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Networks and the Nature of the Firm

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My keynote at the Open Exchange Summit in Nashville on April 18, 2018. I talk about the implications for many different kinds of companies of the fact that increasingly large segments of our economy are being dominated by algorithmically managed network marketplaces.

Published in: Technology
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Networks and the Nature of the Firm

  1. Networks and the Nature of the Firm Tim O’Reilly @timoreilly oreilly.com wtfeconomy.com
  2. How is work changing? What does technology now make possible that was previously impossible? What work needs doing? How do we make the world prosperous for all? Why aren’t we doing it? wtfeconomy.com
  3. We have to let go of the maps that are steering us wrong In 1625, we thought California was an island
  4. In 2018, it’s our map of the economy that is wrong
  5. The invisible hand at work
  6. What happens when there’s only one queue?
  7. And what happens when there’s only one price for everything?
  8. Gradually, then suddenly Large segments of the economy are governed not by free markets but by centrally managed platforms
  9. Gradually, then suddenly Artificial Intelligence and algorithmic systems are everywhere, in new kinds of partnerships with humans
  10. We are all living and working inside a machine
  11. Networks and the Nature of the Firm “The existence of high transaction costs outside firms led to the emergence of the firm as we know it, and management as we know it….The reverse side of Coase’s argument is as important: If the (transaction) costs of exchanging value in the society at large go down drastically as is happening today [because of networks], the form and logic of economic and organizational entities necessarily need to change! The mainstream firm, as we have known it, becomes the more expensive alternative.”Esko Kilpi
  12. If we want to understand the future of business and the economy, we have to understand networked platforms
  13. “A business model is the way that all of the parts of a business work together to create competitive advantage and customer value.” - Dan and Meredith Beam
  14. Who Do You Want Your Customers to Become? Henry Ford didn’t just rethink the automobile and the factory, he rethought the work week, and the reasons why people might want to drive.
  15. A Business Model Map of Uber  A magical app that lets drivers and passengers find each other in real time  A networked marketplace of drivers and passengers  Customers who trust that they don’t have to drive their own car  Augmented workers able to join the market as and when they wish  A matching market managed by algorithm
  16. What makes an app “magical”? 1. It seems unbelievable at first. 2. It changes the way the world works, so that the unbelievable comes to seem inevitable and normal. 3. It results in an ecosystem of new services, jobs, business models, and industries.
  17. Why simply adding an app doesn’t change the game for taxis
  18. The Augmented Worker Neo: “Can you fly that thing?” Trinity: “Not yet.”
  19. This isn’t quite what Trinity’s got, but…
  20. “The Uber app is the drivers’ workplace, as much as the city where they’re driving is. Each decision about its interface structures drivers’ interactions with Uber the company as well as Uber the transportation marketplace. And Uber is now putting the finishing touches on a from-scratch rebuild of the driver app.” Alexis Madrigal, The Atlantic, “Uber Drivers are About to Get a New Boss”
  21. The algorithms decide “who gets what – and why” Markets are outcomes. A better designed marketplace can have better outcomes.
  22. The great opportunity of the 21st century is to use our newfound cognitive tools to build better marketplaces
  23. A language for networked marketplaces Network effect: the value of a network is proportional to the square of the number of possible connections Scale effect: bigger is better (but not always) Feedback effect: the more data you collect from the marketplace, the more you can learn, and the better the services you can provide Two-sided market: different classes of users being matched up: searchers and advertisers, drivers and passengers, homes and renters.
  24. Asymptotic Networks “The reason Lyft is able to compete with Uber is that even if they have fewer drivers in many cities, both platforms are still able to guarantee a ride with an average wait time of 4 minutes. Neither can improve by adding more drivers to a city.” James Currier
  25. Market Networks In a market network, you’re not connecting a simple marketplace of buyers and sellers, but also connecting them with intermediaries and service providers. A Market Network combines elements of a professional network, an online marketplace, and SaaS tools.
  26. “We wouldn’t be able to build defensibility from our supply- side relationships purely on the basis of a Marketplace Network Effect, because it was in the interests of the real estate agents to syndicate their listings through every possible channel…. So we created an XML feed standard … This prevented brokers from having to go through the hassle of posting them manually to every channel, and soon our competitors had adopted the same XML standards for their sites as well.” And, after 2009, when the real estate market collapsed, ”to scale [a] new monetization strategy targeting smaller customers, we set to work creating cost-effective marketing and lead generation products for the individual real estate agents.” Pete Flint
  27. “Once they get some traction, platforms survive either because:  They achieve critical mass in a market with network effects. They are the default place to go—this is why Craigslist, Airbnb, ebay, Etsy, and other places with most of the inventory thrive.  They provide a tool set ecosystem. The product or service has certain functions that buyer and seller need (escrow, analytics, a CRM, etc.) that the marketplace can provide with an economy of scale that beats everyone doing it themselves.” Alistair Croll
  28. OX provides tools for market networks Communication and productivity tools for SMBs Cloud storage and collaboration tools to upgrade hosting capabilities Dynamic upgrades and improved security in email
  29. “A Network of Networks” 41
  30. Create more value than you capture
  31. The Clothesline Paradox If you put your clothes in the dryer, the energy you use is measured and counted, but if you hang them on the clothesline to be dried by the sun, the energy saved disappears from our accounting
  32. WordPress
  33. ISP Services - a $100 Billion market in the US alone Web hosting and domain name registration - a $5 Billion market
  34.  Web design  SEO  New media businesses
  35. Having a web site increases the productivity of small businesses by 10%
  36. So that’s where the value gets captured - by everyone!
  37. Why platforms (and economies) fail wtfeconomy.com
  38. Growth goes on forever?
  39. Fitness Landscapes The way in which genes contribute to the survival of an organism can be viewed as a landscape of peaks and valleys. Through a series of experiments, organisms evolve towards fitness peaks, adapted to a particular environment, or they die out. Image source: http://evolution.berkeley.edu/evolibrary/article/side_0_0/complexnovelties_02
  40. Technology also has a fitness landscape In my career, I’ve watched a number of migrations to new peaks, and I’d like to share with you some observations about what happened, and why. And then we’ll talk about some lessons for companies like Google, but also for the overall economy. Apple Personal Computer Big Data and AI Smartphones
  41. The Rules for Success Change  IBM fitness function: Maximize competitive advantage by control over hardware  Microsoft fitness function: Maximize competitive advantage by control over software  Google fitness function: Maximize competitive advantage by control over data and marketplaces  Apple fitness function: Maximize competitive advantage by integrated control of hardware, software, and marketplace.  In each case, companies playing by the old rules lost. Or did they?
  42. Generosity takes us to the next peak Tim Berners-Lee, 1990 The World Wide Web Linus Torvalds, 1991 Linux Big Data and AI Tim Berners-Lee, 1990 The World Wide Web Linus Torvalds, 1991 Linux
  43. How Technologies Mature 1. Some new technology (the PC, the web, the smartphone) lowers the barriers to participation and innovation. 2. The market explodes as “hackers” push the envelope of possibility, and entrepreneurs make things easier for ordinary users. 3. The market stagnates as players become platforms, and raise barriers to entry. Hackers and entrepreneurs move on, looking for new frontiers. Or (rarely) 3. The industry builds a healthy ecosystem, in which hackers, entrepreneurs and platform companies play a creative game of "leapfrog". No one gets complete lock in, and everyone has to improve in order to stay competitive. Value is created for an entire ecosystem.
  44. Generous or “Long-term greedy”?
  45. Google’s share of ad revenue over time O’Reilly Research
  46. O’Reilly Media ● Providing learning for almost 40 years ● Trends called – Open Source, Web 2.0, Maker Movement, Big Data ● 500 employees, thousands of contributors ● 5,000+ enterprise clients, 2.3m platform users globally ● 17 global technology events serving 20k individuals and 1,000 sponsor companies
  47. Change the world by spreading the knowledge of innovators
  48. O’Reilly’s Platform-Centered Learning Ecosystem Safari (learning platform) Conferences/ Foo Camps Live Training Books Video Jupyter Notebooks Expert Network Materials for reference and learning Immersive learning experiences with industry experts Cutting edge idea forums Digital platform for on-demand learning across modalities. Books, video, synchronous and asynchronous online learning Our ecosystem matches thousands of learning providers with millions of customers
  49. “Doing digital is not the same as being digital.” Josh Bersin Deloitte
  50. How is this possible? McDonalds 440,000 employees, 68 million monthly users Snap ~300 employees, 100 million monthly users
  51. “My grandfather wouldn’t recognize what I do as work.” – Hal Varian
  52. Many of today’s workers are programs. Developers are actually their managers. Every day, they are inspecting the performance of their workers and giving them instruction (in the form of code) about how to do a better job
  53. The lessons of technology are also lessons for the organization of the business “Services not only represent a software structure but also the organizational structure.” Werner Vogels, Amazon CTO
  54. How Amazon Became a Platform “[Jeff’s] Big Mandate went something along these lines: 1) All teams will henceforth expose their data and functionality through service interfaces. 2) Teams must communicate with each other through these interfaces. 3) There will be no other form of interprocess communication allowed: no direct linking, no direct reads of another team’s data store, no shared-memory model, no back-doors whatsoever. The only communication allowed is via service interface calls over the network. 4) It doesn’t matter what technology they use. HTTP, Corba, Pubsub, custom protocols — doesn’t matter. Bezos doesn’t care. 5) All service interfaces, without exception, must be designed from the ground up to be externalizable. That is to say, the team must plan and design to be able to expose the interface to developers in the outside world. No exceptions. 6) Anyone who doesn’t do this will be fired.” Steve Yegge, in http://siliconangle.com/furrier/2011/10/12/google-engineer-accidently- shares-his-internal-memo-about-google-platform/
  55. Two-pizza teams
  56. Algorithmic systems have an “objective function” Google: Relevance Facebook: Engagement Uber and Lyft: Passenger pick up time Scheduling software used by McDonald’s, The Gap, or Walmart: Reduce employee costs and benefits
  57. What are you asking your algorithms to optimize for?
  58. When platforms get their algorithms wrong, there can be serious consequences!
  59. The runaway objective function “Even robots with a seemingly benign task could indifferently harm us. ‘Let’s say you create a self- improving A.I. to pick strawberries,’ Musk said, ‘and it gets better and better at picking strawberries and picks more and more and it is self- improving, so all it really wants to do is pick strawberries. So then it would have all the world be strawberry fields. Strawberry fields forever.’ No room for human beings.” Elon Musk, quoted in Vanity Fair https://www.vanityfair.com/news/2017/03/elon-musk- billion-dollar-crusade-to-stop-ai-space-x
  60. Will there really be nothing left for people to do? Is there really nothing left for humans to do?
  61. The Equinix NY4 data center, where trillions of dollars change hands
  62. What is the objective function of our financial markets? “The Social Responsibility of Business Is to Increase Its Profits” Milton Friedman, 1970
  63. Divergence of productivity and real median family income in the US
  64. “The art of debugging is figuring out what you really told your program to do rather than what you thought you told it to do.” Andrew Singer
  65. Oikonomia vs Chrematistike
  66. Can we use algorithmic systems and modern tools for matching people to work that needs doing to build a better economy for all? wtfeconomy.com
  67. “Doughnut Economics” Kate Raworth
  68. “Computational Sustainability is a new interdisciplinary research field, with the overarching goal of studying and providing solutions to computational problems for balancing environmental, economic, and societal needs for a sustainable future. Such problems are unique in scale, impact, complexity, and richness, often involving combinatorial decisions, in highly dynamic and uncertain environments, offering challenges but also opportunities for the advancement of the state-of-the-art of computer and information science. Work in Computational Sustainability integrates in a unique way various areas within computer science and applied mathematics, such as constraint reasoning, optimization, machine learning, and dynamical systems.” Carla Gomes
  69. The fundamental economic question is no longer how to incentivize production but how to incentivize fair distribution of the fruits of increased productivity Brian Arthur
  70. “Economic Possibilities for Our Grandchildren” The world of his grandchildren—the world of those of us living today— would, “for the first time . . . be faced with [mankind’s] real, his permanent problem—how to use his freedom from pressing economic cares, how to occupy the leisure, which science and compound interest will have won for him, to live wisely and agreeably and well.” John Maynard Keynes John Maynard Keynes
  71. There’s plenty to go around. It’s just not going around!
  72. It isn’t technology that wants to eliminate jobs “Prosperity in human societies is best understood as the accumulation of solutions to human problems. We won’t run out of work until we run out of problems.” Nick Hanauer
  73. Let’s use the power of networked platforms, and new kinds of partnership with machines, to build the world we actually want to live in
  74. wtfeconomy.com WTF??!! Amazement or Dismay
  75. Tim O’Reilly @timoreilly • O’Reilly AI Conference • Strata: The Business of Data • JupyterCon • O’Reilly Open Source Summit • Maker Faire • Foo Camp • … • 40,000+ ebooks • Tens of thousands of hours of video training • Live training • Millions of customers • A platform for knowledge exchange • Commercial internet • Open source software • Web 2.0 • Maker movement • Government as a platform • AI and The Next Economy Founder & CEO, O’Reilly Media Partner, O’Reilly AlphaTech Ventures Board member, Code for America Co-founder, Maker Media

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