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.
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
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Networks and the Nature of the Firm
1. Networks and the Nature of the Firm
Tim OâReilly
@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 arenât 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
14. We are all living and working inside a machine
15.
16. Networks and the Nature of the Firm
âThe existence of high transaction costs outside
firms led to the emergence of the firm as we
know it, and management as we know itâŚ.The
reverse side of Coaseâs 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.âEsko Kilpi
17. If we want to understand the future of business and the
economy, we have to understand networked platforms
18. âA business model is the way that
all of the parts of a business work
together to create competitive
advantage and customer value.â
- Dan and Meredith Beam
19. Who Do You Want Your Customers to Become?
Henry Ford didnât just rethink
the automobile and the
factory, he rethought the
work week, and the reasons
why people might want to
drive.
20. A Business Model Map of Uber
ď§ A magical app that lets drivers
and passengers find each other
in real time
ď§ A networked marketplace of
drivers and passengers
ď§ Customers who trust that they
donât have to drive their own car
ď§ Augmented workers able to join
the market as and when they
wish
ď§ A matching market managed by
algorithm
21. What makes an app âmagicalâ?
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.
25. âThe Uber app is the driversâ workplace,
as much as the city where theyâre driving
is. Each decision about its interface
structures driversâ 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.â
Alexis Madrigal, The Atlantic,
âUber Drivers are About to Get a New Bossâ
26. The algorithms decide âwho gets what â and whyâ
Markets are outcomes. A better designed
marketplace can have better outcomes.
27. The great opportunity of the 21st century is to use our
newfound cognitive tools to build better marketplaces
28. A language for networked marketplaces
ď§Network effect: the value of a network is
proportional to the square of the number of
possible connections
ď§Scale effect: bigger is better (but not always)
ď§Feedback effect: the more data you collect from
the marketplace, the more you can learn, and the
better the services you can provide
ď§Two-sided market: different classes of users
being matched up: searchers and advertisers,
drivers and passengers, homes and renters.
29.
30. Asymptotic Networks
âThe 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.â
James Currier
31.
32. Market Networks
In a market network, youâre 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.
33.
34. âWe wouldnât 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 channelâŚ. So we created an XML feed standard âŚ
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.â
And, after 2009, when the real estate market collapsed, âto
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.â
Pete Flint
35. âOnce they get some traction, platforms survive
either because:
ď§ They achieve critical mass in a market with
network effects. They are the default place to
goâthis is why Craigslist, Airbnb, ebay, Etsy,
and other places with most of the inventory
thrive.
ď§ 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.â
Alistair Croll
36.
37.
38.
39. 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
43. 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
53. 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
54. Technology also has a fitness landscape
In my career, Iâve watched a number of migrations to new peaks, and Iâd like to share with
you some observations about what happened, and why. And then weâll talk about some
lessons for companies like Google, but also for the overall economy.
Apple
Personal
Computer
Big Data
and
AI
Smartphones
55. The Rules for Success Change
ď§ IBM fitness function: Maximize competitive advantage by control over hardware
ď§ Microsoft fitness function: Maximize competitive advantage by control over software
ď§ Google fitness function: Maximize competitive advantage by control over data and
marketplaces
ď§ Apple fitness function: Maximize competitive advantage by integrated control of
hardware, software, and marketplace.
ď§ In each case, companies playing by the old rules lost. Or did they?
56. 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
57. 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 âhackersâ 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.
60. OâReilly Media
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72. Many of todayâs 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
73. The lessons of technology are also lessons
for the organization of the business
âServices not only represent a
software structure but also the
organizational structure.â
Werner Vogels, Amazon CTO
74. How Amazon Became a Platform
â[Jeffâs] 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 teamâs data store, no shared-memory model, no back-doors
whatsoever. The only communication allowed is via service interface calls over the network.
4) It doesnât matter what technology they use. HTTP, Corba, Pubsub, custom protocols â
doesnât matter. Bezos doesnât 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 doesnât do this will be fired.â
Steve Yegge, in http://siliconangle.com/furrier/2011/10/12/google-engineer-accidently-
shares-his-internal-memo-about-google-platform/
76. Algorithmic systems have an âobjective functionâ
ď§Google: Relevance
ď§Facebook: Engagement
ď§Uber and Lyft: Passenger pick up time
ď§Scheduling software used by McDonaldâs, The Gap, or
Walmart: Reduce employee costs and benefits
77. What are you asking your algorithms to optimize for?
81. The runaway objective function
âEven robots with a seemingly
benign task could indifferently harm
us. âLetâs say you create a self-
improving A.I. to pick strawberries,â
Musk said, âand 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.â No
room for human beings.â
Elon Musk, quoted in Vanity Fair
https://www.vanityfair.com/news/2017/03/elon-musk-
billion-dollar-crusade-to-stop-ai-space-x
82. Will there really be nothing left for people to do?
Is there really
nothing left for
humans to do?
83. The Equinix NY4 data center,
where trillions of dollars change hands
84. What is the objective function of our financial markets?
âThe Social Responsibility of Business Is to
Increase Its Profitsâ
Milton Friedman, 1970
90. âComputational 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.â
Carla Gomes
91. 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
92. âEconomic Possibilities for Our Grandchildrenâ
The world of his grandchildrenâthe world of
those of us living todayâ would, âfor the
first time . . . be faced with [mankindâs] real,
his permanent problemâhow 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.â
John Maynard Keynes
John Maynard Keynes
94. It isnât technology that wants to eliminate jobs
âProsperity in human societies is
best understood as the
accumulation of solutions to
human problems. We wonât run
out of work until we run out of
problems.â
Nick Hanauer
95. Letâs use the power of networked platforms, and
new kinds of partnership with machines, to build
the world we actually want to live in
97. Tim OâReilly
@timoreilly
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Founder & CEO, OâReilly Media
Partner, OâReilly AlphaTech Ventures
Board member, Code for America
Co-founder, Maker Media