number

Experiment Value

Var=1Var=5Var=10

Best Content

Content Provider

Content Value

Simulation of Value of Choice

Service/Content/Application Provider

Best Service/Content/Application


Value of Non-Neutral Network(No Market Uncertainty)

Value of Non-Neutral Network(No Market Uncertainty)

In this case, R(SCP) = the number of subscribers, times the fixed price. The fixed price with no market uncertainty is just “AP” the mean of the no longer random variable describing the value of a set of services selected by the service provider

R(SCP) = “N” * “AP” V(Total) = “N” * “AP” * (1 + “P”)

In this case, R(SCP) = the number of subscribers, times the fixed price. The fixed price with no market uncertainty is just “AP” the mean of the no longer random variable describing the value of a set of services selected by the service provider

R(SCP) = “N” * “AP” V(Total) = “N” * “AP” * (1 + “P”)


Value of Non-Neutral Network(Market Uncertainty)

Value of Non-Neutral Network(Market Uncertainty)

The single provider only gets 50% of the users because the other 50% of users value the service bundle at less than the provider is charging

V(Total) = “N/2” * “AP” * (1 + “P”) Market uncertainty reduces the value of a non-

neutral network by 50%

The single provider only gets 50% of the users because the other 50% of users value the service bundle at less than the provider is charging

V(Total) = “N/2” * “AP” * (1 + “P”) Market uncertainty reduces the value of a non-

neutral network by 50% Normal Density Function

00.050.1

0.150.2

0.250.3

0.350.4

0.45

-3 -2 -1 0 1 2 3

Experiment Value

Probability

S.D=1

1s.d.

13%

34%

2%2%Mean

34%

13%

U100U10U2 U1000Us er Value

100


Value of Neutral Network(No Market Uncertainty)Value of Neutral Network(No Market Uncertainty)

Users have choices, but don’t care much about them V(Total) = “N” * “AP” * (1 + “P”)

Same value as non-neutral network But, in this case the transport provider does not get all of this

We assume they get 75% of the content/service revenue because their content/services are as good as any other service providers

The other content/service providers get 25% of content/service revenue Transport SP gets 0.75*N*AP for services + P*N*AP for

transport services All others split 0.25*N*AP content/service revenue

Users have choices, but don’t care much about them V(Total) = “N” * “AP” * (1 + “P”)

Same value as non-neutral network But, in this case the transport provider does not get all of this

We assume they get 75% of the content/service revenue because their content/services are as good as any other service providers

The other content/service providers get 25% of content/service revenue Transport SP gets 0.75*N*AP for services + P*N*AP for

transport services All others split 0.25*N*AP content/service revenue


Value of Neutral Network (Market Uncertainty)Value of Neutral Network (Market Uncertainty) V(Total) = (revenue of services from transport provider) + (revenue from services for other providers) + (revenue from new users) + (transport revenue)

V(Total) = (“N/8” * AP) + /25% of the 50% of users that value the /bundled service the most - Very Happy ((3/8) * “N” * Ux) + /rest of the 50% don’t get the bundle, but /they pay more - i.e. Ux

((34/100) * “N” * Ux) + /68% of the 50% of non-users become /users because they have choice, they pay Ux “P” * ((“N/8” * AP) + ((3/8) * “N” * Ux)) + ((34/100) * “N” * Ux))) /Transport

= (1+P) * (“N/8” * AP + (71.5/100) * “N” * Ux)

Total service revenue is (“N/8” * AP + (71.5/100) * “N” * Ux), and the network transport tax is P times this service revenue

V(Total) = (revenue of services from transport provider) + (revenue from services for other providers) + (revenue from new users) + (transport revenue)

V(Total) = (“N/8” * AP) + /25% of the 50% of users that value the /bundled service the most - Very Happy ((3/8) * “N” * Ux) + /rest of the 50% don’t get the bundle, but /they pay more - i.e. Ux

((34/100) * “N” * Ux) + /68% of the 50% of non-users become /users because they have choice, they pay Ux “P” * ((“N/8” * AP) + ((3/8) * “N” * Ux)) + ((34/100) * “N” * Ux))) /Transport

= (1+P) * (“N/8” * AP + (71.5/100) * “N” * Ux)

Total service revenue is (“N/8” * AP + (71.5/100) * “N” * Ux), and the network transport tax is P times this service revenue

Value linked to uncertainty

Best of x choices


Value ModelValue Model

AP = $100 - The average price users are willing to pay for a service.

SD = $100 – The standard deviation of the distribution describing the value of services to users.

“N” = 1000 – Number of potential users “P” = .50 - Fraction of revenue for services that a user

pays for transport – network tax. X = 100 – Number of choices a user has for services. U(100) is rounded to 2 standard deviations above AP, thus

U(100) = $300.

AP = $100 - The average price users are willing to pay for a service.

SD = $100 – The standard deviation of the distribution describing the value of services to users.

“N” = 1000 – Number of potential users “P” = .50 - Fraction of revenue for services that a user

pays for transport – network tax. X = 100 – Number of choices a user has for services. U(100) is rounded to 2 standard deviations above AP, thus

U(100) = $300.


ResultsResultsNo Market Uncertainty

Non Neutral Network Neutral Network

Transport Services Total Transport Services Total

Transport SP 50K 100K 150K 50K 75K 125K

Other SPs 0 0 0 0 25K 25K

Total network value 50K 100K 150K 50K 100K 150K

High Market Uncertainty

Non Neutral Network Neutral Network

Transport Services Total Transport Services Total

Transport SP 25K 50K 75K 113,500 12,500 126,000

Other SPs 0 0 0 0 214,500 214,500

Total network value 25K 50K 75K 113,500 227,000 340,500

• Uncertainty decreases the value of a non-neutral network• Uncertainty increases the value of a neutral network


ConclusionConclusion Real options provide a way to model uncertainty Our model illustrates the tradeoffs between: market

uncertainty, the advantages of control and central management, and the number of experiments

It shows that neutral networks generate more total revenue (transport + services) in uncertain markets

The question changes from neutrality or not, to how to split the bigger pie

Suggestions for what next

Real options provide a way to model uncertainty Our model illustrates the tradeoffs between: market

uncertainty, the advantages of control and central management, and the number of experiments

It shows that neutral networks generate more total revenue (transport + services) in uncertain markets

The question changes from neutrality or not, to how to split the bigger pie

Suggestions for what next


AcknowledgementsAcknowledgements

My thesis advisor H.T. Kung Carliss Baldwin and Marco Iansiti from

Harvard Business School Scott Bradner

My thesis advisor H.T. Kung Carliss Baldwin and Marco Iansiti from

Harvard Business School Scott Bradner

© Mark Gaynor 11/05/08 - IPAM1 Real Option Framework to Value Network Architecture and Network...

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