How Will Technological Disruption Strike Next? · Dilemma. Management faces a choice: embrace the change that will destroy a lucrative but vulnerable business, or protect it and hope

How Will Technological Disruption Strike Next?

A GUIDE FOR INVESTORS

October 2019

By Matthew Ward and Colin Moar

B A R I N G S I N V E ST M E N T I N ST I T U T E .C O M | 2

Investors have been scrambling to identify industries about to feel the brunt of all those dynamic forces

that have gained momentum since the emergence of the Internet in the late 1990s.

A useful framework for this analysis involves understanding how innovation has driven disruption in the

past, why it can take time to gather momentum, and how to assess the durability of change at different

levels of a society’s infrastructure. With this background, it becomes easier to identify the most import-

ant building blocks for a successful technology business while also understanding the elements that will

affect the rate of change. These may proceed very slowly for some time before a rapid acceleration.

The current pace of technological disruption raises thorny questions about the potential impact from

artificial intelligence and the Internet of Things, as well as the consequences of consumer behavior and

government regulation. This analytical roadmap should make it easier to explore initial answers.

“ECONOMIC PROGRESS, IN CAPITALIST SOCIETY, MEANS TUR MOIL.”

—JOSEPH SCHUMPETER, 1942


INNOVATION IS ALWAYS DISRUPTIVE

Clayton Christensen, the Harvard University professor and business development guru, describes the

process of “disruptive innovation” in two parts. First, as successful companies evolve and innovate,

they move up the value chain, adding richness of function and utility, and usually therefore charging

a higher price for that good or service. The second phase is an unintended consequence of these

price increases which allows new entrants to emerge. The incumbent’s higher prices eventually lead

to demand destruction at the lower end, when price-conscious buyers who don’t require the higher

functionality start looking elsewhere. The high profit margins generated by the winners attract the

new entrant with clever ideas who is better able to price attractively for more focused functionality,

and therefore grab significant market share. And so the cycle continues…

Longstanding technology giants such as IBM and Oracle are prime examples of this dynamic as they

grapple with the implications of the so-called Public Cloud. Private Clouds are data centers owned

or rented by companies for their own use, but built remotely from the offices they serve, rather than

on-premise, yet still maintained within the corporate security firewall. Public Clouds emerged as an

alternative that can serve more customers and drive far superior economics but operate outside of

the firewall and connect through the public internet. As the inevitable data security concerns are

addressed, more applications are either being migrated to the Public Cloud or rebuilt on these more

modern and cheaper IT architectures. These incumbents face a ferocious battle to protect the core

products and services on which they built their companies, as younger and more innovative firms

aggressively adopt new technologies to better serve the end customer. As is typical behavior, both

companies have belatedly realized the error in their delay to embrace Public Cloud1 and are now

forced to play catch up—from a position of weakness. The extent of their panic can be seen in IBM’s

acquisition of Red Hat2, which cost $34 billion in cash, a 63% premium to the close and the largest and

most expensive acquisition in its history.

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SOURCE: www.claytonchristensen.com, December 2015.1

FIGURE 1: Incumbents Nearly Always Win


This is a precisely what is meant by the Innovator’s

Dilemma. Management faces a choice: embrace the

change that will destroy a lucrative but vulnerable business,

or protect it and hope it will weather the new competitive

threat. There are few examples of those companies that

are able to embrace the disruption and become stronger.

Microsoft, under the leadership of Satya Nadella, offers a

notable exception as it stepped away from the foundations

of its decades-long success—its proprietary and closed

Windows Operating System—to adopt a radically different

approach built on opening up to external ecosystems

through its hugely popular Office applications suite and

Public Cloud services. Most, however, usually wither and

die or are bought for pennies on the dollar.

DISRUPTION DELIVERS A SHOCK, BUT IT STILL TAKES TIME

Thomas Edison and Joseph Swan invented lightbulbs in

the 1870s and with that started the race to electrification.

However, by 1900 only 5% of mechanical drive power

was coming from electric motors. Steam engines were

the lifeblood of American industry at the end of the 19th

Century, but it took another three decades to really see

the disruption caused by electrification and adoption of

electric motors.

What took so long? Factories had to be designed in a

completely new and different way to benefit from the

cheaper, smaller and much more efficient motors with

power that could now be distributed across a factory floor.

This change, for example, enabled the mass-production

lines that drove Henry Ford’s success. Consider these

two pictures, which show a 10-year gap and a world of

difference in New York’s Fifth Avenue. Once busy with

horse and carts, it wasn’t long before it was choked with

only cars, showing that once adoption of a new technology

picks up, the disruption can be exponentially swift.3

FIGURE 2: Easter Morning 1900. Fifth Avenue, New York City. Spot the automobile.

SOURCE: Library of Congress, Prints & Photographs Division, LC-DIG-ggbain-11656

SOURCE: National Archives. Photo No. 30-N-18827.

FIGURE 3: Easter Morning 1913. Fifth Avenue, New York City. Spot the horse.


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The first computer program was written in 1950, but it can be argued that it wasn’t until 2000 that significant

productivity improvements attributed to this innovation really got going. A large part of the problem is that Creative

Destruction, as described memorably by economist Joseph Schumpeter, needs to first get rid of the dead wood in an

industry before the better business practices really take root. As a society, we are still early in the process of learning

how best to use the internet and, even more so, the new Public Cloud Computing model, which significantly reduces

the costs and risks of starting new businesses. The rate of early adoption has still been spectacular with Amazon’s

AWS, the fastest-growing large-scale Enterprise Services business in history. Nine years after reaching $500 million of

revenues, it now generates three times the revenue Microsoft had managed over the same timeframe (Microsoft’s own

Public Cloud business, Azure, is today outpacing even AWS).4 Still, it takes time for firms to incorporate the benefits for

the Public Cloud into their own business models.

CREATION REQUIRES DESTRUCTION

Recent history is full of once-successful companies and even industries that have been decimated by new entrants that

have emerged with the rise of the internet in the mid-1990s.

Film photography was a $10 billion industry in 1997. The first digital camera (Casio’s QV-10 for $900) was introduced

at the same time Kodak’s market cap was $31 billion.5 By 2012, Kodak was bankrupt. Its attempt to introduce a digital

camera was too late to compete with others that built greater volume share in that space, with the resulting unit-cost

advantages, and was botched anyway due to overconfidence in Kodak’s brand as a leader that had seemingly cornered

the photography industry. It was, ultimately, the company’s inability to overcome the Innovators’ Dilemma. It could

not move faster than new entrants to embrace digital, as doing so at the price points set by competitors would have

crushed its own highly profitable photographic film business.

SOURCE: Barings.

FIGURE 4: Public Cloud Players Outpace Their Software Predecessors


Mobile phones in 1995 were very expensive, typically costing $1,000 for a voice-only handset, and just 13% of

Americans had one. U.S. household spending on long-distance voice calls fell from $77 billion in 2000 to $16

billion in 2013. By 2015, 44% of U.S. households had a cell phone but no land-line connection.6 The disruption

here was initially more about the convenience of mobility, with the price of the service being a secondary

concern, though one that played an increasingly important part as mobile phone penetration extended to

low-income consumers.

In 2012, cable TV cord-cutting households in the U.S. numbered less than 1 million. Today, there are more than

7 million, roughly the combined populations of New Jersey and Virginia.7 Even market leading services such

as Disney’s ESPN have been impacted, as the disruptors offering video streaming services over the internet

are accelerating changing viewing habits and taking advantage of incumbents’ unwillingness to give up their

lucrative bundled packages. So far, Netflix has found room under the cable firms’ bundled pricing umbrella,

moving along Christensen’s model path by improving its product with more original content, which allows

higher prices—until the next disruptor emerges underneath even their price points. Referring back to the

Innovators’ Dilemma discussed above, we think it is noteworthy to see Disney taking the bold strategic decision

to develop its own competitive streaming service. If you’re going to panic, panic early!

More than 1,500 shopping malls were built between 1956 and 2005. In 2007, the year before the financial crisis,

none opened at all. Between 2005 and 2015, 20% of all U.S. malls closed.8 ECommerce competitors have the

enviable ability to reach their customers via the Internet and, therefore, in much cheaper ways than renting

prime physical space. This advantageous starting point has enabled the likes of Amazon in the U.S. and Alibaba

in China to offer very attractive prices to their customers. Yet still they are able to make an acceptable margin

while investing aggressively in product selection and the enormous logistics effort that goes into delivering a

product and saving the customer the cost of a journey to the shops, also overcoming the immediate gratification

that comes from traditional retail shopping.

Source: Business Insider, September 2017. *Includes 408 Potential Closures Announced in Bankruptcy Filings.9

FIGURE 5: Number of Retail Stores Closing in 2017

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DIFFERENTIATING TEMPORARY DISRUPTION FROM PERMANENT DISRUPTION

Several factors are common to all of these examples, notably the digitization of the goods and services offered.

But, to truly be disruptive, this has to be combined with the technologies that enable the superior business

models which can better meet buyer needs, such as lower prices, greater convenience and more choice.

We find it instructive to view these disruptions through the lens of the broader societal environment acting

either as an accelerant or a brake on the rate at which they take place. Stewart Brand, the scientist and writer,

offers a diagram that highlights different rates of change in discrete layers of our society. Nature changes at the

slowest pace, fashion at the fastest rate. The vast majority of businesses that we assess operate in the fashion or

commerce layers, and, as such, they struggle to maintain both strong growth and profitability over the long term.

Businesses in the commerce and fashion layers that strive to make best use of the emerging infrastructure

companies, particularly Public Cloud services, as tools with which to disrupt the incumbent competition have

a good chance to succeed. They will inherently be incentivised to focus on innovation and lowering unit costs

in order to compete. Their real challenge is to maintain the pace of change and stay far enough in front of the

next wave of innovators that come behind them. The rewards are rapid growth and significant market shares

in large markets. AirBnB, the accommodation sharing business, ServiceNow, which automates IT, operations

and customer service processes, and Slack, which offers collaboration and messaging tools for teams, would be

three such examples.

The infrastructure layer is reserved for those businesses that invest for the long term, extract rents from the very

large base of users that use their goods and services, and ideally are able to operate without antagonising the

layers beneath: governance, culture and nature. A healthy platform dynamic that grows into (or even creates) a

large addressable market can more easily generate multiple self-sustaining flywheels.

Fashion

Commerce

Governance

Culture

Nature

Infrastructure

FIGURE 6: Pace Layering

SOURCE: Brand, S., 1999, The Clock of the Long Now, p. 37.


Companies such as Google, Facebook, Microsoft and particularly Amazon are doing a remarkable job of becoming

part of the infrastructure layer. If successful, the power they can wield and the profits they derive will be very large and

sustainable over the long term. If they fail, the reasons will most likely come from actions taken by governments and

regulators unhappy with their dominant market share.

Ultimately, the most enduring and successful investments in our view are those businesses that fit the model of

disruption laid out by Christensen and have a strong case to become part of the infrastructure layer described by Brand.

THE BUILDING BLOCKS OF DISRUPTION

So how do they do it? There is no magic formula, but there are key features of business models that have proved the

most disruptive in recent years.

ENTERING MARKETS WITH “FREE” AS A GROWTH STRATEGY

It is very hard to compete with “free” goods or services, and many new entrants in the digital sphere have grown

user bases rapidly on the back of no-charge offerings. The upfront cost of creating the first unit of digital goods

such as a software application or TV series to be streamed over the internet can easily exceed millions of dollars.

However, the marginal cost of the second copy—a perfect replica—is close to zero. And the same holds true for

the millionth copy, all thanks to the evolution of semiconductors with Moore’s Law and its exponential impact on

the cost of computer processing and data storage. Suddenly the ease with which you can distribute your goods, as

long as they are digital, is only really limited by how many people can access the internet and the time they have

available to consume your content.

Google’s Search is a great example of a “complementary good”, where offering Search for free has created an

unprecedented amount of demand (and data) for the advertising inventory on their websites from merchants. The

proceeds from this have allowed Google to reinvest and finance the extension of its platform into new industries, such

as autonomous vehicles.

While driverless vehicles might seem a long way from search engines, the ability for these digital companies to sustain

their advantage is built upon data and the rising economies of scale inherent in a digital business. More data means

better insight in how to utilize that data, which in turn drives more user engagement which attracts more merchants

trying to sell to the users, which again generates more data. And so the cycle continues.

Of course, this is where we see friction with the governance and culture layers of society. New laws, such as the

European Union’s General Data Protection Regulation, attempt to slow the growth of these internet giants as they

continually extend their lead over the smaller competitors and use the profits to fund disruptions in adjacent markets.

Scandals around Facebook’s lack of protection of personal data and the content uploaded onto YouTube are all forcing a

much-needed reappraisal of the role of data across all aspects of how our society works. Among the crucial questions

are whether these services are actually “free” and how far regulators will move to shape the rules of competition.


MASS PRODUCTION OF I.T.

INFRASTRUCTURE ACCELERATES THE FALL IN UNIT COSTS

The Public Cloud vendors have built business models

that proactively commoditize the computing hardware

that underpins IT infrastructure based on the scale and

standardization of the purchases from so-called white box

manufacturers. It was a purchase-department equivalent of the

Henry Ford sales model, “you can have any color as long as it’s

black”. The resulting huge drop in unit costs of the infrastructure

means it is being rented out at prices so low that even very

small companies with tiny operating budgets can afford to

build a digital side of their business on it. IT becomes a variable

operating cost, not a fixed capital cost. It is no accident that

the leading Public Cloud vendor, Amazon’s AWS, was built on

the success of the start-ups that were early adopters. AirBnB

and Netflix are just two that helped fill up AWS’s capacity, thus

lowering their costs—creating savings which could then be

passed on to new customers that kept the flywheel spinning.

The on-demand rental model10 allows companies that use Public

Cloud services to focus more on the customer-facing features of

their business that differentiate them from their competition. The

costs are so low that start-ups can test new business ideas and,

if they don’t work, they can switch them off having only paid for

the minimum computing resource required. This speaks to one

of the tenets underpinning AWS’ parent company Amazon—

failure is a good thing, as long as you survive long enough to

learn from the mistake.

Accelerating innovation is the inevitable by-product of widely

available Public Cloud infrastructure, as more entrepreneurs

can access IT infrastructure at a cost and scale that had

previously been reserved for the largest companies. Low unit

costs of computing are just half of the equation. Perhaps even

more important, a dramatically lower cost of failure is equally

as important as it incentivizes risk taking. Public Cloud enables

this, which makes it one of the primary engines of innovation

in the digital economy.


PLATFORMS DRIVE SCALE AND PROFITABILITY

The primary building block of a platform is Metcalfe’s Law11 which states that the value of a (telecommmunications)

network rises exponentially with the number of users. Platforms such as Facebook or Alibaba allow two or three types of

entities to meet and transact (consumers, merchants and advertisers). The value lies in a platform’s ability to aggregate end

users and connect them to merchants who want to sell them services or goods. When the platform offers an unlimited

supply of digital services, the traditional economic benefits flip in favor of the aggregator of demand and away from

suppliers that traditionally make use of their ability to limit supply in order to extract profits. This is a principal reason the

internet has been so disruptive to industries such as newspapers and retail.

In order to keep the flywheel of engagement and data spinning, the platforms add more services for their customers,

often encroaching on other markets and taking away from their core offerings. Or they allow third parties to bring more

innovation to the platform to better serve existing customers.12 For example, Tencent, the leader in China’s video gaming

and social media markets, became a major player in personal finance there after it enabled peer-2-peer payments over its

WeChat messaging platform. Having a large existing base of users means launching a new service or product category

can very rapidly become a large new business on its own. The returns to scale for platforms can be extremely attractive.

Threats to these already-successful platforms are again primarily from the layers of governance and culture upon which

their infrastructure is built, not from the layers above that are increasingly dependent on the platform’s infrastructure to

grow themselves.


DISRUPTION TAKES TIME, BUT MAY ARRIVE FASTER IN A DIGITAL WORLD

While these three elements—a free service that builds scale, infrastructure that drives down unit costs and a platform

that captures economic benefits—may help identify winners, they do not offer a formula for instant success.

Technology investors also need to analyze the time horizon over which such disruption can occur. Just as with light

bulbs, steam engines and automobiles, some extraordinary breakthroughs evolve slowly, for a long time, before they can

transform an industry overnight and all at once. For many parts of the technology industry itself or, indeed, industries

that depend on technology, dramatic change is at hand.

It seems an obvious point, but getting over-excited about the potential for disruption to occur can be extremely risky when

investing in companies based on the amount of hype around any given technological innovation. The dot-com boom-

then-spectacular-bust is the clearest example of over-estimating the short-term impacts of technological innovations—the

internet in that case—while under-estimating the long-term impact of technological disruption.

After the internet bust, it took another decade or so of business failures and rising internet penetration for enough

of the infrastructure components to be put in place to really change how consumers and enterprises behaved.

The ubiquitous availability of smartphones from Apple and the other manufacturers using Google’s “free” Android

operating system have served as a launch pad for new applications to proliferate and enable consumers to move their

lives increasingly online. Rapid growth in adoption of Public Cloud infrastructure followed soon after. Now we are

seeing a similar pattern of exponential growth in the rate of digitalization of businesses taking advantage of platforms

across all sectors of the economy.

This established base of profitable infrastructure13 has laid the groundwork for an ever-expanding list of new

technological innovations, and therefore markets, for technology companies to attack. The biggest question now is

how fast the disruption will arrive. Brand’s societal layers offer some guidance. Change will be quick for consumer

internet businesses playing to new fads and even cybersecurity firms trying to fight the newest threat vectors from

hackers, as both sit near the fashion and commerce layers. It will be much slower for those more deeply entrenched

in the infrastructure layer. But these companies need to contend increasingly with government regulation around data

privacy, and there is a growing argument for speed of change at this layer to increase somewhat in order to prevent

more draconian regulation later on. The competitive response from the incumbents may also slow the rate of progress.

Finally, the speed with which the disruptor can scale revenues and profits to create a sustainable business over the long

term will determine the pace of change.

The time taken for the disruptor to win depends on a number of different factors. If the incumbent is part of the

infrastructure layer, then the time taken will certainly be measured in years, if not decades. For example, Oracle’s

market-leading database business has been battling new entrants for many years. While its organic growth lags the

overall growth in enterprise software spending, Oracle built in barriers to exit from their high-end database licences

and structured maintenance contracts in ways that has slowed the decline in market share, even to players such as

MongoDB that offer a freemium model14 to ease the pain of adoption. The disruption threat is very real. But the decline

may be very slow.

B A R I N G S I N V E ST M E N T I N ST I T U T E .C O M | 1 2

A disruptor that has built its business on the Public Cloud infrastructure layer has given itself a very good chance of

success. However, the speed with which it can grow will be limited if the business requires physical rather than digital

assets. Overall eCommerce growth is multiples of that seen in physical retail, but it is still gated by the need to build a

network of physical warehouses and last-mile delivery capability.

Consumer behavior also needs to change from driving to a mall to instead order online, an evolution that progresses

at different rates in different geographies. In China, arguably, the long history of Communist rule prevented the retail

industry from investing in attractive shopping experiences, resulting in poorly located shops and a lack of focus on

aspirational brands to drive mall traffic. ECommerce companies such as Alibaba and JD.com offer infinite (digital) shelf

space and sell whatever is desired by the Chinese consumer. The relative lack of entrenched shopping habits probably

helped turbo-charge the early days of Chinese eCommerce.

Meanwhile, China built out the infrastructure for online payments, which offered a further boost. By contrast, in the U.S., a

highly over-banked population and a more powerful retail sector have slowed the disruption from digital payment solutions.

Ultimately we are highly sensitive to the risks around over-hyping the next big thing in technological disruption, given

the significant investments needed to change how deeply technology can penetrate a given industry, and how rapidly

it can spread through an economy. However, when tipping points are reached, the digital nature of these disruptive

technologies can have dramatic impacts on incumbents that are held back by their slow-to-adapt physical assets.

Properly assessing the magnitude and nature of the frictions involved is a crucial step in determining how long it will

take to see the significant positive impacts from technological disruption.

CONCLUSION

WE TEND TO BELIEVE THAT “HISTORY DOES NOT REPEAT, BUT IT DOES SOMETIMES RHYME.”15

LOOKING AT HISTORIC PERIODS OF TECHNOLOGICAL DISRUPTION, WE DO SEE A NUMBER OF

IMPORTANT COMMONALITIES WITH THE FORCES DRIVING CHANGE IN TODAY’S ECONOMY:

The automation of manual processes that put workers’ jobs at risk, which today requires the

digitalization of businesses.

A sharp bifurcation between the winners and losers that depends on whether the business is a

new entrant that fully adopts the new technology, or an incumbent trying to defend the strategy

it used to succeed in the past.

The time it takes for transformational technologies to become dominant is measured in decades, not

years. But we would argue that we are fast approaching the tipping point where the process accelerates.


What is new though is the nature of the internet and the changes it has enabled. It is a transformational technology

that has uniquely combined the multiplicative power of a large network with the scalability of digital assets (data), such

that the first businesses to reach scale are more likely to accelerate their growth rates. The Public Cloud is the modern

infrastructure layer at the center of many of the most disruptive technological shifts today. As a consequence, barriers

to starting new disruptive businesses have never been lower.

Meanwhile, investors should keep the Innovator’s Dilemma in mind as they sort through what keeps past winners from

defending themselves against disruption. Businesses that were built on profiting from frictions created by limits in the

supply of a good or service are collapsing in the face of increasingly digital competition, as digital supply is effectively

unlimited and therefore selling at zero marginal cost.

The most successful and enduring businesses in this world of dramatic technological change are those that can

disrupt industries and their incumbent leaders. This includes adopting business models that play to Christensen’s

model of disruptive innovation: offering simpler products must meet customer needs better than the legacy

competition; providing “Freemium” pricing strategies that build rapid scale; and operating their business on top of

digital platforms, such as those provided by the Public Clouds to get the full benefits of the lower unit costs and the

freedom to focus on innovation. If executed well, these strategies can generate high and sustainable profitability

over the long term.

WHILE THIS FRAMEWORK CAN BE A USEFUL STARTING POINT TO ASSESS POTENTIAL INVESTMENTS THAT

WILL BENEFIT FROM TECHNOLOGICAL DISRUPTION, IT ALSO RAISES A FAR THORNIER SET OF QUESTIONS:

• How will the modes of disruption affect the introduction of artificial intelligence and speed or slow the pace of change?

• How will increasing government regulations shape the scope of innovation, as new rules protect data privacy and

assign monetary value to data through fines and limits on competition?

• Will legacy enterprise software accelerate its move to the Cloud or be replaced by new Cloud-native competition?

• How will the advent of digital payments and blockchain drive change and disruption in the consumption and regula-

tion of financial services?

• What should investors watch for as technological change reshapes transportation through autonomous vehicles?

• How fast will the Internet of Things/Industry 4.0 drive change in industries such as manufacturing, healthcare, energy,

utilities and real estate, all of which we hope to bring into future work when the opportunities present themselves?

Ultimately we remain in the early stages of this technological disruption process, with the World Wide Web only

29 years old and the Public Cloud less than half that age. Many industries are still a long way from fully embracing the

benefits of digitizing their business and adapting their strategy to better leverage the new opportunities this presents.

Those that are too slow or resistant to the change will lose. Those that build their business on top of the new and

evolving digital infrastructures have a far greater chance.


COLIN MOARANALYST, TECHNOLOGY SECTOR TEAM

Colin is a Global Technology Analyst. Colin joined Barings in November 2016

from RWC Partners, where he was an Analyst for a Global Long-Short equity fund.

Previously, Colin has held equity analyst and fund management positions at Polar

Capital Partners, HSBC Global Asset Management and Aviva Investors. Colin holds a

BCom in Business Studies from the University of Edinburgh, passed the IMC in 1997

and the Institute of Investment Management and Research Associate level in 2000.

MATTHEW WARDHEAD OF TECHNOLOGY SECTOR TEAM

Matthew is Head of the Technology Sector Team. Matthew joined Barings in January

2008 from Bear Stearns International, where he was a Vice President in Equity

Research responsible for coverage of Telecoms stocks in the Pan-European region.

Matthew holds a BA in Business Economics from the University of Exeter and is a

Fellow Chartered Accountant (FCA).

We would like to take this opportunity to thank Barings colleagues Christopher Smart,

Andrew Lennon, Ian Dalton, Dan Mick, Alistair Packard and Brian Pope for their

thoughtful insights in developing the ideas behind this paper and to Michael Henry

for his helpful contributions through the editorial process.


1. This Web site and the information contained in it, is provided by Clayton Christensen, claytonchristensen.com, and its affiliated

organizations and is intended to provide general information on a particular subject or subjects and is not an exhaustive treatment

of such subjects. Accordingly, the claytonchristensen.com Web site is not intended to provide consulting, or other professional

advice or services. Before making any decision or taking any action that might affect you or your business, you should consult

a qualified professional advisor. THE CLAYTON CHRISTENSEN SITE, CLAYTONCHRISTENSEN.COM IS PROVIDED AS IS, AND

CLAYTON CHRISTENSEN MAKES NO EXPRESS OR IMPLIED REPRESENTATIONS OR WARRANTIES REGARDING THE WEB SITE.Certain

links in the claytonchristensen.com Web site lead to resources maintained by third parties over whom Clayton Christensen and

claytonchristensen.com has no control. Claytonchristensen.com makes no representations or warranties as to the accuracy of, or

any other aspect relating to those resources.

2. Red Hat’s most exciting business, and the main reason for IBM’s acquisition, is its OpenShift service which enables the migration of

workloads from on-premise settings into Cloud datacenters.

3. Source: Business Insider. As of March 2011.

4. Source: Company filings; Bloomberg; Barings’ estimates. Note: Revenues capped at $50 billion for illustration purposes.

5. “Creative Destruction” is attributed to economist Joseph Schumpeter who derived the idea from Karl Marx’s theories on economic

innovation and the business cycle. These examples and statistics are from Machine, Platform, Crowd: Harnessing our Digital Future—

Andrew McAfee & Erik Brynjolfsson. As of June 2017.

6. Ibid.

7. Source: theatlantic.com. As of September 2017. https://www.theatlantic.com/business/archive/2017/09/nfl-ratings-trump-anthem-

protests/541173/.

8. Ibid.

9. Source: Business Insider. As of June 4, 2017. http://uk.businessinsider.com/list-of-stores-closing-2017-6.

10. Certain AWS services are now billed by the second.

11. Definition of Metcalfe’s Law and Network Effects: https://en.wikipedia.org/wiki/Metcalfe%27s_law.

12. Often takes the form of Platform-as-a-Service (PaaS) offerings where either the customer builds their own custom applications on

top of the platform infrastructure, or third party application providers sell apps over the platform (app stores) thus building a more

significant ecosystem around that platform.

13. Only Amazon splits out their Public Cloud profitability, but it is running at a healthy high-20% GAAP operating margin. Microsoft’s

Azure is part of their broader Intelligent Cloud, which makes nearly 40% operating margins.

14. A pricing strategy where basic services are offered for free, but in order to have access to more features, a subscription fee will be

charged, often with different tiers of functionality and numbers of seats sold. The proportion of paid users can be very small, hence

losses in these businesses are often very high early. However, successful conversion from free to paid tiers offers clearly positive

economics over the life of the subscription.

15. A quote often ascribed to Mark Twain.

ENDNOTES

Barings is a $335+ billion* global financial services firm dedicated to meeting the evolving investment and capital needs of our

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