What can we learn from the last major diffusions of technology into our society (mobile & PC) and how will that apply to the Internet of Things? What strategies & business models should we consider to build sustainably profitable solutions.

2. Capturing Value From The
Next 10 Billion Devices
Paul R Brody
Vice President & Global Industry Leader, Electronics

3. Page 3
Our Discussion Today
Entering
A
New
Era
In
Mobile
&
Social
Computing
The
Next
Battleground:
Distributed,
Autonomous
Internet
of
Things
The
Shape
of
Business
Models
To
Come
Writing
The
Rules
of
The
Next
Marketplace

4. Page 4
You
can
see
the
computer
age
everywhere
but
in
the
productivity
statistics.
Robert
Solow,
1987

5. Page 5
Computers
spread
through
enterprises
throughout
the
1970s
and
1980s
even
as
productivity
growth
stalled
0
5,625
11,250
16,875
22,500
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
IBM PC Apple II Macintosh Amiga Atari 400/800
Atari ST C 64 TRS-80 NeXT PET
Other
PC
Platform
Volumes,
1980-­‐1990
jeremyreimer.com
0%
1%
1%
2%
3%
1970s 1980s 1990s
GPD
Per
Capita
Growth,
G7
OECD

6. Page 6
The
1980s
saw
intense
battles
to
define
the
shape
of
the
computing
world
as
multiple
Personal
Computer
ecosystems
battled
for
market
supremacy
0%
25%
50%
75%
100%
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
Mac Amiga PC C64 Apple II
Atari ST Other
PC
Platform
Market
Share,
1980-­‐1990
jeremyreimer.com

7. Page 7
Though
personal
computers
seemed
to
be
everywhere,
the
reality
is
that
we
had
only
just
started
to
really
consume
computing
power
PC
Platform
Volumes,
1975-­‐2010
jeremyreimer.com
PC
“Wins”

8. Page 8
The
reality
is
that
only
after
standards
had
been
established
and
scale
achieved
did
volumes
really
start
to
expand
enormously
0
100,000
200,000
300,000
400,000
1975 1979 1983 1987 1991 1995 1999 2003 2007
IBM PC
Apple II
Macintosh
All OthersPC
Platform
Volumes,
1975-­‐2010
jeremyreimer.com
PC
“Wins”

9. Page 9
It
was
only
then
that
economists
could
start
to
see
a
significant
increase
in
productivity
growth
from
the
rapid
expansion
of
the
personal
computer
US
Productivity
Growth,
1960-­‐2007
Total
Factor
Productivity,
Average
Annual
Percentage
!
Information
Technology
&
US
Productivity
Growth,
Jorgenson,
Ho,
&
Samuels
-­‐0.1%
0%
0.1%
0.2%
0.3%
0.4%
1960-­‐2007 2000-­‐2007
IT
Producing IT
Intensive Non-­‐IT
Intensive

10. Page 10
In
the
PC
industry,
the
market
development
era
had
to
be
completed
before
we
could
see
the
value
of
scale
and
productivity
Perfect
The
Product
Build
The
Ecosystem
Establish
Control
Points
Market
Development
Era
IBM
PC
5150
Cut
Costs
&
Grow
Scale
Focus
on
Value
Creation
Refine
User
Experience
Scale
&
Productivity
Era
Dell
scaled
up
PC
business
with
Build
To
Order

11. Page 11
The
mobile
industry
today
is
where
the
PC
industry
was
in
1990:
just
out
of
the
first
battles
for
market-­‐share
and
into
the
period
of
scaling
up
0%
25%
50%
75%
100%
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Symbian Windows
Palm Blackberry
Android iPhone
Linux Others
Smartphone
Platform
Market
Share
&
Shipments,
2000-­‐2012
jeremyreimer.com

12. Page 12
The
mobile
industry
today
is
where
the
PC
industry
was
in
1990:
just
out
of
the
first
battles
for
market-­‐share
and
into
the
period
of
scaling
up
0
150
300
450
600
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Symbian WinMobile
PalmOS Blackberry
Android iPhone
Linux Others
Smartphone
Platform
Market
Share
&
Shipments,
2000-­‐2012
jeremyreimer.com

13. Page 13
Social
networks
are
also
consolidating
into
a
small
group
of
very
big
players
June
2009
Image
cc
From
Vincenzo
Cosenza,
vincos.it

14. Page 14
Social
networks
are
also
consolidating
into
a
small
group
of
very
big
players
December
2013
Image
cc
From
Vincenzo
Cosenza,
vincos.it

15. Page 15
Though
the
volumes
may
seem
large,
only
about
20%
of
the
world
population
have
mobile
phones
or
are
connected
through
social
networks.
We’re
just
getting
started.
Perfect
The
Product
Build
The
Ecosystem
Establish
Control
Points
Market
Development
Era
The
T-­‐Mobile
G1:
First
Android
Phone
Cut
Costs
&
Grow
Scale
Focus
on
Value
Creation
Refine
User
Experience
Scale
&
Productivity
Era
The
Smartisan
T1
Android
Phone

16. Page 16
For
industry
participants,
the
implications
are
clear
as
well:
time
to
shift
your
approach
from
designing
business
models
and
ecosystems
to
enabling
productivity
Development
Era Scaling
Era
• Attempted
social
network
-­‐
Ping
• Added
new
services
like
books,
music,
video
and
apps
• Product
line
extensions
• Shift
towards
fashion
and
marketing
• Attempted
extensions
with
Smart
TV
apps,
music
store
&
movie
store
• Flood
market
with
offerings
• Close
non-­‐performing
areas
• Simplify
product
line
• Use
scale
to
drive
out
cost
• Consulting
offerings
• Customized
solutions
• Research-­‐led
engagements
• High
volume
product
offerings
• $7
billion
in
scaling
investment
• Product-­‐led
engagements
with
clients

17. Page 17
Our Discussion Today
Entering
A
New
Era
In
Mobile
&
Social
Computing
The
Next
Battleground:
Distributed,
Autonomous
Internet
of
Things
The
Shape
of
Business
Models
To
Come
Writing
The
Rules
of
The
Next
Marketplace

18. Page 18
Those
who
cannot
remember
the
past
are
condemned
to
repeat
it.
George
Santayana,
1906

19. Page 19
Even
as
social
&
mobile
enter
the
era
of
scale,
we
are
still
trying
to
define
the
universe
of
options
and
capabilities
in
the
Internet
of
Things
era
Smart
Cities
Smart
Infrastructure
Connected
Home
Medical
Wearables
Smart
Watches

20. Page 20
However
the
market
evolves,
it
will
likely
be
shaped
by
a
set
of
technologies
now
emerging
and
converging
with
each
other
Software
Defined
Supply
Chain
Analytics
&
Cognitive
Computing
Distributed
Computing
How
to
manufacture
billions
of
smart
devices
easily
and
effectively
in
small
quantities
and
in
a
highly
customized
way.
How
to
turn
data
into
useful
insight
and,
from
there,
into
recommendations
for
action.
Computing
power
will
be
everywhere.
We
must
find
a
way
to
harness
it
to
keep
the
cost
and
complexity
of
managing
the
IOT
feasible.

21. Page 21
Software
Defined
Supply
Chain
Analytics
&
Cognitive
Computing
Distributed
Computing
How
to
manufacture
billions
of
smart
devices
easily
and
effectively
in
small
quantities
and
in
a
highly
customized
way.
How
to
turn
data
into
useful
insight
and,
from
there,
into
recommendations
for
action.
Computing
power
will
be
everywhere.
We
must
find
a
way
to
harness
it
to
keep
the
cost
and
complexity
of
managing
the
IOT
feasible.

22. Page 22
The
combination
of
3D
printing
with
related
digital
manufacturing
technologies
is
reshaping
the
global
supply
chain
3 D P R I N T I N G
O P E N S O U R C EINTELLIGENT ROBOTICS

23. Page 23
3D
printing
(aka
Additive
Manufacturing)
is
the
most
critical
of
these
new
technologies
$0.00
$0.08
$0.15
$0.23
$0.30
2013 2018 2023
COST PER UNIT VOLUME PRINTED!
$/CUBIC CM - BLENDED AVERAGE
-79%
-92%
Over the next 10 years, 3D
printing will become 92%
cheaper than today.
This technology will shift from
being a tool for prototyping to
one of mass manufacturing.

24. Page 24
Using
these
new
manufacturing
technologies,
the
required
scale
to
produce
a
product
efficiently
is
up
to
90%
lower
than
current
manufacturing
methodologies
90%
LESS VOLUME
REQUIRED
0
25
50
75
100
2012 Traditional 2017 Digital 2022 Digital
17
25
100
3
29
100
17
24
100
2
24
100
AGGREGATE NORMALIZED!
MINIMUM ECONOMIC SCALE

25. Page 25
The
net
result
is
a
much
more
flexible,
responsive
supply
chain
HARDWARE CONSTRAINED
BUILD A MOLD
OR CAST
HARDWIRE
PRODUCTION LINE
DEVELOP
EMBEDDED CHIP
SOFTWARE DEFINED
PRINT PARTS DIRECTLY
BY SOFTWARE
RECONFIGURE ASSEMBLY
THROUGH SOFTWARE
DIGITAL CONTROLS
USING SOFTWARE

26. Page 26
When
you
use
a
supply
chain
that
is
built
on
3D
printing,
the
results
are
dramatic
Software Defined Supply Chain - 2012Case Example:!
!
To manufacture
efficiently, you need
the scale that comes
from covering a
whole market in the
traditional model

27. Page 27
When
you
use
a
supply
chain
that
is
built
on
3D
printing,
the
results
are
dramatic
Software Defined Supply Chain - 2017Case Example:!
!
By 2017, 3D printing
and robotic assembly
make it simple and
easy enough to start
manufacturing
regionally.

28. Page 28
When
you
use
a
supply
chain
that
is
built
on
3D
printing,
the
results
are
dramatic
Software Defined Supply Chain - 2022Case Example:!
!
By 2022, we forecast
that most mew
manufacturing
capacity will be
shifting back towards
a localized model

29. Page 29
Software
Defined
Supply
Chain
Analytics
&
Cognitive
Computing
Distributed
Computing
How
to
manufacture
billions
of
smart
devices
easily
and
effectively
in
small
quantities
and
in
a
highly
customized
way.
How
to
turn
data
into
useful
insight
and,
from
there,
into
recommendations
for
action.
Computing
power
will
be
everywhere.
We
must
find
a
way
to
harness
it
to
keep
the
cost
and
complexity
of
managing
the
IOT
feasible.

30. Page 30
Cognitive
computing
will
allow
us
to
blend
unstructured
information
with
structured
data
Unstructured
data
like
medical
papers
give
guidelines:
Structured
data
from
systems
shows
an
individual
patient:
What
is
the
right
course
of
treatment?

31. Page 31
Without
cognitive
computing
-­‐
a
kind
of
electronic
common
sense
-­‐
we
will
be
overwhelmed
with
the
complexity
and
data
required
to
manage
smart
devices
Very
stylish
Not
nearly
smart
enough

32. Page 32
Software
Defined
Supply
Chain
Analytics
&
Cognitive
Computing
Distributed
Computing
How
to
manufacture
billions
of
smart
devices
easily
and
effectively
in
small
quantities
and
in
a
highly
customized
way.
How
to
turn
data
into
useful
insight
and,
from
there,
into
recommendations
for
action.
Computing
power
will
be
everywhere.
We
must
find
a
way
to
harness
it
to
keep
the
cost
and
complexity
of
managing
the
IOT
feasible.

33. Page 33
Thanks
to
Moore’s
law,
it
will
soon
be
cheaper
and
easier
to
put
a
fully
powered
system
on
chip
platform
into
even
the
simplest
systems
than
to
customize
an
embedded
chip
Full ARM SoC as powerful as many
cell phones with 2GB of RAM.
Boots when connected. Runs Mac
OS Core (XNU)
Receives MPEG stream and converts
it to HDMI output.
The
Apple
Lightning
to
HDMI
Connector
Source:
ExtremeTech.com
report
on
Apple
lightning
HDMI
connector
cable,
retrieved
March
2013

34. Page 34
Significant
recent
advances
in
the
software
of
distributed
computing
mean
that
we
may
soon
be
able
to
harness
and
use
that
computing
power
that
will
be
everywhere
Billions
of
Devices
Millions
of
Locations
Terabytes
of
storage
&
bandwidth
The
cloud
is
moving
out
of
your
data
center
and
into
your
doorknob.
Image
Flickr
Creative
Commons
License

35. Page 35
The
solution
to
harnessing
all
this
distributed
computing
power
is
now
visible:
BitCoin
Traditional banks are built on
private, centralized systems:
There is one central ledger for
accounts, identities, and transactions.
Account owners
Bank balances
Transaction records
New
Transactions
In Bitcoin, the central functions are distributed to all the
participants in the system:
Thanks to cheap computing power and clever process design, BitCoin
enables truly distributed transaction processing.
Every user has access to their own copy of the entire transaction ledger in
a long file called the BLOCK CHAIN:

36. Page 36
BitCoin
is
built
on
the
concept
of
distributed
consensus
-­‐
all
participants
can
see
all
the
transactions
and
many
participants
verify
the
work
of
each
transaction
Transactions are confirmed by
CONSENSUS
Multiple ecosystem participants
check on each transaction to
provide REDUNDANT
VERIFICATION
No single point of failure
No need to trust all the
participants

37. Page 37
Take
away
the
financial
component
of
BitCoin
and
you
have
a
powerful
decentralized
computing
system
that
can
be
used
for
all
kinds
of
systems
Take Bitcoin and remove the
financial component
You a have powerful distributed
transaction processing system
Account owners
Bank balances
Transaction records
Any transaction-
intensive processing
activity
Transaction processing engines are the foundation of
many key technology systems:
Travel Resrvations
Billing Systems
Health Records
Social Media
Device Data
Documents
Both old… And new…

38. Page 38
Case
Example:
GitChain
project
marries
distributed
computing
and
software
development
in
a
single
scalable
platform
GitHub: A Centralized S/W Development System GitChain: A Decentralized S/W Development System
•Same
basic
features
as
GitHub
•Better
local
performance
with
slow
networks
•Better
security
&
redundancy
•Check
In
/
Check
out
software
to
develop
•Share
and
copy
code
with
other
developers
•Build
a
social
network
through
professional
work

39. Page 39
Though
relatively
young
and
immature,
BitCoin
is
growing
a
rate
reminiscent
of
past
platforms
like
Facebook
and
Twitter
0
1,000,000,000
2,000,000,000
3,000,000,000
4,000,000,000
BitCoin NYSE Twitter Facebook
Transactions Per Day!
Various Online Services
Standard Scale!
As of April 2014
1
100
10,000
1,000,000
100,000,000
10,000,000,000
BitCoin NYSE Twitter Facebook
Transactions Per Day!
Various Online Services
Log Scale!
As of April 2014
0
22,500
45,000
67,500
90,000
2009
2010
2011
2012
2013
2014
BitCoin Transactions Per Day!
Overall Growth Trend
Standard Scale!
As of April 2014

40. Page 40
The
combination
of
these
technologies
will
allow
us
to
build,
scale
up,
and
manage
networks
of
billions
of
devices
Software
Defined
Supply
Chain
Analytics
&
Cognitive
Computing
Distributed
Computing

41. Page 41
Our Discussion Today
Entering
A
New
Era
In
Mobile
&
Social
Computing
The
Next
Battleground:
Distributed,
Autonomous
Internet
of
Things
The
Shape
of
Business
Models
To
Come
Writing
The
Rules
of
The
Next
Marketplace

42. Page 42
The
future
is
already
here.
It’s
just
not
very
evenly
distributed.
William
Gibson

43. Page 43
Our
research
suggests
too
many
companies
are
trying
to
build
a
smart-­‐phone
ecosystem
based
on
apps
and
subscriptions
and
that
may
not
be
realistic
No
Apps
No
Subscription
No
Problem

44. Page 44
The
web
made
digital
services
easy
to
search,
use,
and
purchase
DISCOVER
USE
PAY
Online
Payment
icon
(cc)
by
Slawek
Jurczyk
from
the
Noun
Project

45. Page 45
With
physical
beacons
and
connected
devices,
search
and
discovery,
usage,
and
payment
will
become
just
as
simple
in
real
life
as
online
DISCOVER
USE
PAY

46. Page 46
Technology
companies
are
creating
the
devices
necessary
to
instrument,
use
and
pay
for
services
and
asset
usage
DISCOVER
USE
PAY

47. Page 47
The
power
of
Internet
of
Things
will
be
to
increase
the
leverage
from
physical
assets
and
to
create
new,
digital
markets
for
physical
goods
and
services
Unlocking
Capacity
Creating New
Markets
Reducing
Risk
Improving
Efficiency
Creating
New Value

48. Page 48
Services
like
UBER
capture
unused
capacity
and
make
it
available
through
an
online
Drivers
and
customers
can
both
see
the
marketplace:
Analytics
tells
drivers
where
to
find
customers:
UBER
(and
similar
services)
are
using
data
to
bring
LIQUIDITY
to
markets:

49. Page 49
The
results
are
striking
in
terms
of
economic
value
created:
Sources:
Uber,
New
York
Taxi
&
Limousine
Commission,
Boston
Taxi
Commission,
UBER
fares
based
on
UberX
Today,
average
Taxi
utilization
is
relatively
low:
55%
UBER
fares
are
lower
than
regular
taxi
prices
-­‐18%
…but
Uber
drives
report
higher
incomes:
+22%

50. Page 50
The
speed
and
scale
with
which
Uber
has
grown
as
spawned
a
wave
of
investment:
The
number
of
new
digital
online
services
that
do
this
is
growing
enormously:
UBER
(and
similar
services)
are
using
data
to
bring
LIQUIDITY
to
markets:
Just
550
Employees
Estimated
$1bn
in
revenue
$10bn
Valuation

51. Page 51
Our Discussion Today
Entering
A
New
Era
In
Mobile
&
Social
Computing
The
Next
Battleground:
Distributed,
Autonomous
Internet
of
Things
The
Shape
of
Business
Models
To
Come
Writing
The
Rules
of
The
Next
Marketplace

52. Page 52
He
who
has
the
gold,
makes
the
rules.
Unknown

53. Page 53
If
we
want
to
see
some
real
battles,
we
should
take
a
look
at
the
fights
going
on
between
existing
industry
leaders
and
disruptive
attackers
using
the
Internet
of
Things
Car
Sharing
Apartment
Sharing
Recent
Regulatory
Battles
Over
Market
Disruption

54. Page 54
Despite
dominating
existing
industries,
incumbents
(so
far)
seem
to
be
losing
the
battle
against
market
disruptions
Products come and go.
Systems last longer.
Relationships endure.

55. Page 55
It’s
important
for
our
economic
growth
that
innovators
win
these
regulatory
battles
US
Productivity
Growth,
1960-­‐2007
Total
Factor
Productivity,
Average
Annual
Percentage
Information
Technology
&
US
Productivity
Growth,
Jorgenson,
Ho,
&
Samuels
-­‐0.075%
0%
0.075%
0.15%
0.225%
0.3%
1960-­‐2007
IT
Producing IT
Intensive
Non-­‐IT
Intensive
IT Intensive Industries IT Share of
CapEx
Securities contracts & investments 85%
Air transportation 68%
Professional Services 63%
Broadcasting and telecom 57%
Educational services 55%
Newspaper & book publishers 55%
Management of companies 54%
Administrative and support services 50%
Water transportation 48%
Machinery 34%
Federal General government 30%
Retail Trade 16%

56. Page 56
The
list
of
industries
that
have
yet
to
really
be
transformed
by
IT
and
to
leverage
IT
is
enormous,
and
it
is
the
biggest
area
of
opportunity
for
the
Internet
of
Things
Non-IT Intensive Industries IT Share of
CapEx
Farms 1%
Real estate 1%
Oil and gas extraction 3%
Accommodation 7%
Utilities 7%
Amusements and recreation 8%
Electrical equipment appliances 11%
Federal Government enterprises 11%
Ambulatory health care services 12%
Fabricated metal products 14%
Motion picture and sound recording 14%
Warehousing and storage 14%
Smart
Planting
Technology
RFID
wrist
bands
at
DisneyLand
3D
printed
solid
objects
Smart
containers
&
warehouses
Smart
hotel
rooms
&
door
locks
Electronic
Medical
Records

57. Page 57
When
it
comes
to
transforming
our
economy,
we’ve
only
just
gotten
started
48% 50%
2%
IT
Producing
IT
Intensive
Non-­‐IT
Intensive
44%
53%
3%
Economic
Share
IT
Producing,
Intensive
&
Non-­‐Intensive
Industries
!
Share
of
Total
Economic
Output,
Information
Technology
&
US
Productivity
Growth,
Jorgenson,
Ho,
&
Samuels
1960-­‐1995
Average 2000-­‐2007
Average

58. Paul R Brody
LinkedIn.com/In/PBrody
@pbrody
Twitter & Weibo: @pbrody