spectrum workshop - issues and challenges in spectrum allocations and spectrum valuation

Spectrum workshop Issues and challenges in spectrum allocations and spectrum valuation

Stefan Zehle, CEO

Coleago Consulting

[email protected]

+44 7974 356 258

http://www.coleago.co.uk/consulting-services/spectrum-strategy-and-spectrum-auctions/spectrum-valuation.html



http://www.coleago.co.uk/

2

Introductions

Market, spectrum and technology overview

Principles of spectrum valuation

Spectrum valuation in practice

Spectrum renewal

Summary

Appendix 1 - Steps in Network Consultation

Appendix 2 - The Modelling Process

Agenda

© Copyright Coleago 2012 Spectrum Workshop

Our skills and experience

Introductions

3 © Copyright Coleago 2012 Spectrum Workshop

Coleago offers advisory services focused on the TMT sector

4

Strategy &

Business

Planning

Marketing &

Customer

Management

Regulation &

Interconnect

Business

Transformation &

Cost Reduction

Due Diligence

Improving

Network

Performance

Spectrum and

Licences

Digital Content &

Media

Training


A refreshingly different approach to consulting

5

Junior Consultant

Senior Consultant

Manager

Senior

Managers

Partner

Analyst

Traditional

Consulting Firm

Model


Spectrum related work

6

Country Year

France 1994/5

Hong Kong 1995

Singapore 1995

Poland 1995

Austria 1995

Belgium 1995

Finland 1996

Denmark 1996

Italy 1996

Taiwan 1996

Brazil 1996/7

Mexico 1996/7

Argentina 1997

Country Year

Czech Republic 1999

Netherlands 2000

United Kingdom 2000

Belgium 2000

Egypt 2006

US (AWS) 2006

Canada (AWS) 2008

India (3G & BWA) 2009/10

UK (2.6GHz) 2009

Poland (2.6GHz) 2009

Ukraine (3G) 2010

Thailand (3G) 2010

Ireland (Renewal) 2010

Country Year

Canada 2001

Ireland 2002

Sudan 2003

Algeria 2004

Iran 2004

Maldives 2004

Oman 2004

Saudi Arabia 2004

USA 2006

Belgium 1997

Kuwait 1997

Ireland 1997

Norway 1998


2011 was an interesting year and 2012 will be similar!

7

Country Year

Australia renewal 2011/12

Bangladesh 3G 2011

New Zealand 2011

Switzerland 2011/12

United Kingdom 2011/12

Syria 2011

Belgium 2011

Pakistan 2012


Our spectrum expertise is much broader than simply spectrum

modelling and valuation

Spectrum

Consultations

Auction Strategy &

Auction Readiness

Administered

Incentive Pricing

Live Auction Support

© Copyright Coleago 2012 Spectrum Workshop 8

http://www.coleago.co.uk/consulting-services/spectrum-strategy-and-spectrum-auctions.html

http://www.coleago.co.uk/consulting-services/spectrum-strategy-and-spectrum-auctions.html

The role of spectrum in determining

operator performance

Market development, spectrum

and technology overview


Significant traffic growth driven by mass market adoption of

smartphones and large-screen mobile broadband

10

Step Change in Mobile

Broadband

Data speeds capable of

delivering a good user

experience

Data optimised and

desirable devices for

consumer and business

applications

Flat fees; pricing

consistent with the

application

Compelling applications

and content

Time

Data Traffic

Minimum Acceptable User Experience

0

1

10

100 LTE

5

50 HSPD

A+

CSD

HSCS

D

GPRS

HSPD

A

Mbit/s

Time

EDGE

-

10

20

30

40

50

60

70

80

90

3 O2 Orange Vodafone T-Mobile

GB

£ / G

Byte

Jun-06 May-08 Mar-09


Mobile data traffic is not just about laptops and smartphones…

11

Cisco forecasts imply an average data usage CAGR of ~70% p.a.


Mobile data traffic is rapid and consumer create most of the traffic,

example Sweden

© Copyright Coleago 2012

0

50

100

150

200

250

300

2H 061H 072H 071H 082H 081H 092H09

Mb

yte

s/ C

usto

mer / M

on

th

Mobile Data Usage in Sweden

Consumer Business Blended

0

5,000

10,000

15,000

20,000

25,000

30,000

1H 07 1H 08 1H 09Te

rra

byte

s

Annual Mobile Data Traffic in Sweden

Private Business Total

12 Spectrum Workshop

Singapore exhibits similar trends as see in Europe

131244

550

802

1,007

1,615

2,197

2,626

0

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1,000

1,500

2,000

2,500

3,0001

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StarHub Singapore Packet Data Traffic

102164

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StarHub Singapore Packet Data Traffic per 3G Customer

© Copyright Coleago 2012 13 Spectrum Workshop

Technology developments: LTE is now a commercial reality and

WiMAX is potentially being marginalised

14

FDD TDD

HSPA LTE WiMAX LTE

200+ operators

support 3.6Mbps+

circa 40 operators

support 14.4Mbps

The first commercial

LTE service launched

December 2009 in

Sweden and Norway

by TeliaSonera

Test networks

launched at 800MHz

and 2.6GHz in

Germany (Sep 2010)

LTE 1800 trials in Finland and Australia

Russian telecoms

operator Yoto (2nd

largest worldwide

WiMax player)

intends to switch

from WiMax to LTE

for its future roll-out.

Clearwire, the largest

WiMax player, and

Sprint, have also

made statements

that neither would

rule out LTE

technology.

Nortel’s Chinese

R&D unit completed

a streaming video

session over LTE

TDD.

Likely that LTE rather

than WiMax will be

rolled out in India.

MWC Barcelona:

TDD LTE equipment

1-2 years from mass

production.


0%

5%

10%

15%

20%

25%

30%

-

10

20

30

40

50

60

4Q

05

1Q

06

2Q

06

3Q

06

4Q

06

1Q

07

2Q

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3Q

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4Q

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1Q

08

2Q

08

3Q

08

4Q

08

1Q

09

2Q

09

3Q

09

4Q

09

AR

PU

StarHub Singapore - Voice & Data ARPU

Voice Data Data %

Decoupling of traffic and revenues: growth in data usage far outstrips

data ARPU growth

15

0%

5%

10%

15%

20%

25%

30%

0

5

10

15

20

25

30

35

40

1Q

06

2Q

06

3Q

06

4Q

06

1Q

07

2Q

07

3Q

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4Q

07

1Q

08

2Q

08

3Q

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4Q

08

1Q

09

2Q

09

3Q

09

4Q

09

Data

% o

f AR

PU

Mo

nth

ly A

RP

U €

Orange France Data Voice and Data ARPU

Voice Data Data ARPU %

0%

5%

10%

15%

20%

25%

30%

35%

0

10

20

30

40

50

60

Q107

Q207

Q307

Q407

Q108

Q208

Q308

Q408

Q109

Q209

Q309

Q409

Data

% o

f AR

PUM

on

thly

AR

PU

US

$

AT&T USA - Voice and Data ARPU

Data Voice Data % of ARPU

Mo

nth

ly A

RP

U S

$

Orange France voice and data ARPU

0%

5%

10%

15%

20%

25%

30%

35%

0

10

20

30

40

50

60

Q107

Q207

Q307

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Q208

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Data

% o

f AR

PUM

on

thly

AR

PU

US

$

AT&T USA - Voice and Data ARPU

Data Voice Data % of ARPU

Data revenue growth (partly) offsets declining voice ARPU

Relative to data traffic however, data revenue growth remains modest

Significant investments relative to revenue

StarHub Singapore voice and data ARPU

Mo

nth

ly A

RP

U €


More spectrum becoming available for mobile communications

16

Mo

bile

Dig

ital

TV

Dig

ital

Div

ide

nd

Mo

bile

GS

M

3G

3G

3G

LT

E

Mo

bile

Exp

an

sio

n

450M

Hz

470M

Hz

698M

Hz

806M

Hz

850M

Hz

900M

Hz

1800M

Hz

1900M

Hz

2100M

Hz

2300M

Hz

2500M

Hz

3400M

Hz

3600M

Hz

Better for

Coverage

Geographic

Coverage

Indoor

Coverage

Better for

Capacity


The cost of geographic coverage is lower with lower frequency bands

17

100% 126%

323%

455%

675%

1230%

0%

200%

400%

600%

800%

1000%

1200%

1400%700M

Hz

850M

Hz

2100M

Hz

2500M

Hz

3500M

Hz

5800M

Hz

Relative Capex to Build Coverage

Coverage of rural areas

with digital dividend

700/800 MHz spectrum is

about 30% of the cost

compared with 2100 MHz

coverage.

Source: SFR, France


The superior propagation characteristics of low band spectrum yield a higher

probability of (deep) in-building service at a given performance

This may be translated in terms of a % of demand that is only addressable with low

band spectrum (or with potentially expensive in-building solutions)

Indoor propagation characteristics

18

Probability of

service

With spectrum

below 1GHz

With spectrum

above 1GHz

% Demand Deep indoor


The surge in data traffic results in a incremental capex and a squeeze

on margins

The capex-to-sales ratio is increasing

again, reversing the declining trend

– Threat of negative returns on

incremental customers

In response to high traffic volumes,

operators have started to abandon

unlimited data plans in 2010

Increased prevalence of service

restrictions (e.g. P2P, continuous

video)

– However, future net neutrality

regulations could preclude this

19

Congestion squeezes margins

Time

Revenues per

incremental

customer decline

Marginal costs per customer

increase at capacity limits

Squeeze on margins

due to costs of

congestion-relief


Shifting emphasis: Is capacity to data what geographic coverage was

to Voice?

As networks ‘fill up’:

– Capacity becomes a scarce resource

– Mobile communications shifts from a “buyer’s market” to a “seller’s market”

Key premises:

– It may not be feasible to build oneself out of congestion

– Traffic will tend to migrate from more congested networks to less congested

networks

If so, market shares will tend to converge towards shares of industry capacity

– Direct impact: market shares of data traffic and revenues

– Indirect impact: market shares of voice, through linked / correlated accounts

Maintaining a fair share of industry capacity is of strategic importance


There may be no alternative to securing spectrum

But securing fair-share of capacity is a strategic imperative for individual operators

– To ensure a level playing field and to protect (or grow) market share

Once other means have been exhausted, spectrum acquisition may be the only

remaining option

21

Shares of Spectrum and capacity

Share of

Industry

Capacity

MNO average

MNO

Amount of

Spectrum

acquired by

an MNO

Minimum

required

for capacity

parity

Demand vs. Industry capacity

Time

Capacity

Market Congestion?


Spectrum is moving centre stage

GSM Spectrum liberalisation / re-farming

– Introduction of technology neutrality, enabling introduction of HSPA and LTE in

former GSM bands

New Mobile Spectrum releases

– 2.6GHz and the digital dividend spectrum in 700 / 800 MHz

Licence Expiry

– In many countries the 900 and 1800 MHz GSM licences are near to expiry, and

some 2.1 GHz licence are only 4 years away from expiry

– Renewal may involve negotiations around Administered Incentive Pricing

New mobile spectrum releases and spectrum renewal negotiations invariably call

for a spectrum valuation exercise, in which all existing and expected future

spectrum needs to be considered jointly


The basic principles of valuing

spectrum

Spectrum valuation




Spectrum valuation is central to spectrum award and renewal

processes

Shareholder

Value

What and

how much

spectrum do

we want?

How do we obtain the

spectrum as cheaply as

possible?

What is the

value of the

spectrum?


Recent auction outcomes show big variations in prices

25

2.6GHz prices paid


Very large variations in prices paid are due to different auction

dynamics and levels of competition

26

Country Year €/MHz/pop Commentary

Hong Kong 2009 0.252 5 bidders for 3 blocks

Sweden 2008 0.130 5 bidders for 4 blocks; one new entrant

Denmark 2010 0.164 4 bidders; 2nd price auction, low spectrum

caps

Norway 2007 0.036 2 operators plus Craig Wireless

Germany 2010 0.028 4 operators and 140MHz; substitute spectrum

available

Finland 2009 0.004 3 operators and 140MHz; single TDD block

sold for 50% higher price than FDD

Netherlands 2010 0.001 3 operators and two cablecos; low spectrum

caps, and 2nd price rule

2.6GHz FDD prices paid in recent auctions:


Digital dividend spectrum is more expensive: Demand and supply is

the key driver

27

0.73

0.03

0.11

0.02 0.02

-

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

800 MHz Paired

1.8 GHz Paired

2.0 GHz Paired

2.6 GHz Paired

2.6 GHz Unpaired

€/ M

hs /

Po

ps

German Spectrum Auction Prices €/MHz/Pop


Valuing spectrum is conceptually straightforward

28

Net Present Value with

NPV without

Valuation

Business value with

extra spectrum

Business value

without extra

spectrum

Maximum value of

extra spectrum

The valuation needs to take mitigating strategies into account: We

compare optimal ‘acquire’ with optimal ‘non-acquire’ cases (i.e.

assume optimal strategy is pursued in all cases)


Valuations are typically based on a 10 year forecast and a terminal

value using Discounted Cash Flow Analysis

29

Free Cash Flow

Forecast

NPV of 10

Year Forecast Terminal

Value

EV

Valuation

Aligned with management forecasts

in the early years

Valuations are then subject to

benchmarking using company

comparables such as EV / EBITDA


How value is created from spectrum is not always fully appreciated

There are two options to end an auction:

Option A, you could obtain 20 MHz

– You value 20 MHz at € 500 million

– You can obtain it for € 480 million

Option B, you could obtain 10 MHz



30

Which would you

choose?


Value creation arises where spectrum valuation and the price paid in

the award process meet

There are two options to end an auction:

Option A, you could obtain 20 MHz



Option B, you could obtain 10 MHz



31

Value created:

€ 20 million

Value created:

€ 60 million


It’s about increasing shareholder value, not about acquiring the

largest or most valuable spectrum blocks

32

Value placed on a block

Price paid

Value created

Oddly, the point about value creation is often the most difficult to

communicate to senior management.

€ / $


33

Increasingly there are multiple-bands to be valued

Business value with

spectrum

Business value

without spectrum

Maximum values of

spectrum


Synergies between and within blocks requires a holistic approach

34

800MHz

900MHz

1800MHz

2100MHz

2600MHz


The degree of complexity and the number of valuations can be

difficult to comprehend

Spectrum valuation is increasingly

complex

Large number of feasible spectrum

combinations all require values

Edge-block interference means the

position of spectrum blocks is important

Key uncertainties around demand and

technology require a scenario-driven

approach

35

Band Mode Available MHz

800MHz FDD

TDD 2 x 30

900MHz FDD 2 x 35

1800MHz FDD 2 x 75

2.1GHz FDD

TDD

2 x 60

1 x 20

1 x 15

2.6GHz FDD

TDD

2 x 70

1 x 45

Total 620MHz

Example: Swiss Spectrum Auction


Operational sources of spectrum value

Blocking value

Capacity competition

Quality & coverage competition

Access speed claim competition

Site-build capex avoidance

Technology migration benefits

Any assumptions that have a market

share impact will lead to high

spectrum valuations

Technically related sources usually

generate lower spectrum valuations


Non operational sources of spectrum value

Tax shield

Terminal value assumptions


A good general philosophy

38

“It’s better to be roughly right than precisely wrong”

John Maynard Keynes


Issues in spectrum valuation



40

Spectrum valuation must take all potential resources into account,

in different parts of the network

Deep indoor

Deep indoor

Rural Urban

Feasible coverage with

low band spectrum only

Addressable with

all bands

Macro network

Macro densification

layer

Capacity solutions

layer

Lower scope for cell-

splits in (dense) urban

given high site density

Higher scope for cell-

splits in rural given

low site density

Outdoor: small cells

Indoor: Femto cells and

WiFi

Limited scope for small

cells and WiFi offload


Identifying industry bottlenecks is paramount

Technology roadmap and device penetration

Low (initial) penetration of LTE-enabled devices limit the utilisable capacity in LTE

bands such as 800MHz and 2.6GHz

– 3G capacity likely to remain the bottleneck in the near/medium term

The site upgrade path may have a significant impact on the valuation

Regulatory network deployment constraints

Severe emission limits may prevent operators from deploying additional mobile

channels on individual sites (e.g. Switzerland)

Planning constraints may limit the scope for site build, and constrain site densification

(e.g. no permission to build on residential property in Ukraine)

The problem may be capacity, in-building quality, geographic coverage, or all three

Securing the right mix of spectrum may be as important as obtaining the right quantity


Spectrum valuation must take account of mitigating strategies

Capacity solutions

– Indoor: Femto cells, Private WiFi

– Outdoor: small cells

– Traffic offloading on public WiFi

Yield management / repositioning the offer

– Focus on existing and new voice customers (converged offerings)?

– Prioritize access to network capacity to high-value customers?

Infrastructure-sharing

– Potential source of capacity and coverage synergies as well as cost rationalisation

Future spectrum releases?

Buy capacity from a competitor?

Mitigate limited geographic footprint through national roaming?

A valuation must reflect all that is relevant to the asset being valued


Challenging strategic questions need to be addressed

Should operators deploy HSPA in 900MHz or go straight to LTE?

900MHz enabled HSPA devices widely available today

Potential first mover advantage

LTE offers higher performance

Migrating from to LTE from HSPA in the future introduces extra costs

Should operators pursue a strategic or tactical LTE deployment?

Strategic: urban or national LTE footprint?

– What is the business case?

Tactical: only deploy LTE as a capacity resource in busiest parts of the network?

How much GSM spectrum can or should one re-farm for 3-4G?

When can GSM be switched off?


Generic methodological principles



Key sources of spectrum value

45

Greater capacity

(all bands)

Fewer sites

for given coverage

and capacity

(all bands)

More traffic

Greater coverage

footprint

(low band)

Extra Spectrum

Higher costs of

sale & overheads

In-building quality

(low band)

Greater

performance

(2x20MHz LTE)

More customers

Higher network

costs

Lower network

costs

Spectrum roll-out

costs

More revenues


Valuing capacity: Network congestion puts customers and

revenues at risk

46

% of cells

overloaded

Mbps per

Cell

Network Cells

(ranked by peak demand)

Maximum Throughput per Cell

(including densification uplift and

other capacity solutions)

Need to take an industry-wide view: consider congestion levels versus any spare

capacity across all operators

Unserved demand

leads to loss of

customers and

revenues if there’s

a better alternative

elsewhere

Unconstrained Peak

Demand per Cell

Constrained Peak

Traffic per Cell


Illustration

Operator A has more spectrum, leading to higher cell throughput

Operator A is positioned as a quality network, and prices its services at a premium

Operator B is a low cost operator; as a result, customers are more willing to accept a

lower quality of service during peak hours

Operator B has a lower cell throughput, but higher overall congestion tolerance

Valuing capacity: Customer migration between networks will

depend on relative congestion-tolerance levels

47

Cell

Throughput

(Mbps)

Congestion-

Tolerance

Threshold

Cell

Throughput

(Mbps)

Congestion-

Tolerance

Threshold

Operator A

Operator B


Valuing capacity: Which customers have highest propensity to

churn?

The relative impact of congestion across key segments is likely to reflect

Degree of customer exposure to the problem (hence sensitivity to congestion)

Yield management strategies pursued by operators

– De-prioritising least desirable customers (lowest % margin contributors)

48

Device type Segment Description Average %

margin

Sensitivity to

congestion

Small

screen

(“HS”)

“Standalone HS Low” Low data usage; not

sensitive to congestion

High (low

data) Negligible

“Standalone HS High” High small-screen data

usage

High (limited

data) Moderate

“Linked HS-PC” Correlated small & large-

screen; incl. tethering

Medium

(heavy data) High

Large-

screen

(“PC”) “Standalone PC” Independent of small

screen voice and data

Low (heavy

data no voice) High


49

Valuing in-building quality: Benefit of Low Band spectrum

Probability of

service

With spectrum

below 1GHz

With spectrum

above 1GHz

Deep indoor

RuralUrban

Deep indoor

In-building quality benefits of LB

spectrum can be expressed in terms

of addressable demand

– Without low band spectrum, none

of this ‘deep indoor’ demand can be

served

– Unless potentially costly indoor

solutions are deployed

– Such solutions can only solve part

of the problem

Cannot be mitigated using yield

management strategies

Hong Kong: 850MHz worth 5x more

per MHz than 2.6GHz spectrum!

Value of additional blocks of low band

spectrum can be quantified using the

‘capacity-value’ approach

% Demand


Valuing deep indoor capacity: Additional Low Band spectrum

increases the % demand that can be served

50

% of cells

overloaded with

1 block

Deep

indoor

Mbps per

Cell

Network Cells

(ranked by peak demand)

Max Indoor Throughput per Cell

with 2 LB Blocks

The first block of low band spectrum provides the largest increase in addressable

indoor demand; subsequent blocks generate decreasing marginal returns

Constrained Deep

Indoor Traffic per Cell

Max with

1 LB Block

Extra demand

addressable with

additional LB

block

Unconstrained Deep

Indoor Demand per Cell


Low Band spectrum may enable an operator to extend the geographic footprint

Potential impact on addressable market, hence market share (if significant rural

demand exists)

Impact of wider footprint on marketing productivity

– Share of gross ads, retention rate (reduced churn)

– Scope for price premium (ARPU impact)

51

Valuing geographic coverage: Low Band impact on footprint

Deep indoor

Deep indoor

Rural Urban


Performance (widest LTE channel)

One 2x10MHz LTE channel provides greater performance for a given level of traffic

than two 2x5MHz channels,

One 2x20MHz LTE channel provides greater performance for a given level of traffic

than two 2x10MHz channels, but only marginally

Potential impact on marketing productivity of “speed claim” / experienced performance

Network cost avoidance

To achieve a given level of capacity: deploying spectrum on existing sites is typically

less expensive than splitting cells and deploying micro solutions (indoor: Femto cells;

outdoor: small cells)

To achieve a given geographic footprint: rolling out a network with lower bands is less

expensive (and yields better quality of coverage) than doing so with higher bands

Positioning of spectrum blocks can also impact on value

Edge block interference (e.g. 2.6GHz FDD versus TDD)

Interference with digital terrestrial TV (800MHz)

52

Other spectrum value components


Model structure overview

53

Customers,

ARPU/AUPU,

Revenues

Network

Dimensions

Network

Costs

Scenario Manager, User Interface

Traffic

Segmented

Analysis

Total

Market

Demand

Capacity /

Congestion

Analysis

Consolidation Model Network Model Market Model

Market

Scenarios

Technical

Scenarios

Regulatory

Scenarios

Competition

Scenarios

Coverage

Analysis

Spectrum valuation: cash flows ‘With’

minus ‘Without’ extra spectrum

Cash flows, Financial Statements

Device

Diffusion

Traffic

Distribution

Profile

All MNO’s

(Industry-

wide

view)


Spectrum renewal costs also bear on the

terminal value of new spectrum acquired

Spectrum Renewal


Uncertainties around the conditions, process and costs of spectrum

renewal pose further challenges for operators

Typical approaches to spectrum renewal

Setting of renewal fees using Administered Incentive Pricing (AIP)

Re-auctioning existing spectrum holdings upon licence expiry (e.g. Singapore

2008 for 900MHz renewal, proposed in Switzerland and the Netherlands

Private, bi-lateral negotiations between regulator and individual operators, with

threat of auction if no agreement is reached (e.g. Australia)

Typical regulatory objectives

Secure an adequate return to society and incentivise efficient use of spectrum

Maintain competition

By setting prices that will appear:

– Comparatively cheap for those who make best economic use of it and

comparatively expensive for less efficient users of the spectrum, thus

‘incentivise’ more efficient use of spectrum resources


Operators who face licence expiry are usually better off with a

negotiated settlement rather than a re-auction

Operators faced with the expiry in their licence and refarming usually go

through a negotiation process

Case study: Australian 800MHz, 1.8GHz, 1.9GHz TDD and 2.1GHz renewal

– Separate negotiations with each operator on renewal fees

– Threat of auctioning the spectrum to be renewed if individual operators fail to

reach negotiated agreement

Developing a compelling negotiation case for favourable spectrum renewal

terms is essential

– Covering both renewal fees as well as conditions (e.g. technology neutrality)

– Ensuring competitors may no less per MHz, and ideally more!

“Independent” reports commissioned by operators that support their case may

help to sway the argument in their favour


Administered Incentive Pricing (AIP)

Most regulators are obliged to agree an allocation methodology for renewal

that:

– yields a return for society and ensures that economic benefit is generated

– ensures that the mobile market is sufficiently competitive

Recognising that a simple re-auction may not be appropriate, many regulators

have opted for negotiated renewal prices using different methods, such as:

– Spectrum fee benchmarking

– Optimum Deprival Value (ODV)

– Best Alternative Use (BAU)


Benchmarking

Benchmarking is the process of setting prices against a proxy taken from

another, comparable market.

Benchmarks do not reflect valuations but prices paid.

International benchmarks suffer problems of translation to the local context.

– Spectrum demand and supply are very different is each country

– Markets vary in terms of population, population density, geography, income

levels / willingness to pay and input cost levels (e.g. staff costs).

– Technically, benchmarking is further affected by such factors as choice of

exchange rate, the comparator set and so on.

– Timing also matters, since perceptions of the prospective value of mobile

spectrum has varied significantly over time.

Benchmarks are not considered as a suitable method in setting spectrum prices,

but cash strapped governments have used them to justify high reserve prices.

– A situation best avoided, but depends on regulatory policy


Optimal Deprival Value (ODV) – Academic description

Deprival value is a cost-based valuation approach that answers the question:

“What is the least cost system or bundle of assets needed to provide

customers with the existing level and quality of services, should a certain

existing asset be removed?”

This approach can be applied to valuing spectrum rights by addressing the

following:

“If an operator was deprived of incremental spectrum rights, what incremental

costs would be incurred to replicate the existing level and quantity of services

using the remaining spectrum rights?”

These costs are “avoided” by owning the incremental spectrum rights and so

represent the value of those rights. The rights holder should be prepared to

pay up to the value of the incremental costs to avoid being deprived of its

spectrum rights, so long as the incremental costs are less than the present

value of the free cash flows generated from the spectrum services.


Optimal Deprival Value (ODV)

ODV calculates this price on the basis of the ‘deprival value’ of a marginal block

of spectrum (typically 5MHz), for an ‘average reference operator’

– Deprival value: the network costs that would need to be incurred to offer the

same quality of mobile service, if the marginal spectrum block were lost

– The only source of value is technical, hence ODV produces a low value

Since this is calculated for an ‘average operator’ with ‘average spectrum

holdings’, the ODV price per MHz should appear:

– Less expensive for operators with less spectrum, who would value it more

highly

– More expensive for those with surplus spectrum, who should value the

marginal block less highly

– In this sense, ODV would reflect an ‘optimal price’ in terms of incentives, by

encouraging ‘spectrum hoarders’ to give up marginal blocks to more efficient

users

ODV generates a uniform price per MHz in any band, for all operators


Best Alternative Use (BAU)

In contrast to ODV, BAU considers the value placed on an incremental block of

spectrum by alternative users or uses, such as:

– An alternative technological use

– A new mobile entrant

– Competitors

The case for new mobile market entry is typically weak, and the alternative

technological uses of mobile spectrum are invariably less valuable than mobile

Hence BAU is normally driven by the value placed by existing competitors on a

marginal block of spectrum

– Unlike ODV, BAU may generate different prices per MHz for each operator

If all other things are equal, BAU should generate a higher price per MHz for

operators with spectrum surpluses, and a lower price per MHz for those with

smaller holdings


In some markets, regulators propose to align renewal fees of expiring

licences with auction outcomes for new spectrum

Current consultation in the UK: base 900MHz and 1800MHz renewal fees on

forthcoming 800MHz and 2.6GHz auction

– 900MHz renewal based on 800MHz proceeds

– 1800MHz renewal based on linear average between 800MHz and 2.6GHz

proceeds (!)

India: proposal to base 1800MHz renewal on proceeds of 2.1GHz auction

No longer an auction for new spectrum, but a simultaneous auction and renewal

fee negotiation!


How to obtain the spectrum as

cheaply as possible

Auction strategy


No auction design is perfect


Design Principle SMRA SMRA-AS CCA

Supports simultaneous award of spectrum

in multi-bands ✔✔✔ ✔✔✔ ✔✔✔

Reduces exposure or aggregation risk ✘ ✔ ✔✔✔

Flexibility over the use of specific or

generic lots ✔✔ ✔✔ ✔

Transparency of bidders and bids ✔✔✔ ✔✔✔ ✔✔

Certainty over prices paid ✔✔✔ ✔✔✔ ✘

Certainty over lots awarded ✔✔✔ ✔✔✔ ✘

Certainty over total expenditure ✔✔✔ ✔✔ ✘

Simplicity and ease of presentation and

transparency of results ✔✔✔ ✔✔✔ ✘

CCA second price auctions

Key characteristics

Winners do not pay the price they bid but a function of the next best allocation of

resources (if the winning bidder were absent)

– Very complex combinatorial algorithms

– Predicting prices paid is challenging for bidders

The price paid by any bidder is determined by marginal valuations expressed by

competing bidders

Prices paid per lot can differ significantly between bidders

– It is possible for a bidder to pay more for less spectrum than a competitor!


Real Example: impact of second price rule in the Denmark CCA

based 2.6GHz auction in 2010

Hutchison paid €0.9 million for 2x10 MHz

of FDD plus 25 MHz of TDD

The other bidders who acquired 2x20

MHz FDD paid ~20x more per MHz

This dramatic outcome was a product of a

second price combinatorial auction with

tight spectrum caps:

– TDC, Telenor and Telia’s prices

reflected Hutchison’s bid value for an

additional lot of 2x10MHz FDD

– Hutchison’s 2x10MHz FDD could not

have been sold to anyone else, hence

the 2nd price was the reserve price

66

* Prices paid per MHz


H3G TDC Telia Telenor

Conclusions

67

Spectrum auctions are increasingly complex

These are multi-dimensional problems

Complex game-theoretical aspects

A thorough understanding of the auction rules and the risks and opportunities is

critical

Valuations for each feasible package is required

Not just own valuations, but also the (likely) valuations of other bidders

Extensive competitor analysis and intelligence gathering is required (cash

position, strategic objectives, public announcements, past auction behaviour,…)

Implementation work-streams need to start well in advance

Influence auction rules at consultation stage

Influence government spectrum policies


Overview of auction strategy development and auction readiness


1 Auction objectives,

valuations, bid limits

Understand the work of the valuation team. To agree auction

objectives. Set bid limits and explain rationale.

2 Develop competitor

intelligence

Identify competing bidders and ascertain their auction objectives,

auction strategies and bid limits relative to own valuation.

3 Develop bid strategy Generate actionable insight into the auction format and rules, and into

the underlying opportunities, risks, and mitigating strategies.

4

Develop bid

optimisation &

support tools

Create the tools that allow Coleago to validate bid strategy and

support the implementation of the bid strategy in a live auction

environment.

5 Bid strategy testing

and refinement

Validate strategic hypotheses through auction simulations and

quantify risks and opportunities

6 Mock auctions &

auction readiness

Test the bidding strategy and to train the auction team and to test

auction support tools, bid room protocols, procedures and disaster

recovery as well as providing insight to senior management .

7 Game plan To be able to execute the bid strategy in accordance with robust

corporate governance.

Understand valuations, bid limits and auction

objectives as well as highlighting auction risks

An initial workshop with senior management is often useful to

highlight the key issues that will arise in the auction

A typical workshop agenda is as follows

Overview of the spectrum on offer and any caps

High level overview of the auction process

Explanation of key auction issues and risks that must be addressed

Discussion and agreement of primary and secondary auction objectives

Explanation of the role of bid limits and agreement on the nature of any

limits to be imposed on the bid team

Discussion surrounding management’s attitude towards risk taking in the

auction

Spectrum Workshop © Copyright Coleago 2012 69

Competitor intelligence

Competitor intelligence is

critical in this auction

The valuation workstream also

provides valuation matrices for

all other bidders

We will need to make an

assessment of other bidder’s

likely bid limits

We analyse other bidders

relative to your operation and

adjust their bid limits accordingly

The exercise is highly subjective

so having a framework is useful

Bidder Limit Analysis

Bidder

1

Bidder

2

Bidder

3

Bidder

4

Financial

Strength 1 1 3 3

Strategic

Imperative 2 3 2 2

Previous

Bidding

History 3 2 1 3

Public

Announce-

ments 1 3 3 2

Capacity

Constraints 2 3 1 1


Develop bidding strategy

In the many auctions there is no “dominant strategy”

The academics will analyse the auction rules in detail in conjunction with

– Your auction objectives, valuations and budget limits

– Competitor intelligence, valuations and bid limits

The analysis will allow them to develop a range of potential auction

strategies

We will then “War Game” the potential strategies to

– Test how robust each strategy is to different competitor strategies

– Identify the actions of other bidders that would cause a change in

strategy

– Develop an initial “Auction Game Plan”

We would present the initial “Game Plan” at a bid strategy workshop


Develop the auction simulation tool


Identify and develop appropriate live auction support

tools

With potentially only ten minutes per round many aspects of bid

execution will need to be automated

There are a range of auction support tools that may be appropriate

Auction bid tracker

– Tracks historic bids (audit and governance)

– Predicts when bid limits may be breached for both you operation and

other bidders based on bid increments and bid levels

– Analyses dynamic lot valuations and prices and provides data on

absolute and relative value creation

Bid optimisation tool

– Utilises the results from previous auctions and updates spectrum

values for current and future auctions and generates automated

recommendations for bids


An example of a bid optimiser from the Canadian AWS

spectrum auction


Bid strategy testing and refinement

Extensive auction simulations will be used to test the impact of

deviations from the ‘dominant bid strategy’ under numerous competitive

scenarios, covering:

– Alternative competitor valuation and cash-constraint assumptions

– Alternative ‘price discovery’/ bid inflation assumptions

– Individual and collective deviations from ‘sincere bidding’ strategies

including strategic demand reduction and ‘eligibility parking’

Key outputs

– Comprehensive testing of alternative bid strategies under a broad

range of assumptions to validate approach

– Identification and quantification of risks and opportunities

– Empirical validation of supplementary-bid optimisation and price

prediction capabilities (subject to auction format)


Mock auctions – bid team training

Mock auctions are often more about training the bid team than

developing bid strategy

We recommend running a minimum of two mock auctions

Plan the mock auction process and schedule of auctions

Identify and invite the right participants

Prepare instructions and bidder briefs, including bid limits for each mock

auction for all participants

Explain the auction design, key issues and mock auction process

Run the mock auctions, providing support and training as required

The results and conclusions will be presented at a final auction bid

strategy workshop where the strategy will be refined if appropriate


Mock auctions – testing protocols and procedures

The Belgian auction will require extremely robust auction room

protocols and procedures

The mock auctions provide an opportunity to test all aspects of bid strategy

execution

The effectiveness of the live auction support tools

Bidding protocols

– Deciding the bid strategy, preparing the next bid, entering the bid,

checking the bid, submitting the bid, updating the auction activity

journal

Escalation procedures in the event of anticipated bid limit breaches

Disaster recovery


Auction Game Plan Document

Pre-auction activity – e.g. aggressive statements prior to the auction

Statement of hierarchy of primary and secondary auction objectives

Your valuation and bid limit matrices

Competitor bid limits and triggers for re-assessment of competitors

Opening auction bid strategy

Description of bidding patterns which might indicate strategic behaviour

Description of trigger points for switching auction objectives / strategy

Alternative bidding strategies in response to strategic behaviour

Triggers for bid limit escalation procedures

Bid team roles and responsibilities

Bidding protocols and procedures

Disaster recovery

Post auction press releases prepared for win / lose outcomes


Summary


Summary

Operators typically under estimate the complexities and challenges

associated with spectrum valuation

– Often regarding auction bidding strategy as the more challenging

Early engagement with regulators is essential to ensure that any

spectrum award or renewal process is favourable to you

Coleago can support you across a broad range of issues

– Regulatory strategy and lobbying

– Support during formal spectrum consultation

– AIP lobbying and modelling

– And of course, spectrum valuation, auction strategy and readiness

and live auction support


Steps in Network Consultation

APPENDIX 1

81

Appendix


Typical steps in a public spectrum consultation process


Stage Activity Operator’s Actions

Policy

Formulation

The Government formulates policy for the allocation of spectrum.

Government departments or ministries involved may include

Telecoms, Development, Finance, Competition Commission, etc

Lobby politicians

PR campaign to influence the debate

Notice of

Consultation

At this stage the process moves to the telecoms regulatory authority

who issues a notice of consultation. This includes a description of the

consultation process and timetable. There may also be a workshop to

obtain inputs from stakeholders in an informal manner.

Lobby politicians


Prepare workshop materials

Meetings with regulatory agency

1st Round

Consultation

The regulator issues a formal consultation document which contains a

list of decisions that need to be made in relation to the spectrum

allocation, a discussion and analysis of the issues, perhaps a

preliminary conclusion (“we are minded to....”), and an invitation to

respond to questions relating to each decision that needs to made.

Analyse consultation document

Commission independent reports that support own view point

Prepare & submit response to consultation


Cross Submission

The regulator would normally publish the submissions received from

different stakeholders and invite cross submissions. This gives

stakeholders the opportunity to comment on points made by other

stakeholders.

Analyse other submissions quantitatively (how many agree

with x) and qualitatively

Prepare and file cross submission document


2nd Round

Consultation

The regulator issues a second consultation document which draws on

the submission received and presents its conclusion and a proposal

ahead of the final determination. If an auction is proposed this would

include a description of the auction format and rules.

Analyse consultation document

Submit response to consultation


Final

Determination

The regulator publishes the final determination, including the process,

detailed procedures and rules. The regulator answers questions for

clarification of the process, procedures and rules.

Analyse determination document

Questions for clarification

Explore legal recourse if necessary

Approach to modelling

APPENDIX 1

83

Appendix


Approach to Network Modelling

Overall approach:

Options:

Calculate traffic offloaded onto public WiFi and/or small sites, subject to separate

offload limits in different parts of the network; model using abstract cost per Mbps

Treat densification as a capacity resource relative to existing sites, subject to separate

densification limits in different parts of the network

84

Compare traffic in

each 1% of sites

(all operators) Adjust traffic on

basis of relative

congestion

(all operators)

Calc. resources

required to meet

adjusted traffic

(single operator) Compare max

capacity in each

1% of sites

(all operators)

Calculate capex

and opex

(units x unit costs)

- Spectrum

- Technologies

- Densification, etc.

- RAN

- Backhaul

- Core

LTE roll-out

(single operator)

Appendix


Model structure overview

85

Customers,

ARPU/AUPU,

Revenues

Network

Dimensions

Network

Costs

Scenario Manager, User Interface

Traffic

Segmented

Analysis

Total

Market

Demand

Capacity /

Congestion

Analysis

Consolidation Model Network Model Market Model

Market

Scenarios

Technical

Scenarios

Regulatory

Scenarios

Competition

Scenarios

Coverage

Analysis

Spectrum valuation: cash flows ‘With’

minus ‘Without’ extra spectrum

Cash flows, Financial Statements

Device

Diffusion

Traffic

Distribution

Profile

All MNO’s

(Industry-

wide

view)

Appendix


Impact of spectrum scenario on Reference Demand

86

Customers

ARPU and

AUPU

Reference

Demand

Revenues

and Traffic

Customers

ARPU and

AUPU

Pre-Congestion

Demand

Revenues

and Traffic

Customers

ARPU and

AUPU

Congestion-

Adjusted

Demand

Revenues

and Traffic

Adjustments based

on all commercial

value drivers except

capacity:

– Relative footprint

– Quality

– Performance

Impact on:

– Share of gross ads

– Churn

– ARPU

Adjustments based

on relative

congestion:

– Equalisation of

congestion levels

– Subject to relative

congestion

tolerance limits

– Traffic and subs

migrate from more

to less congested

networks

Impact on:

– Share of gross ads

– Churn

Traffic

Distribution

Profile

Capacity /

Congestion

Analysis

Net Traffic

Migration

Within Consolidation Model

Within Technical Model

Appendix


Valuing capacity: Combined congestion-impact biases

87

“Standalone HS High” 0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

0.0% 20.0% 40.0% 60.0% 80.0% 100.0%

Rela

tive to

avera

ge

% of base

Relative AUPU versus ARPU

ARPU AUPU

“Linked HS-PC” 0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

0.0% 20.0% 40.0% 60.0% 80.0% 100.0%

Rela

tive to

avera

ge

% of base


ARPU AUPU

“Standalone PC” 0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

0.0% 20.0% 40.0% 60.0% 80.0% 100.0%

Rela

tive to

avera

ge

% of base


ARPU AUPU

Key

segments:

Bias within each

segment:

Bias across

segments:

Highest

(e.g. 60%)

Next highest

(e.g. 25%)

Lowest

(e.g. 15%)

Net impact of

congestion:

High impact

on traffic

relative to

revenues

Moderate

impact on

traffic relative

to revenues

Low impact

on traffic

relative to

revenues

Appendix


Modelling workflow (overview)

88

Reference

Demand

(all operators)

Within Consolidation Model

Pre-Congestion-

Demand

(all operators)

Spectrum

impact excl.

capacity

Congestion

Impact

Congestion-

Adjusted Demand

(all operators)

Impact on %

congestion

tolerance

(all operators)

Peak traffic

across network

(all operators)

Congestion

analysis

(all operators)

Within Network Model

Net traffic

migration

(all operators)

Adjusted traffic

(all operators)

Capacity upgrade

requirements

(selected operator)

P&L and Cash

Flows

(selected operator)

Network

dimensions

(selected operator)

Unit costs

Capex & Network

Opex

(selected operator)

Link budgets,

3G+ throughputs

Coverage

analysis

(all operators)

Max effective

capacity per cell

(all operators)

Costs of Sale

& Overheads

(selected operator)

Appendix
