The Future of Platforms

Abstract

Platforms power the world’s most valuable companies, but it will get harder and harder to capture and monetize their disruptive potential. Today, platform companies are in nearly every market, and they all share common features. They use digital technology to create self-sustaining positive-feedback loops that potentially increase the value of their platforms with each new participant. They build ecosystems of third-party firms and individual contractors that allow them to bypass the traditional supply chains and labor pools required by traditional companies.

Moreover, all platform companies face the same four business challenges. They must choose the key “sides” of the platform (that is, identify which market participants they want to bring together, such as buyers and sellers, or users and innovators). They must solve a chicken-or-egg problem to jump-start the network effects on which they depend. They must design a business model capable of generating revenues that exceed their costs. And finally, they must establish rules for using (and not abusing) the platform, as well as cultivating and governing the all-important ecosystem.
For all their similarities, it is possible to distinguish platforms on the basis of their principal activity. This yields two basic types: transaction and innovation platforms, with some hybrid companies that combine the two.

Full text

2 MIT SLOAN MANAGEMENT REVIEW SPRING 2020
NAVIGATING THE SHARING ECONOMY
JEAN FRANCOIS PODEVIN/THEISPOT.COM
Platforms power some of the world’s most valuable companies,
but it will get harder and harder to capture and monetize their disruptive potential.
BY MICHAEL A. CUSUMANO, DAVID B. YOFFIE, AND ANNABELLE GAWER
The Future of Platforms

SLOANREVIEW.MIT.EDU SPRING 2020 MIT SLOAN MANAGEMENT REVIEW 3
The world’s most valuable public companies and its
first trillion-dollar businesses are built on digital plat-
forms that bring together two or more market actors
and grow through network effects. The top-ranked
companies by market capitalization are Microsoft,
Apple, Amazon, and Alphabet (Google’s parent com-
pany). Facebook, Alibaba, and Tencent are not far
behind. As of November 2019, these seven companies
represented more than $5.4 trillion in market value,
and all of them are platform businesses.1
Platforms are also remarkably popular among
entrepreneurs and investors in private ventures.
When we examined a 2017 list of more than 200 uni-
corns (startups with valuations of $1 billion or
more), we estimated that 60% to 70% were platform
businesses. At the time, these included companies
such as Ant Financial (an affiliate of Alibaba), Uber,
Didi Chuxing, Xiaomi, and Airbnb.2
But the path to success for a platform venture is by
no means easy or guaranteed, nor is it completely dif-
ferent from that of companies with more-conventional
business models. Why? Because, like all companies,
platforms must ultimately perform better than their
competitors. In addition, to survive long-term, plat-
forms must also be politically and socially viable,
or they risk being crushed by government regulation
or social opposition, as well as potentially massive
debt obligations. These observations are common
sense, but amid all the hype over digital platforms —
a phenomenon we sometimes call platformania —
common sense hasn’t always been so common.
We have been studying and working with plat-
form businesses for more than 30 years. In 2015, we
undertook a new round of research aimed at analyz-
ing the evolution of platforms and their long-term
performance versus that of conventional businesses.
Our research confirmed that successful platforms
yield a powerful competitive advantage with finan-
cial results to match. It also revealed that the nature
of platforms is changing, as are the ecosystems and
technologies that drive them, and the challenges and
rules associated with managing a platform business.
Platforms are here to stay, but to build a success-
ful, sustainable company around them, executives,
entrepreneurs, and investors need to know the dif-
ferent types of platforms and their business models.
They need to understand why some platforms
generate sales growth and profits relatively easily,
while others lose extraordinary sums of money.
They need to anticipate the trends that will deter-
mine platform success versus failure in the coming
years and the technologies that will spawn tomor-
row’s disruptive platform battlegrounds. We seek
to address these needs in this article.
Platform Company Evolution
The companies that shaped the evolution of modern
platform strategies and business models are familiar
names. In the 1980s and early 1990s, Microsoft, Intel,
and Apple, along with IBM, disrupted the vertically
integrated mainframe computer industry. They
made the personal computer into one of the first
mass-market digital platforms, which resulted in
separate industry layers for semiconductors, PC
hardware, software operating systems, application
software, sales, and services. A second wave of plat-
form firms emerged in the mid-1990s, led by
Amazon, Google, Netscape, and Yahoo in the U.S.,
Alibaba and Tencent in China, and Rakuten in Japan.
They leveraged the internet to disrupt a variety of in-
dustries, including retail, travel, and publishing. In
the next decade, social media businesses, pioneered
by Friendster and Myspace, and then Facebook,
LinkedIn, and Twitter, used platforms to enable new
ways for people to interact, and for companies to tar-
get customers. More recently, Airbnb, Didi Chuxing,
Grab, Uber, and smaller ventures such as Deliveroo
and TaskRabbit have used platform strategies to
launch the gig (or sharing) economy.
Today, platform companies are in nearly every
market, and they all share common features. They
use digital technology to create self-sustaining
positive-feedback loops that potentially increase
the value of their platforms with each new participant.

4 MIT SLOAN MANAGEMENT REVIEW SPRING 2020 SLOANREVIEW.MIT.EDU
NAVIGATING THE SHARING ECONOMY
They build ecosystems of third-party firms and
individual contractors that allow them to bypass
the traditional supply chains and labor pools
required by traditional companies.
Moreover, all platform companies face the same
four business challenges. They must choose the key
“sides” of the platform (that is, identify which mar-
ket participants they want to bring together, such as
buyers and sellers, or users and innovators). They
must solve a chicken-or-egg problem to jump-start
the network effects on which they depend. They
must design a business model capable of generating
revenues that exceed their costs. And finally, they
must establish rules for using (and not abusing) the
platform, as well as cultivating and governing the all-
important ecosystem.
For all their similarities, it is possible to distin-
guish platforms on the basis of their principal
activity. This yields two basic types: transaction and
innovation platforms, with some hybrid companies
that combine the two. (See “Basic Platform Types.”)
• Innovation platforms facilitate the development
of new, complementary products and services, such
as PC or smartphone apps, that are built mostly by
third-party companies without traditional supplier
contracts. By complementary, we mean that these
innovations add functionality or assets to the plat-
form. This is the source of their network effects:
The more complements there are or the higher
quality they are, the more attractive the platform
becomes to users and other potential market actors.
Innovation platforms typically deliver and capture
value by directly selling or renting a product, as
in traditional businesses. If the platform is free,
companies can monetize it by selling advertising or
other ancillary services. Microsoft Windows,
Google Android, Apple iOS, and Amazon Web
Services are commonly used innovation platforms.
• Transaction platforms are intermediaries or
online marketplaces that make it possible for par-
ticipants to exchange goods and services or
information. The more participants and functions
available on a transaction platform, the more useful
it becomes. These platforms create value by enabling
exchanges that would not otherwise occur without
the platform as an intermediary. They capture value
by collecting transaction fees or charging for ad-
vertising. Google Search, Amazon Marketplace,
Facebook, Tencent’s WeChat, Alibaba’s Taobao
marketplace, Uber, and Airbnb are commonly used
transaction platforms.
Hybrid companies contain both innovation and
transaction platforms. Their strategies are novel be-
cause, in the early years of the PC and the internet,
innovation and transaction platforms were distinct
businesses. Connecting buyers and sellers, advertisers
and consumers, or users of social networks appeared
to be a fundamentally different activity from stimu-
lating outside companies to create complementary
innovations. In the past decade, however, a growing
number of successful innovation platforms have in-
tegrated transaction platforms into their business
models. Rather than lose control over distribution,
the owners of these platforms have sought to manage
the customer experience, like Apple has done with its
App Store. Likewise, some successful transaction
platforms have opened their application program-
ming interfaces (APIs) and encouraged third parties
to create complementary apps and services. The
owners of these platforms, such as Facebook and
WeChat, recognize that not all innovation can or
should be internal. Other prominent examples of
hybrid strategies include Google’s decision to buy
Android, Amazon’s decision to create multiple in-
novation platforms around Amazon Web Services
and Alexa-Echo home AI devices, and Uber’s and
Airbnb’s decisions to allow third-party companies to
offer services that complement their ride-sharing
and room-sharing platforms. Today, the most valu-
able global companies (which we mentioned above)
all follow hybrid strategies.
Platform Company Value
Most platforms lose money (sometimes billions of
dollars), but platforms that dominate their markets
have been extraordinarily successful. When we com-
pared the largest 43 publicly listed digital platform
companies from 1995 to 2015 with a control sample
of 100 nonplatform companies in the same set of
businesses, we found that the two samples had
roughly the same level of annual revenues (about
$4.5 billion). But platform companies achieved their
sales with half the number of employees. Moreover,
This article and the book
on which it is based, The
Business of Platforms,
build on some 30 years of
research on the strategies
and business models of
platform companies.
Using 20 years of data from
the Forbes Global 2000,
the authors identified the
largest 43 publicly listed
platforms built around
the personal computer,
internet services, or mobile
devices from 1995 to 2015
and compared perfor-
mance with a control
sample of 100 nonplatform
companies in the same set
of businesses.
Drawing on annual reports,
the authors also identified
209 direct competitors to
the 43 platform companies
and analyzed reasons for
the competitors’ failures.
Through interviews, case
studies, and other sources,
they identified common
challenges faced by all
types of platforms, as
well as future trends for
platform technologies
and business models.
THE
RESEARCH

SLOANREVIEW.MIT.EDU SPRING 2020 MIT SLOAN MANAGEMENT REVIEW 5
platform companies were twice as profitable, were
growing twice as fast, and were more than twice as
valuable as their conventional counterparts.
In the process of examining the proxy statements
and annual reports of the 43 success stories, we identi-
fied 209 platform companies that were their direct
competitors but failed or disappeared as independent
companies. The causes of these failures were primarily
mispricing (under- or overcharging) on one side of
the market, oversubsidizing platform participants, or
entering markets too late. The high number of plat-
form failures supports the observation that even
platform businesses can fail or struggle as the com-
petitive environment or other factors change. For
example, computing and communications platforms
have faced continuous threats from new technologies
over the past 40 years. Early success stories such as
Myspace, Nokia, and BlackBerry saw their fortunes
rapidly decline. Looking at the bigger picture, PCs
cannibalized mainframes, smartphones cannibalized
traditional cellphones, smartphones and the cloud are
cannibalizing PCs, and so on.
In sum, platforms can become extraordinarily
successful businesses, and some successful plat-
form companies maintain their powerful positions
for decades. However, the creation of a platform,
even when it results in an IPO, is no guarantee of
long-term success. The business must still be able
to generate a profit and respond to change and
competition.
Future Platform Trends
While the past 20 years have seen a dramatic expan-
sion of platform-based technologies, applications,
BASIC PLATFORM TYPES
In the quest for competitive advantage, companies are combining transaction and innovation platforms into a hybrid model.
SOURCE: THE BUSINESS OF PLATFORMS: STRATEGY IN THE AGE OF DIGITAL COMPETITION, INNOVATION, AND POWER (HARPER BUSINESS, 2019)
HYBRID
COMPANIES
•
Apple
•
Google
•
Microsoft
•
Valve
•
Salesforce
•
Facebook
•
Tencent
•
Amazon
•
Snapchat
•
Instagram
•
Twitter
•
Airbnb
•
JD.com
•
Uber
•
LendingClub
•
TripAdvisor
•
Amazon Marketplace
•
WeChat
•
Facebook Social Network
•
Salesforce Exchange
•
Steam
•
Windows Store
•
Alibaba
•
Rakuten
•
LinkedIn
•
Match.com
•
Baidu
•
Google Play
•
Pinterest
•
Apple App Store •
Apple iOS
•
ARM CPU •
IBM Watson
•
Nintendo
•
Intel CPU
•
Sony PlayStation
•
GE Predix
•
SAP NetWeaver
•
Qualcomm Brew
•
Google Android
•
Microsoft Azure
•
Steam Machine
•
Force.com
•
Facebook for Developers
•
WeChat APIs
•
Amazon Web Services
INNOVATION
PLATFORMS
TRANSACTION
PLATFORMS
Innovations
The platform serves as a technological foundation upon
which other firms develop complementary innovations.
Transactions
The platform serves as an intermediary for direct
exchange or transactions, subject to network effects.

6 MIT SLOAN MANAGEMENT REVIEW SPRING 2020 SLOANREVIEW.MIT.EDU
NAVIGATING THE SHARING ECONOMY
and business models, the next 20 years may see even
more disruptive change. Digitization and emerging
technologies such as artificial intelligence, machine
learning, big data analytics, and infrastructure
services have not yet attained their full disruptive
potential. More and more individual user and trans-
actional data will become connected with different
platform services and functions, with the potential
to generate positive and negative outcomes.
No one can predict the future, but we have iden-
tified four major trends that are likely to affect
platform dynamics across industries: the emergence
of the hybrid model as the dominant strategy for
platform businesses, the use of AI and machine
learning to produce major improvements in plat-
form operations and capabilities, increasing market
concentration by a small number of powerful plat-
form companies, and the demand for more platform
curation and regulation to address problems un-
leashed by some of today’s platform companies.
TREND 1: More hybrid business models. Com-
petition and the potential of digital technology and
data will turn more and more platform firms into
hybrids. The underlying driver of this trend is digital
competition. Unlike in the traditional economy,
where companies require expensive physical invest-
ments to build out their business models, in the digital
world, companies can grow rapidly with a clever com-
bination of data, software, and ecosystem strategies.
TREND 2: More turbocharged innovation.
Next-generation platforms will drive innovation to a
new level. Advances in artificial intelligence, ma-
chine learning, and big data analytics are already
enabling organizations to do more things with less
investment, including building businesses that were
impossible in years past. Although AI is still in its na-
scent phase, Google, Amazon, Apple, Microsoft,
IBM, and other companies are no longer treating the
technology as fully proprietary. Instead, they have
turned some of their AI capabilities into platform
services that third parties can access and build upon
for their own applications. The combination of plat-
forms enabling the capture of more data, with the
ongoing improvements in cloud computing, should
allow future platforms to enable a wide range of new
applications, such as products with voice interfaces
and driverless cars.
TREND 3: More industry concentration. The
total number of platforms has been exploding, and
dominant market shares, as well as strong network ef-
fects, have been increasingly difficult to attain because
of multihoming (the ability of platform users and
complementors to access more than one platform for
the same purpose, such as using both Lyft and Uber
for ride-sharing). Nevertheless, in coming years, we
expect to see even more market power concentrated
in a smaller number of large platform companies.
This paradoxical situation will result because
some markets will tip toward one platform and fur-
ther concentrate market power. Witness IBM’s
ascension to the pinnacle of platform power in the
computer industry in the 1960s and 1970s, and
Intel’s and Microsoft’s in the 1980s and 1990s. In the
past decade, the number of markets that appear to
have tipped to a few dominant players has ex-
panded, with Amazon, Alibaba, Apple, Google,
Facebook, Microsoft, Tencent, and Uber, among
others, achieving market shares well over 50%.
TREND 4: More curation and regulation. Mark
Zuckerberg based his early dictum to “move fast
and break things” on the premise that good things
PLATFORM BUSINESS PERFORMANCE, 1995-2015
An analysis of the performance of successful platform companies versus an industry
control sample reveals the outsized advantage delivered by platforms.
SOURCE: THE BUSINESS OF PLATFORMS: STRATEGY IN THE AGE OF DIGITAL COMPETITION, INNOVATION,
AND POWER (HARPER BUSINESS, 2019)
VARIABLE*
INDUSTRY
CONTROL
SAMPLE
PLATFORM
COMPANIES
Number of Companies 100 43
Sales (millions) $4,845 $4,335
Employees 19,000 9,872
Operating Profit % 12% 21%
Market Value (millions) $8,243 $21,726
Market Value/Sales Multiple** 1.94 5.35
R&D/Sales 9% 13%
S&M + G&A/Sales*** 17% 24%
Sales Growth Versus Prior Year 9% 18%
Market Value Growth 8% 14%
Total number of years of data for the sample firms 1,018 374
* Differences significant at p < 0.001 for industry sample versus platforms comparison using
two-sample Wilcoxon rank sum (Mann-Whitney) test
**Market Value/Sales Multiple = ratio of market value compared with prior-year sales
*** S&M + G&A/Sales = sales and marketing expenses plus general and administrative expenses
divided by sales

SLOANREVIEW.MIT.EDU SPRING 2020 MIT SLOAN MANAGEMENT REVIEW 7
will happen if we connect the people of the world.
Most platform entrepreneurs and investors agreed
with him: They believed that platforms would
connect people with products and services at ever-
decreasing prices and free the world from the
frictions and imperfections of traditional and local
marketplaces. As it turns out, not all actors in the
digital world are do-gooders. Those engaged in
partisan politics, spies, terrorists, counterfeiters,
money launderers, and drug dealers all found ways
to use digital platforms to their advantage.
Once the platforms reach a scale at which they
can affect social, political, and economic systems,
their owners increasingly need to evolve from hands-
off to hands-on curation. (See “A Crisis of Ethics in
Technology Innovation,” by Max Wessel and Nicole
Helmer, in this issue.) In the years ahead, virtually all
large platform companies will evolve from free mar-
ketplaces to curated businesses with increasing
government oversight and potentially new types of
regulation. Although it is a cliché, for the world’s big-
gest platforms, growing power means increased
responsibility — and oversight.
Three Emerging Platform
Battlegrounds
Several competitions are currently underway that il-
lustrate the trends above and offer insight into what
might come next in platform technology and strat-
egy. Several fast-emerging fields — AI, cloud
computing, and, ultimately, quantum computing —
will enable disruptive innovations as well as changes
in business models.
Voice wars: Rapid growth, but chaotic compe-
tition. Recent advances in machine learning and
the subfield of deep learning have led to dramatic
improvements in pattern recognition, especially
for images and voice. Apple got the world excited
about a voice interface with the introduction of Siri
in 2011. For the first time, consumers had access to
a natural conversation technology that worked (at
least some of the time). Despite its first-mover
advantage, however, Apple’s strategy for Siri was
classic Apple: It designed Siri as a product to com-
plement the iPhone, not as a platform that could
generate powerful network effects in its own right.
Enter Amazon. When it introduced the Echo
speaker and Alexa software in late 2014, it set in mo-
tion a war for platform domination among Alibaba,
Apple, Google, Microsoft, Tencent, and a host of
voice startups. Amazon’s strateg y was to link multiple
platforms powered by Amazon Web Services and
offer a combination of speech recognition and high-
quality speech synthesis with various applications.
Immediately identifying the potential for network
effects, Amazon launched its Alexa Skills Kit — a
collection of self-service APIs and tools that made it
easy for third-party developers to create new Alexa
apps. This open-platform strategy accelerated the
number of Alexa skills from roughly 5,000 in late
2016 to more than 90,000 in 2019.
Amazon’s success spurred Apple, Google,
Samsung, and various Chinese companies into ac-
tion. By late 2017, voice had morphed into a classic
platform battle: Amazon and Google began heavily
discounting products to build their installed base,
with each side racing to add applications and func-
tions. All the major players have also been licensing
their technologies (often for free) to consumer
electronics, automotive, and enterprise software
firms, hoping that these companies will use their
voice platforms and solutions.
How the platform war in voice computing will
evolve depends heavily on the ease of multihoming.
Currently, consumers can easily switch voice plat-
forms or use more than one. It will also depend on
how the players choose to position themselves.
There are many opportunities for competitor dif-
ferentiation and niche competition in voice: Apple
has focused on the quality of music, Amazon on
In the years ahead, virtually all large platform companies will
evolve from free marketplaces to curated businesses with
increasing government oversight and potentially new types
of regulation.

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NAVIGATING THE SHARING ECONOMY
media and e-commerce, and Google on search-
related queries, to name only a few.
Meanwhile, competitive advantage has not yet
hardened into market concentration. Google has
already embedded its voice capabilities into hun-
dreds of millions of Android devices. But Amazon
has the largest smart-speaker installed base, with
tens of millions of devices sitting in users’ homes,
especially in the United States.
Ultimately, we expect the winner or winners in
voice to be those platforms that build the largest in-
stalled base of users and create the more vibrant
ecosystems for producing innovative applications.
These ecosystems are likely to generate compelling
voice solutions that reduce platform multihoming
and competition from niche players and differenti-
ated competitors.
Ride-sharing and self-driving cars: From plat-
form to service. While AI will spawn a range of new
products, platforms, and services, it will also enable
new capabilities that create, enhance, and destroy ex-
isting businesses. Nowhere is this dynamic clearer
than in the emergence of self-driving cars, where
Japan’s SoftBank has invested $60 billion in 40 com-
panies, including Didi, Grab, and Uber. Although
Uber has already fallen far below its peak valuations,
and other investments may follow, SoftBank is bet-
ting that transportation services platforms, such as
ride-sharing accessed through smartphones, will
eventually become highly concentrated businesses,
generating huge returns similar to Alibaba, Apple,
Google, and other digital platforms.3
Ironically, this new AI-powered technology not
only threatens the century-long hegemony of auto-
makers but may also disrupt today’s ride-sharing
platforms. Despite relatively strong network effects
between users and drivers, innovation in technol-
ogy and business models could replace the
platforms belonging to companies such as Didi,
Grab, Lyft, and Uber.
The business challenge for ride-sharing plat-
forms is simple: They tend to lose money, and lots
of it. Unlike asset-light transaction platforms such
as eBay, Expedia, or Priceline, ride-sharing plat-
forms are not fully digital businesses: The ordering
and payment transaction is digital, but the service
delivery is physical, with mostly local and limited
economies of scale and scope. Furthermore, the
cost of attracting and paying drivers while keeping
fares below the market price of taxis has squeezed
the profit potential and resulted in huge losses for
these companies. In addition, many drivers and
riders multihome: They drive for or use both Uber
and Lyft, as well as conventional taxis.
The bottom line is that platformizing a low-margin
business like taxi services or food delivery does not
necessarily make it a profitable business, like selling
software products or other digital goods. As a result,
Didi, Grab, Lyft, and Uber have announced that their
long-term strategies are to move beyond purely
transactional platforms that match riders with driv-
ers to transportation as a service. As Lyft CEO Logan
Green said, “We are going to move the entire [car]
industry from one based on ownership to one based
on subscription.”4 In this new model, ride-sharing
platforms will probably own or lease fleets of auto-
mobiles, as well as bicycles and scooters.
Tech companies like Google and most of the major
automobile manufacturers, including General Motors
and Toyota, are also investing aggressively in similar
strategies. Despite a long history of selling products,
even the most conservative car companies see AI as a
way to transform themselves into service companies.
Autonomous vehicle technology promises to re-
move human drivers, which would dramatically
drive down the marginal cost of transportation ser-
vices for ride-sharing platform owners. But, in
addition to bringing new competitors into the
industry, it would also require massive capital invest-
ments in R&D and fleet costs. Some observers see
Ultimately, we expect the winner or winners in voice to
be those platforms that build the largest installed base of
users and create the more vibrant ecosystems for producing
innovative applications.

SLOANREVIEW.MIT.EDU SPRING 2020 MIT SLOAN MANAGEMENT REVIEW 9
this combination of conditions forcing Uber and
other ride-sharing platforms to “either figure out a
way to buy or at least manage an enormous fleet …
or face annihilation by others who will.”5 In response
to this threat, Uber began investing in autonomous
vehicle technology in 2014. Lyft has taken a different
approach by trying to form partnerships through its
Open Platform Initiative.
Owning or leasing a fleet of autonomous vehicles
is counter to the two-sided platform business model
of matching riders with drivers and their cars. If they
make the transition to autonomous fleets, Uber and
Lyft will become one-sided, company-controlled
platforms that own and resell their own assets. The
risk is that self-driving car services are unlikely to
materialize as quickly or be as profitable as purely
digital platforms with high transaction volumes.
Nonetheless, future consumers are likely to benefit
from more and cheaper ride-sharing services, as
long as these businesses have enough capital and
cash flow to survive.
Quantum computers: A next-generation com-
puting platform. In 1981 Nobel laureate Richard
Feynman challenged his fellow scientists to build a
computer mimicking nature — a quantum com-
puter. The challenge was accepted. In 2015 McKinsey
consultants estimated that 7,000 researchers were
working on quantum computing, with a combined
budget of $1.5 billion.6 By 2018, dozens of universi-
ties, approximately 30 major companies, and more
than a dozen startups had notable quantum com-
puting R&D efforts underway.7 More recently still,
Google announced that it had built a quantum
computer that far exceeded the capabilities of the
world’s fastest supercomputers, at least for specific
types of calculations.8
The state of quantum technology today resem-
bles that of conventional computing in the late 1940s
and early 1950s: Quantum computers are difficult
and expensive to build and program, and reside pri-
marily in universities and corporate research labs.
Nonetheless, they represent a revolutionary innova-
tion platform, with the additional potential to
stimulate new transaction platforms for specialized
applications in simulation, optimization, cryptogra-
phy, and secure communication.
Will quantum computing produce successful
new platform businesses? Currently, the network
effects appear weak because the application ecosys-
tems are still nascent and divided among several
platform contenders. A spin-off from the University
of British Columbia named D-Wave Systems,
founded in 1999, has the lead in applications and the
largest patent portfolio, followed by IBM and
Microsoft. However, D-Wave has not built a general-
purpose quantum computer, unlike most other
entrants into the field, and recently IBM has taken
the lead in annual patent filings. To build better pro-
gramming tools and test real-world applications,
more researchers must gain access to these patents
and to more-powerful quantum computers.
Quantum computers will not replace digital
computers. Nor do we see this field as a winner-
takes-all-or-most market in which one company’s
unique architecture will dominate, as occurred in
mainframes, PCs, smartphones, microprocessors,
consumer electronics, and other markets. Quantum
computers will most likely always be special-purpose
devices for certain types of massively parallel com-
putations, with different technologies more useful
for particular applications.
At the same time, quantum computing platforms
are likely to face intense scrutiny and regulation be-
cause of the potential cryptography applications. On
the one hand, quantum computers may be able to
break secure keys generated by the most powerful
conventional computers, which now protect much
of the world’s information and financial assets. On
the other hand, quantum computers themselves
could generate unbreakable keys and facilitate truly
secure communication. The leading companies will
have to regulate themselves as well as work closely
with governments, which are likely to play a major
role in overseeing some of these new applications
and services.
Platforms as Disrupters
We are heading into a future where we will buy and
own fewer products (cars, bikes, vacation homes,
household tools, and so on), and we will contract
for more services directly with one another. We will
likely manage this sharing through peer-to-peer
transaction platforms along with general-purpose
digital technologies, such as blockchain, to enable
more secure and transparent exchanges.
Some platforms that enable this future will follow

10 MIT SLOAN MANAGEMENT REVIEW SPRING 2020 SLOANREVIEW.MIT.EDU
NAVIGATING THE SHARING ECONOMY
the model of disruption that Clayton Christensen
has described, with cheaper, inferior technologies
gradually overtaking incumbents. This occurred
with the gradual domination of personal comput-
ers over mainframe computers and the rise of
e-commerce and internet marketplaces over tradi-
tional stores, though the older technologies and ways
of doing business continue to exist. We expect to see
similar Christensen-style disruptions in the future,
with voice platforms and self-driving cars.
But this is not the only type of disruption we ex-
pect to see in the platform economy. Our research
illustrates how platform disruption can come from
above, as well as from below. For example, Apple and
the iPhone disrupted the smartphone industry by
building a high-end platform with superior perfor-
mance and features from the very beginning.
Similarly, quantum computing systems and applica-
tions such as cryptography or complex simulations
will likely arrive as expensive solutions coming from
the high end of the market.
Massive infusions of capital are a third form of
disruption that could be just as powerful as new
technologies and business models, such as turning
transportation into a subscription service. The use
of smartphones to match drivers and riders was in-
novative as a business model and required only
modest investments in new technology. But what is
less remarked on is the fact that Uber and other
ride-sharing platforms disrupted the taxi business
by spending billions of dollars in venture capital to
subsidize a low-margin commodity transportation
business. Whether or not Uber and similar ven-
tures survive, and whether or not financial backers
such as SoftBank ever recoup their investments,
they have disrupted the taxi business forever.
In short, industrywide platforms and their
global ecosystems have already disrupted many
aspects of our personal and working lives. New in-
novation and transaction platforms have enabled
nearly every type of exchange and activity imagin-
able in today’s world, and platform entrepreneurs
have made Anything-as-a-Service possible. No
matter how they evolve, we expect that future plat-
forms will continue to inspire both innovation and
disruption.
Michael A. Cusumano is the MIT Sloan Management
Review distinguished professor of management at
MIT Sloan School of Management, David B. Yoffie is
the Max and Doris Starr Professor of International Busi-
ness Administration at Harvard Business School, and
Annabelle Gawer (@AnnabelleGawer) is chaired pro-
fessor of digital economy at Surrey Business School
at the University of Surrey. This article is adapted from
the authors’ book The Business of Platforms: Strategy
in the Age of Digital Competition, Innovation, and
Power (Harper Business, 2019). Comment on this
article at http://sloanreview.mit.edu/x/61304.
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All rights reserved.
Massive infusions of capital are a third form of disruption
that could be just as powerful as new technologies and
business models.