capturing value from the next 10 billion devices
DESCRIPTION
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.TRANSCRIPT
Capturing Value From The Next 10 Billion DevicesPaul R Brody Vice President & Global Industry Leader, Electronics
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
Page 4
You can see the computer age everywhere but in the productivity statistics.
Robert Solow, 1987
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 400/800Atari ST C 64 TRS-80 NeXT PETOther
PC Platform Volumes, 1980-‐1990 jeremyreimer.com
0%
1%
1%
2%
3%
1970s 1980s 1990s
GPD Per Capita Growth, G7 OECD
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 IIAtari ST Other
PC Platform Market Share, 1980-‐1990 jeremyreimer.com
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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”
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 PCApple IIMacintoshAll OthersPC Platform
Volumes, 1975-‐2010 jeremyreimer.com
PC “Wins”
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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
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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
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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 WindowsPalm BlackberryAndroid iPhoneLinux Others
Smartphone Platform Market Share & Shipments, 2000-‐2012 jeremyreimer.com
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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 WinMobilePalmOS BlackberryAndroid iPhoneLinux Others
Smartphone Platform Market Share & Shipments, 2000-‐2012 jeremyreimer.com
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Social networks are also consolidating into a small group of very big players
June 2009
Image cc From Vincenzo Cosenza, vincos.it
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Social networks are also consolidating into a small group of very big players
December 2013
Image cc From Vincenzo Cosenza, vincos.it
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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
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
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
Page 18
Those who cannot remember the past are condemned to repeat it.
George Santayana, 1906
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 CitiesSmart Infrastructure
Connected Home
Medical Wearables
Smart Watches
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 ComputingDistributed 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.
Page 21
Software Defined Supply Chain
Analytics & Cognitive ComputingDistributed 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.
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 GO P E N S O U R C EINTELLIGENT ROBOTICS
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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.
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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
1725
100
3
29
100
1724
100
2
24
100
AGGREGATE NORMALIZED!MINIMUM ECONOMIC SCALE
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
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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
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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.
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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
Page 29
Software Defined Supply Chain
Analytics & Cognitive ComputingDistributed 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.
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?
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
Page 32
Software Defined Supply Chain
Analytics & Cognitive ComputingDistributed 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.
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
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
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:
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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
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…
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
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 ServicesStandard 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 ServicesLog 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 TrendStandard Scale!As of April 2014
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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 ComputingDistributed Computing
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
Page 42
The future is already here. It’s just not very evenly distributed.
William Gibson
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
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
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
Page 46
Technology companies are creating the devices necessary to instrument, use and pay for services and asset usage
DISCOVER
USE
PAY
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
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:
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%
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
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
Page 52
He who has the gold, makes the rules.
Unknown
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
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.
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 IntensiveNon-‐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%
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
Page 57
When it comes to transforming our economy, we’ve only just gotten started
48% 50%
2%
IT ProducingIT IntensiveNon-‐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
Paul R BrodyLinkedIn.com/In/PBrody
@pbrody
Twitter & Weibo: @pbrody