A Mobile-Centric View of Silicon Valley

Prepared for Opinno & PromoMadrid

January 31, 2011

Licensed under Creative Commons Attribution 3.0 Unported License (http://www.creativecommons.org/licenses/by/3.0)You are free to Share or Remix any part of this work as long as you attribute this work to SF Mobile (sfmobile.org)

Lars KampLars Kamp

Work Network

Management Consulting

@l1rs

2

www.sfmobile.org

San Francisco, CA415.894.5423lars@sfmobile.org

Suite 1200560 Mission StreetSan Francisco, CA 94105415.894.5423lars.kamp@accenture.com

Today’s topics.

Mobile Economics

Silicon

History

3

Silicon

Cloud

What’s Next?

History

4

A note on people’s ability to predict the future.

”People tend to overestimate

what can be done in one year

and to underestimate what can

5

J. C. R. Licklider“Grandfather of the Internet”

be done in five to ten years.”

J. C. R. Licklider, 1965

Q: Whose mission statement is this?

“We have a dream of improving the lives of many millions

of people by means of small, intimate life support

systems that people carry with them everywhere.

These systems will help people to organize their lives, to

communicate with other people, and to access

6

communicate with other people, and to access

information of all kinds.

They will be simple to use, and come in a wide range of

models to fit every budget, need, and taste. They will

change the way people live and communicate.”

A: General Magic, 1990. You could say “mobile” started here.

7

General Magic’s “Magic Cap”. Looks familiar?

“Magic Cap” User Interface, 1994

8

Maybe now?

T-Mobile G1 (HTC Dream) User Interface, 2008

9

Three people from the team that architected Magic Cap.

Andy Rubin Tony Faddel Kevin Lynch

10 Source: Wired, SF Mobile analysis.

Economics

11

Software-driven innovation.

” The problem is, in hardware you

can't build a computer that's twice as

good as anyone else's anymore. […]

12

But you can do it in software.”

Steve Jobs, 1994

Steve JobsApple Founder & CEO (on leave), in 1994 Rolling Stone interview

Source: Rolling Stone Magzine.

Mobile is the single biggest global distribution platform.

PC Installed Base TV Households Mobile Subscribers

PC TV Mobile

20091.2 Billion

20091.3 Billion

20094.0 Billion

13

BroadbandSubscribers

Pay TVSubscribers

20131.6 Billion

2009420 Million

2013648 Million

20131.33 Billion

2009600 Million

2013739 Million

4.0 Billion

20135.5 Billion

Source: Gartner, PWC, ITU, IDC, Accenture analysis.

Evolution of “the stack”: Shift from hardware to software.

Phone

ApplicationMiddleware

Middleware

Shell & UIUser Interfaces, App Stores &

User Software

External Interfaces,

e.g. US

B, S

peaker, Flash C

ard

CommsSoftware

Early days Today

Mobile Device Stack

14

Chipsets,Processors, Basebands

Core Operating System

PhoneMiddleware

Hardware

Platform / OS

Middleware

External Interfaces,

e.g. US

B, S

peaker, Flash C

ard

Hardware

1-2 MB of closed software

>1 GB of open software

Hardware Software

Source: Accenture analysis.

Value in mobile is moving up the stack…

Services and Content

Screen, User Interfaces,User Software

e.g

. US

B, S

peaker, F

lash

Card

Cost to build ($M)

Per-unit Revenue ($)

Break-even # of units

$0.1M $1.00 0.1M

$20M $0.20 100M

Mobile Handset Stack & Elements

DIRECTIONAL

15

Chipsets, Processors, Radio Basebands

Core Operating System

DeviceMiddleware

ApplicationMiddleware

Exte

rnal In

terfa

ces,

e.g

. US

B, S

peaker, F

lash

Card

$10M $0.10 100M

$1,000M $5.00 200M

Valu

e F

low

Hardware Software

Source: Estimates based on industry interviews; see David Wheeler “Linux Kernel 2.6: It's Worth More!” for estimating the cost of the Linux Kernel.

… and is fueling the app store economy.

149,000

211,000

2008 2009 2010

Size of Catalog (K) – Apple App Store vs. Android Market2008-2010, as of Q2 2010, by Number of Available Apps at End of Quarter, Excluding Books

Android

~20,000 monthly submission

16

740 4,40013,200

25,300

52,610

74,500

97,000

600 2,900 5,200 11,500

20,100

35,200

56,200

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

App StoreJuly 11

Android MarketOct 22

Day 1 500 Apps

Day 1 62 Apps

~7,000 monthly submission

Source: Apple press releases & earnings calls, Google, AndroLib, PCWorld, Distimo, Accenture analysis. Catalog size for Apples excludes books. All numbers rounded.

But: An app is not a business model.

60%

70%

80%

90%

100%

60%

70%

80%

90%

100%

60%

70%

80%

90%

100%

Ret

entio

n R

ate

60%

70%

80%

90%

100%

Loyalty and Retention Rates of Mobile Apps Over Time, 2010

17

0%

10%

20%

30%

40%

50%

60%

0 30 60 90 120 150 180

0%

10%

20%

30%

40%

50%

60%

0 30 60 90 120 150 1800%

10%

20%

30%

40%

50%

60%

0 30 60 90 120 150 180Days After First Measurement

Ret

entio

n R

ate

News (9.1%)

Games (2.4%)0%

10%

20%

30%

40%

50%

60%

0 30 60 90 120 150 180

News (9.8%)Enter-tainment (2%)

Days After First Measurement

Source: Flurry, Accenture analysis. User retention defined by the number of users who downloaded an application and launched the application at any time in the past, and also launched the app within the last seven days, e.g. "30 days ago" represents any new user that launched a given app in January and also again within the last seven days. "60 days ago" represents new users identified in December and also used within last 7 days. Sample based on relevant 5-6 apps per category with at least 120 days of data availability in the Flurry system.

90% dead after 90 days.

52%

40%

20%

9%

58%

38%

18%

5%

iPhone App RetentionAs of January 2010, by Application Category

30 Days 90 Days

Android App RetentionAs of January 2010, by Application Category

News

Social Networking

30 Days 90 Days

18

34%

35%

33%

10%

9%

4%

34%

38%

42%

10%

7%

16%

Games

Lifestyle

Enter-tainment

39% 10% 42% 11%Average

Retention Rates

Source: Flurry, Accenture analysis.

Expect the center of gravity to shift to post-load.

Post-Load Revenue Streams

Pre-Load Revenue Streams

100%

ILLUSTRATIVE

Ecosystem Revenue Mix Over Time.

19

Primary Revenue Models

• Licensing• Software sales• Hardware sales• Service subscriptions

• Licensing• Ads• Software sales• Hardware sales• Service subscriptions

• Social• Ads• Service subscriptions• Transaction fees• Privacy (User data)

0%

“Yesterday”2000

“Today”2010

“Tomorrow”2015 Onwards

Silicon

20

The one “law” that drives Silicon Valley.

21

Gordon E. MoreCo-founder Intel

Source: Intel.

Moore’s Law – since ~1965 on the desktop.

22 Source: Intel.

Coming your way in mobile as well.

Baseband Processors

“Fat Modems” Baseband & Application Processor

23

Low power silicon for voice/SMS and long

battery life.

OS-enablement of light apps running on top

of baseband.

High performance, low power application

processors.

One company at the core of the mobile revolution.

24

Massive on-deck computing power.

2GHz

2.5GHz

Cortex-A9

Cortex-A15

20nm

2 cores

4 cores

Mobile Silicon: Process Node, Cores & Clock Speed Over Time

25

533MHz667MHz

800MHz833MHz1GHz

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

ARM9

ARM11

Cortex-A8

Cortex-A9

130nm90nm

65nm45nm

32nm

28nm

20nm

Clockspeed:

Cores:

Node:

1 core

1 core

1 core

Source: ARM.

The latest mystery: Apple’s A4 (and A5, A6, etc.).

26

The ARM Architecture – at the core of Apple’s chips.

2007 2008 2009 2010 2011e 2012e

iPxx & TV iPxx & TV

ARM Family ARM11 ARM11 Cortex-A8 Cortex-A8 Cortex-A9 Apple Custom

DMIPs/MHz 1.2 1.2 2.0 2.0 2.5 2.5

x x x x x x

Clock speed 400MHz 412MHz 600MHz 1GHz 1.2GHz 2.0GHz

Apple SoC Processing Speeds for Single Core, 2007 – 2012based on DMIPs & Clock Speed

27

+3% +142% +67% +63% +54%

480 495 1,200 2,000 3,250 5,000DMIPs

+942%

Clock speed 400MHz 412MHz 600MHz 1GHz 1.2GHz 2.0GHz

= = = = = =

Increase in processing

speed

Source: ARM, iSuppli, PDAdb.net, Accenture analysis.

Google’s Android: One OEM and SemiCo at a time.

DSept 2009Donutv1.6

EOct

2009Éclair v2.0

FMay 2010 FroYo v2.2

CApril2009

Cupcakev1.5

GDec2010GiBrv2.3

HH1

2011HoCov3.0

Android Release

Feature

28

Chip

Qualcomm MSM7201A 528MHz

QualcommQSD8250998MHz

Samsung-IntrinsityS5PC1101000MHz

NVIDIATegra 2 250, 1000MHz

TIOMAP 3430600 MHz

Qualcomm MSM7201A 528MHz

HTCDream

SamsungBehold II

MotorolaDroid

HTCNexus One

SamsungNexus II

MotorolaXoom

Feature Device

Cloud

29

The cloud: Massive off-deck computing power.

”In addition to making raw computer

power available in a convenient

economical form, a computer utility

would be concerned with almost any

service or function which could in

30

service or function which could in

some way be related to the

processing, storage, collection and

distribution of information.”

Douglas Parkhill, 1966

Douglas Parkhill“The Challenge of the Computer Utility”, 1966

What is “The Cloud”?

Cloud Origins Cloud Today Cloud Benefits

• Cost ReductionLower infrastructure, energy, licensing and maintenance costs

• Speed to Market

VirtualizationOne computer

acting like

many

• Virtualization and

Grid abstracted

• Computing as a

A style of computing that provides on demand access to a shared set of highly scalable services.

31

• Speed to MarketReduces time requiredto pilot projects

• Elasticity / ScalabilityOn-demand capacity and high business agility

• High Performance ComputingProvides “infinite” computingcapacity as needed

many

Grid Computing

Many

computers

acting like one

+• Computing as a

utility

• Scale economies

of central supply

• Uses massively-

parallel processing

• Geo-distributed

with massive

redundancy

Who is building a cloud?

Facebook – Prineville Google – The DallesYahoo – Lockport

32

Apple – Maiden Microsoft – DublinAmazon – Morrow

Stuff you can do with the cloud.

65 Million Users Gaming Daily

100 Billion Searches Per Month

33

25 Billion Tweets in 2010

1.2 Million Photos Viewed Per Second

Stuff you can do with the cloud and your phone.

34

What’s Next

35

Jevon’s Paradox

” It is a confusion of ideas to suppose

that the economical use of fuel is

equivalent to diminished consumption.

36

William S. JevonsFrom the Book “The Coal Question”

The very contrary is the truth."

William S. Jevons, 1865

Silicon: Order of magnitude jump in processing power.

ARM Family ARM11 Cortex

Shipment Date 2007 2009 2010 2012

Chip ARM1136 Cortex-A8 Cortex-A9 Cortex-A15

DMIPs/MHz 1.2 2.0 2.5 2.5

x x x x

Clock Speed 600MHz 1GHz 2GHz 2.5GHz

= = = =

DMIPs/Core 720 2,000 5,000 6,250

“Typical” Moore’s Law behavior for single core processors

HIGHLY SIMPLIFIED

37

Cores/Cluster 1 1 2 4

x x x x

Clusters 1 1 1 4

= = = =

Total Cores 1 1 2 16

Total DMIPS 720 2000 10,000 100,000

~9xProcessing

Speed Increase

Processing Speed Increase

~138x

Doubles on average every ~21 months

Theoretical max computing power increased through multi-core and clustering

Source: Calculations based on ARM marketing material.

Cloud: 107 = 10M machines, roughly 10x of today.

38 Source: Google.

Industrialization of the mobile cloud...

Today

HTTP(custom libraries)

Cloud Device

39

Tomorrow

SDKs

… will bring massive off-deck computing to mobile.

40 Source: Amazon press release, December 2010.

Plenty of cash.

Cash on Hand for Select Tech Titans Cash and Cash Equivalents, as of 1/26/2011

44

39

35

27

41

27

29

22

11

10

7

6

Total of 226B

105

104

U.S. Asset Prices, 1945 - 2008Normalized, 1995 = 100

As computing gets cheaper…

Nor

mal

ized

Pric

e: 1

995

= 1

00(lo

g)

Computers and Peripheral Equipment

42

1950 1960 1970 1980 1990 2000

103

102

10

Source: The Business Impact of IT, based on U.S. Bureau of Economic Analysis data.

Industrial Equipment

Nor

mal

ized

Pric

e: 1

995

= 1

00

Other Equipment

Transportation Equipment

… companies consume more of it.

U.S. IT Investment, 1970 - 2008Nominal Annual Investment & Investment per Employee

3,500 350B

250B

3,000

2,500

300B

43

1970 1975 1980 2000 2005 2010199519901985

200B

150B

100B

50B

2,000

1,500

1,000

500

0 0

Source: The Business Impact of IT, based on U.S. Bureau of Economic Analysis data.

IT Investment / Employee

Annual Investment

Think again…

”People tend to overestimate

what can be done in one year

and to underestimate what can

44

J. C. R. Licklider“Grandfather of the Internet”

be done in five to ten years.”

J. C. R. Licklider, 1965

45