Capturing Value from The Next 10 Billion Devices
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The document discusses the transition of the mobile and social computing landscape towards a new era defined by the Internet of Things (IoT) and emerging business models. It highlights the evolution of technology, particularly personal computers and mobile devices, and emphasizes the importance of scaling, innovation, and efficiency in manufacturing, facilitated by advancements like 3D printing and cognitive computing. The document posits that harnessing distributed computing power will be crucial for managing the increasing complexity of interconnected devices and shaping future market dynamics.
Capturing Value from The Next 10 Billion Devices
- 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