Digitalization

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Essay prompt:

· Analyze how the increasing intensity of information technology investments, the digitization of business, and the big shifts in the U.S. economy have affected the competitive dynamics of Courier industry – FedEx.

For background on how the increasing intensity of information technology investments, the digitization of business, and the big shifts in the U.S. economy have affected competitive dynamics, please do the below readings. I have attached the articles.

· Hagel, J., Brown, J.S., and Davison, L. “The Big Shift: Measuring the Forces of Change,” Harvard Business Review (87:7-8), Jul-Aug 2009, pp 86-90.

· McAfee, A., and Brynjolfsson, E. “Investing in the IT that makes a competitive difference,” Harvard Business Review (86:7-8), Jul-Aug 2008, pp. 98-107.

· Govindrajan, V. & Srivastava, A. (2016). “Strategy When Creative Destruction Accelerates.” Tuck School of Business Working Paper No. 2836135, Available at SSRN: 

https://ssrn.com/abstract=2836135Links to an external site.

Writing criteria:

1. How well does the essay build on course concepts covered in the reading above.

2. How well does the essay build on facts and evidence of the Courier industry in analyzing the essay prompt.

Essay format:

· Use a maximum of one, single-sided page (no more than 600 words), single-line spacing, 1″ margins on all sides, Verdana font type, and 10-point font size.

International Business

The Big Shift: Measuring the
Forces of Change
by John Hagel III, John Seely Brown, and Lang Davison

From the Magazine (July–August 2009)

Summary.   Reprint: R0907Q Traditional metrics don’t capture many of the

challenges and opportunities in store for U.S. companies and the national

economy. The authors, from Deloitte, present a framework for understanding the

forces that have transformed business over…

During a steep recession, managers obsess over short-term

performance goals such as cost cutting, sales, and market share

growth. Meanwhile, economists chart data like GDP growth,

unemployment levels, and balance-of-trade shifts to gauge the

health of the overall business environment. The problem is,

focusing only on traditional metrics often masks long-term forces

of change that undercut normal sources of economic value.

“Normal” may in fact be a thing of the past: Even when the

economy heats up again, companies’ returns will remain under

pressure.

One reason traditional measures alone don’t capture the

challenges and opportunities for U.S. companies and the national

economy is that the digital infrastructure supporting the lion’s

share of industries has sustained rapid performance

improvements—especially in computing power, bandwidth, and

storage. Previous infrastructures experienced sharp bursts of

more

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innovation in underlying technologies, such as the telephone and

the internal combustion engine, and then quickly stabilized.

Today, we do not yet see any signs of stabilization, which suggests

not only that competitive intensity (which has more than doubled

in the past 40 years) will continue to build but also that the digital

infrastructure will keep boosting the potential—and necessity—

for business innovation.

To help managers in this decidedly challenging time, we present a

framework for understanding three waves of transformation in

the competitive landscape: foundations for major change; flows of

resources, such as knowledge, that allow firms to enhance

productivity; and the impacts of the foundations and flows on

companies and the economy. Combined, those factors reflect

what we call the Big Shift in the global business environment.

The Shift Index

Executives can use the metrics here to gauge the long-

term forces shaping the business environment and

improve their …

Additionally, we have developed an index to measure the changes

that have had the biggest effect on business over the past four

decades (see the exhibit “The Shift Index”). That set of metrics

reveals a dramatic increase in performance pressure on U.S.

companies. Their average return on assets (ROA) has steadily

fallen to almost one quarter of what it was in 1965, despite the fact

that labor productivity has improved. Worse yet, even the highest-

performing companies are struggling to maintain their ROA levels

and losing their leadership positions at an ever-faster rate. The

paradox of falling ROA alongside growing productivity is

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explained at least in part by the rising total compensation of

knowledge workers and other talented employees, and by

consumers’ growing power over vendors that end up “competing

away” their cost savings. An even closer look at the situation

shows a fundamental mismatch between the mind-set of today’s

companies and the environment in which they compete.

Elements of the Big Shift

The first, foundational wave in the Big Shift consists of the

extraordinary changes in digital infrastructure that enable vastly

greater productivity, transparency, and connectivity. Consider

how companies can use digital technology to create ecosystems of

diverse, far-flung users, designers, and suppliers in which product

and process innovations fuel performance gains without

introducing too much complexity.

The second wave involves the increasing movement of

knowledge, talent, and capital. Knowledge flows—which occur in

any social, fluid environment where learning and collaboration

can take place—are quickly becoming one of the most crucial

sources of value creation. Facebook, Twitter, LinkedIn, and other

social media foster them. Virtual communities and online

discussion forums do, too. So do companies situated near one

another, working on similar problems. Twentieth-century

institutions built and protected knowledge stocks—proprietary

resources that no one else could access. The more the business

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environment changes, however, the faster the value of what you

know at any point in time diminishes. In this world, success

hinges on the ability to participate in a growing array of

knowledge flows in order to rapidly refresh your knowledge

stocks. For instance, when an organization tries to improve cycle

times in a manufacturing process, it finds far more value in

problem solving shaped by the diverse experiences, perspectives,

and learning of a tightly knit team (shared through knowledge

flows) than in a training manual (knowledge stocks) alone.

Knowledge flows can help companies gain competitive advantage

in an age of near-constant disruption. The software company SAP,

for instance, routinely taps the more than 1.5 million participants

in its Developer Network, which extends well beyond the

boundaries of the firm. Those who post questions for the network

community to address will receive a response in 17 minutes, on

average, and 85% of all the questions posted to date have been

rated as “resolved.” By providing a virtual platform for customers,

developers, system integrators, and service vendors to create and

exchange knowledge, SAP has significantly increased the

productivity of all the participants in its ecosystem.

The good news is that strong foundational technology is enabling

much richer and more diverse knowledge flows. The bad news is

that mind-sets and practices tend to hamper the generation of

and participation in those flows. That is why we give such

prominence to them in the second wave of the Big Shift. The

number and quality of knowledge flows at a firm—partly

determined by its adoption of openness, cross-enterprise teams,

and information sharing—will be key indicators of its ability to

master the Big Shift and turn performance challenges into

opportunities. The ultimate differentiator among companies,

though, may be a competency for creating and sharing knowledge

across enterprises. Growth in intercompany knowledge flows will

be a particularly important sign that firms are adopting the new
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institutional architectures, governance structures, and

operational practices necessary to take full advantage of the

digital infrastructure.

The initial findings from our research indicate a correlation

between the rapidly growing use of social media and the

increasing knowledge flows between organizations. Worker

passion also appears to be an important amplifier: When people

are engaged with their work and pushing the performance

envelope, they seek ways to connect with others who share their

passion and who can help them get better faster. Self-employed

people are more than twice as likely to be passionate about their

work as those who work for firms, according to a survey we

conducted. This suggests a potential red flag for institutional

leaders—companies appear to have difficulty holding on to

passionate workers.

The final wave reflects how well companies are exploiting

foundational improvements in the digital infrastructure by

creating and sharing knowledge—and what impacts those

changes are having on markets, firms, and individuals. For now,

institutional performance is almost universally suffering in the

face of intensifying competition. But over time, as firms learn

how to harness the digital infrastructure and participate more

effectively in knowledge flows, their performance will improve.

Differences in approach between top-performing and

underperforming companies are telling. As some organizations

participate more in knowledge flows, we should see them break

ahead of the pack and significantly improve overall performance

in the long term. Others, still wedded to the old ways of operating,

are likely to deteriorate quickly.

Closing the Performance Gap

Our research findings highlight the stark performance challenges

for companies. What’s more, the data suggest that unless firms

take radical action, the gap between their potential and their

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realized opportunities will grow wider. That’s because the benefits

from the modest productivity improvements that companies have

achieved increasingly accrue not to the firm or its shareholders

but to creative talent and customers, who are gaining market

power as competition intensifies.

Until now, companies were designed to get more efficient by

growing ever larger, and that’s how they created considerable

economic value. The rapidly changing digital infrastructure has

altered the equation, however: As stability gives way to change

and uncertainty, institutions must increase not just efficiency but

also the rate at which they learn and innovate, which in turn will

boost their rate of performance improvement. “Scalable

efficiency,” in other words, must be replaced by “scalable

learning.” The mismatch between the way companies are

operated and governed on the one hand and how the business

landscape is changing on the other helps explain why returns are

deteriorating while talent and customers reap the rewards of

productivity.

So, how can companies narrow the growing gap between the

performance promised by digital technology and their actual

financial results? Just as twentieth-century firms discovered how

to harness then-new energy, transportation, and communication

infrastructures to become bigger and more efficient, today’s firms

must make the most of the digital infrastructure. This requires

innovations at the institutional level that better position

organizations to succeed both during the current recession and

after the economy recovers. By developing diverse relationships

across enterprises, firms can accelerate performance

improvement as they add participants to their ecosystems,

expanding their learning and innovation—much as SAP has done

with its Developer Network.

Companies must therefore design and then track operational

metrics showing how well they participate in knowledge flows.

For example, they might want to identify relevant geographic

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clusters of talent around the world and assess their access to that

talent. In addition, they might want to track the number of

institutions with which they collaborate to improve performance.

In contrast to the twentieth century—when senior management

decided what shape a company should take in terms of culture,

values, processes, and organizational structure—now we’ll see

institutional innovations largely propelled by individuals,

especially the younger workers, who put digital technologies such

as social media to their most effective use. But management can

play an important supporting role: Recognize that passionate

employees are often talented and motivated but also tend to be

unhappy, because they see a lot of potential for themselves and

for their companies but can feel blocked in their efforts to achieve

it. Identify those who are adept participants in knowledge flows,

provide them with platforms and tools to pursue their passions,

and then celebrate their successes to inspire others.• • •

Performance pressures will continue to increase well past the

current downturn. As a result, leaders must move beyond the

marginal expense cuts they might be focusing on now in order to

weather the recession. They need instead to be ruthless about

deciding which assets, metrics, operations, and practices have the

greatest potential to generate long-term profitable growth and

shedding those that do not. They must keep coming back to the

most basic question of all: What business are we really in?

It’s not just about being lean; it’s also about making smart

investments in the future. One of the easiest but most powerful

ways firms can achieve the performance improvements promised

by technology is to jettison management’s distinction between

“creative talent” and the rest of the organization. All workers can

continually improve their performance by engaging in creative

problem solving, often by connecting with peers inside and

outside the firm. Japanese automakers used elements of thisYou are seeing this message because ad or script blocking software is interfering with
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approach with dramatic effects on the bottom line, turning

assembly-line employees from manual laborers into problem

solvers.

Our Research

We pulled together four decades’ worth of data from

more than a dozen sources, designed and conducted

four …

At the end of the day, the Big Shift framework puts a number of

key questions on the leadership agenda: Are companies organized

to effectively generate and participate in a broader range of

knowledge flows, especially those that go beyond the boundaries

of the firm? How can they best create and capture value from such

flows? And, most important, how do they measure their progress

navigating the Big Shift in the business landscape? We hope that

the Shift Index will help executives answer those questions—in

these difficult times and beyond.

A version of this article appeared in the July–August 2009 issue of Harvard

Business Review.

John Hagel III recently retired from Deloitte,
where he founded and led the Center for the
Edge, a research center based in Silicon Valley.
A long-time resident of Silicon Valley, he is also
a compulsive writer, having published eight
books, including his most recent one, The
Journey Beyond Fear. He will be establishing a
new Center to offer programs based on the
book.

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John Seely Brown, coauthor of A New Culture
of Learning and The Power of Pull as well as
many other books and articles, is a visiting
scholar at the University of Southern California
and independent cochair of the Deloitte Center
for the Edge. He was formerly the chief
scientist of Xerox and director of its Palo Alto
Research Center.

Lang Davison ([email protected]) is
the executive director.

JB

LD

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Electronic copy available at: http://ssrn.com/abstract=2836135

Strategy When Creative Destruction Accelerates

Vijay Govindarajan

Coxe Distinguished Professor, Tuck School of Business and a Marvin Bower Fellow at Harvard

Business School

[email protected]

Anup Srivastava

Assistant Professor, Tuck School of Business, Dartmouth College,

[email protected]

Electronic copy available at: https://ssrn.com/abstract=2836135

Electronic copy available at: http://ssrn.com/abstract=2836135

1

Strategy When Creative Destruction Accelerates

Life is short. That’s never been more true for corporations today. An analysis of all 29,688 firms

that listed from 1960 through 2009, divided into 10-year cohorts, reveals that newly listed firms in

recent cohorts fail more frequently than did those in older ones (Figure 1). Creative destruction is

accelerating because there is a fundamental shift in the American economy. The pre-1970 firms

tended to be heavily invested in physical infrastructure, such as factories and inventories. Later

cohorts have relied increasingly on intangible assets, such as databases, proprietary algorithms,

and expert workers (Figure 2). This transformation is a double-edged sword. The good news is

that newer firms are more nimble. The bad news for these firms is that their days are numbered.

That is, unless they continuously innovate.

The newer firms are grounded in novel business models, like digital services, that can be launched

and distributed quickly. This gives them an advantage over production firms. “Idea” companies

don’t require an expensive infrastructure of factories, warehouses, and suppliers to operate. They

don’t need an extensive distribution network to get their product to market. They don’t need

elaborate marketing campaigns—news of successful products spreads rapidly through blogs and

social networks. Winners emerge quickly and reap rewards disproportionately larger than the

initial investments. Uber, for example, officially launched its mobile app in select U.S. cities in

2011 and within a year’s time had expanded into Europe. Now, its market cap exceeds $60 billion.

Contrast this with the evolution of the automotive industry. Around the beginning of the 20th

century, more than 200 companies sprang up in the U.S. to produce automobiles. It took almost

half a century for the number of large domestic automakers to shrink to four. Despite the

introduction of such disruptive technologies as the assembly line, integrated supply chains, and

lean manufacturing, the consolidation took 50 years. Innovations rooted in physical assets take

time to create. Even Silicon Valley automaker Tesla not only has invested in a capital-intensive

assembly plant in California, but also is building a Gigafactory in Nevada to produce lithium

batteries and a nationwide network of Superchargers for its electric cars. Tesla and other tangible

goods firms, many of them listed in the 1960s and 1970s, do have a distinct advantage, however:

The time and money necessary to produce tangible goods create entry barriers and offer protection

against competitors—unlike ideas, which can be more easily imitated.

Electronic copy available at: https://ssrn.com/abstract=2836135

Electronic copy available at: http://ssrn.com/abstract=2836135

2

And that is the central challenge for firms that rely mostly on intangible assets today: It’s easier

and faster to copy an idea and commoditize digital strategy than to create a physical infrastructure.

Myspace, launched in 2003, was the largest social networking site in the world from 2005 to 2008

before being usurped by relative newcomer Facebook (which rolled out to the public in 2006). It’s

a scenario that is repeated time and again: Evernote, Microsoft OneNote, Apple Notes, Google

Keep, Simplenote, and other note-taking apps leapfrog over each other vying for the same

consumers, as do Skype, FaceTime, Viber, jitsi, and Google Hangouts in the video-chat arena.

Some of them will not survive even as new competitors enter the market.

At any point in time, newer firms outnumber companies in earlier cohorts (Figure 3). The overall

business environment thus keeps changing with the arrival of newer cohorts. Creative destruction

therefore will only speed up in the future, offering both opportunities and threats. The landscape

will change at a dizzying pace, luring investors with the promise of fast ROIs and winner-takes-

all reward structures, creating historically unparalleled opportunities for market capitalization.

Already this year, 18 companies—7 of them U.S. firms—have achieved unicorn status (startups

valued at $1 billion). But the fall from grace can happen just as quickly. Consider Groupon,

described by Forbes as “the fastest growing company ever” just two years after its 2008 launch,

now the poster child for bad business models. Even older, well-established idea companies can be

whiplashed by the market roller-coaster, as Microsoft will testify. The software giant gained more

than $270 billion in market capitalization from August 1998 to December 1999 and then lost in

excess of $340 billion over the next 13 months. Cisco gained $ 300 billion of market cap from

August 1999 to March 2000 and then lost $420 billion over the next one year. Apple lost $150

billion market cap in just one month in 2016.

The pressure on CEOs, particularly heads of companies listed in the past two decades, to produce

short-term value is immense. But beating the survival odds depends on developing a long-term

strategy, one that is invested in continuous innovation.

No company—whether its products are tangible or intangible, is a century or a year old—has the

luxury of basking in yesterday’s success. However, in this information age, that success can be

appropriated too swiftly by a newer company with a better idea. The key to competitive advantage

Electronic copy available at: https://ssrn.com/abstract=2836135

3

is ensuring innovation is an integral part of business strategy, a nonstop cycle of mining, testing,

and executing. Equally important is the timely pullback of organizational resources from

yesterday’s promising ideas that now appear less promising and their continual redeployment

towards tomorrow’s new ideas. In other words, to survive you must build a better mousetrap each

day—or at least an app for one.

Electronic copy available at: https://ssrn.com/abstract=2836135

4

Figure 1

A company listed before 1970 had a 92 percent chance of surviving the next five years, compared to just 63 percent

for a company listed between 2000 and 2009.

If we delete firms that died in 2000 and 2008, the result still holds. That is to say, after controlling for dot.com

bust and the Great Recession, the results still show a decline in survival rates over time.

Electronic copy available at: https://ssrn.com/abstract=2836135

5

Figure 2

Changing completive strategies

To address new economic environment, each new

cohort of listed firms spends more on building

intellectual assets and less on physical assets.

Annual expenditures

on organizational

capital as a percentage

of total assets

Annual expenditure

on physical assets as

a percentage of total

assets

Firms listed in the decade

Electronic copy available at: https://ssrn.com/abstract=2836135

6

Of the total number of firms in 2009, 60 percent were listed between 2000 and 2009 and only 5 percent were

listed prior to 1960.

Figure 3

Constant renewal of listed firms

The set of listed-firm population keeps

renewing itself with the constant listing of new

firm and demise of legacy firms. The average

characteristics at a given time reflect those of

the newest cohorts.

Electronic copy available at: https://ssrn.com/abstract=2836135

Electronic copy available at: https://ssrn.com/abstract=2836135

Process Management

Investing in the IT That Makes
a Competitive Difference
by Andrew McAfee and Erik Brynjolfsson

From the Magazine (July–August 2008)

Summary.   Reprint: R0807J Investments in certain technologies do confer a

competitive edge—one that has to be constantly renewed, as rivals don’t merely

match your moves but use technology to develop more potent ones and leapfrog

over you. That’s the conclusion of…

It’s not just you. It really is getting harder to outpace the other

guys. Our recent research finds that since the middle of the 1990s,

which marked the mainstream adoption of the internet and

commercial enterprise software, competition within the U.S.

economy has accelerated to unprecedented levels. There are a

number of possible reasons for this quickening, including M&A

activity, the opening up of global markets, and companies’

continuing R&D efforts. However, we found that a central catalyst

in this shift is the massive increase in the power of IT

investments.

To better understand when and where IT confers competitive

advantage in today’s economy, we studied all publicly traded U.S.

companies in all industries from the 1960s through 2005, looking

at relevant performance indicators from each (including sales,

earnings, profitability, and market capitalization) and found some

striking patterns: Since the mid-1990s, a new competitive

more

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dynamic has emerged—greater gaps between the leaders and

laggards in an industry, more concentrated and winner-take-all

markets, and more churn among rivals in a sector. Strikingly, this

pattern closely matches the turbulent “creative destruction”

mode of capitalism that was first predicted over 60 years ago by

economist Joseph Schumpeter. This accelerated competition has

coincided with a sharp increase in the quantity and quality of IT

investments, as more organizations have moved to bolster (or

altogether replace) their existing operating models using the

internet and enterprise software. Tellingly, the changes in

competitive dynamics are most apparent in precisely those

sectors that have spent the most on information technology, even

when we controlled for other factors.

This pattern is a familiar one in markets for digitized products

like computer software and music. Those industries have long

been dominated by both a winner-take-all dynamic and high

turbulence, as each group of dominant innovators is threatened

by succeeding waves of innovation. Consider how quickly Google

supplanted Yahoo, which supplanted AltaVista and others that

created the search engine market from nothing. Or the relative

speed with which new recording artists can dominate sales in a

category.

Most industries have historically been fairly immune from this

kind of Schumpeterian competition. However, our findings show

that the internet and enterprise IT are now accelerating

competition within traditional industries in the broader U.S.

economy. Why? Not because more products are becoming digital

but because more processes are: Just as a digital photo or a web-

search algorithm can be endlessly replicated quickly and

accurately by copying the underlying bits, a company’s unique

business processes can now be propagated with much higher

fidelity across the organization by embedding it in enterprise

information technology. As a result, an innovator with a better

way of doing things can scale up with unprecedented speed to

dominate an industry. In response, a rival can roll out further

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process innovations throughout its product lines and geographic

markets to recapture market share. Winners can win big and fast,

but not necessarily for very long.

CVS, Cisco, and Otis Elevator are among the many companies

we’ve observed gaining a market edge by competing on

technology-enabled processes—carefully examining their

working methods, revamping them in interesting ways, and using

readily available enterprise software and networking technologies

to spread these process changes to far-flung locations so they’re

executed the same way every time.

The link between technology and
competition has become much
stronger since the mid-1990s.

In the following pages, we’ll explore why the link between

technology and competition has become much stronger and

tighter since the mid-1990s, and we’ll clarify the roles that

business leaders and enterprise technologies should play in this

new environment. Competing at such high speeds isn’t easy, and

not everyone will be able to keep up. The senior executives who

do may realize not only greatly improved business processes but

also higher market share and increased market value.

How Technology Has Changed Competition

The mid-1990s marked a clear discontinuity in competitive

dynamics and the start of a period of innovation in corporate IT,

when the internet and enterprise software applications—like

enterprise resource management (ERP), customer relationship

management (CRM), and enterprise content management (ECM)

—became practical tools for business. Corporate investments in

IT surged during this time—from about $3,500 spent per worker

in 1994 to about $8,000 in 2005, according the U.S. Bureau of

Economic Analysis (BEA). (See the exhibit “The IT Surge.”) At the

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same time, annual productivity growth in U.S. companies roughly

doubled, after plodding along at about 1.4% for nearly 20 years.

Much attention has been paid to the connection between

productivity growth and the increase in IT investment. But hardly

any has been directed to the nature of the link between IT and

competitiveness. That’s why, with help from Harvard Business

School researcher Michael Sorell and Feng Zhu, who’s now an

assistant professor at USC, we set out two years ago to compare

the increase in IT spending with various measures of competition,

focusing on three quantifiable indicators: concentration,

turbulence, and performance spread.

The IT Surge

The total real stock of IT hardware and software in the

United States began to rise dramatically in the mid-

1990s. …

In a concentrated or winner-take-all industry, just a few

companies account for the bulk of the market share. For our

study, we focused on the degree to which each industry became

more or less concentrated over time. A sector is turbulent if the

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sales leaders in it are frequently leapfrogging one another in rank

order. And finally the performance spread in an industry is large

when the leaders and laggards differ greatly on standard

performance measures such as return on assets, profit margins,

and market capitalization per dollar of revenue—the kinds of

numbers that matter a lot to senior managers and investors.

Were there economywide changes in these three measures after

the mid-1990s, when IT spending accelerated? If so, were the

changes more pronounced in industries that were more IT

intensive—that is, where IT made up a larger share of all fixed

assets within an industry? In a word, yes.

We analyzed industry data from the BEA, as well as from annual

company reports, and found that average turbulence within U.S.

industries rose sharply starting in the mid-1990s. Furthermore,

after declining in previous decades, industry concentration

reversed course and began increasing around the same time.

Finally, the spread between the highest and lowest performers

also increased. These changes coincided with the surge in IT

investment and the concurrent productivity rise, suggesting a

fundamental change in the underlying economics of competition.

(See the exhibit “Competitive Dynamics: Several Ways to Slice

IT.”)

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Competitive Dynamics: Several Ways to Slice IT

How does IT spending affect the nature of competition

and the relative performance of companies within an

industry? …

Looking more closely at the data, we found that the changes in

dynamics were indeed greatest in those industries that were more

IT intensive—for instance, consumer electronics and auto parts

manufacturers. Further, we considered the role of M&A activity,

globalization, and R&D spending in our analysis of the

competitive landscape and found some minor correlations—but

none strong enough to override our measures (see the sidebar “Is

IT the Only Factor That Matters?”).

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Is IT the Only Factor That Matters?

Previous research suggests that the changes we’ve

observed in the competitive environment are not

primarily …

One interpretation of our findings might be that IT is, indeed,

inducing the intensified competition we’ve documented—but

that the change in dynamics is only temporary. According to this

argument, the years since the mid-1990s have seen a onetime

burst of innovation from IT producers, and it’s simply taking IT-

consuming companies a while to absorb them all. Businesses will

eventually figure out how to internalize all the new tools,

proponents of this theory say, and then all industries will revert to

their previous competitive patterns.

While it’s true that the tool kit of corporate IT has expanded a

great deal in recent years, we believe that an overabundance of

new technologies is not the fundamental driver of the change in

dynamics we’ve documented. Instead, our field research suggests

that businesses entered a new era of increased competitiveness in

the mid-1990s not because they had so many IT innovations to

choose from but because some of these new technologies enabled

improvements to companies’ operating models and then made it

possible to replicate those improvements much more widely.

CVS offers a great example. There’s no shortage of people looking

to fill prescriptions—or of outlets ready to handle those orders. So

CVS works hard to maintain a high level of customer service.

Imagine senior management’s concern, then, when surveys

conducted in 2002 revealed that customer satisfaction was

declining. Further analysis uncovered a key problem: Some 17%

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of the prescription orders were being delayed during the

insurance check, which was often performed after customers had

already left the store. The team decided to move the insurance

check forward in the prescription fulfillment process, before the

drug safety review, so all customers would still be around to

answer common questions such as, “Have you changed jobs?”

This two-step process change was embedded in the information

systems that supported pharmacy operations, thereby ensuring

100% compliance. The transaction screen for the drug safety

review now appeared on pharmacists’ computers only after all the

fields in the insurance-check screen had been completed; it was

simply no longer possible to do the safety review first. The

redesigned protocol helped boost customer satisfaction scores

without compromising safety—and not just in one store but in all

of them. CVS used its enterprise information technology to

replicate the new process throughout its 4,000-plus retail

pharmacies nationwide within a year. Performance increased

sharply, and overall customer satisfaction scores rose from 86% to

91%—a dramatic difference within the aggressive pharmacy

market.

The enterprise IT underlying this initiative served two key roles.

It helped the process changes stick: Clerks and pharmacists

couldn’t fall back on their old habits once the new protocol was

embedded in the company’s information systems. More

important, it also allowed for quick and easy propagation of the

new process to all 4,000 sites—radically amplifying the economic

value of the initial innovation. Without enterprise IT, CVS could

still have tried to implement this process innovation, but it would

have been much more cumbersome. Updated procedure manuals

might have been sent to all CVS locations, or managers may have

been rotated in for training sessions and then periodically

surveyed to monitor compliance. But propagating the new

process digitally accelerated and magnified its competitive

impact by vastly increasing the consistency of its execution

throughout the organization.

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Although modern commercial enterprise systems are relatively

recent—SAP’s ERP platform, for example, was introduced in 1992

—by now, companies in virtually every industry have adopted

them. According to one estimate, spending on these complex

platforms already accounted for 75% of all U.S. corporate IT

investment in 2001. More recently, IT consultancy Gartner Group

projected that worldwide enterprise software revenue would

approach $190 billion in 2008.

To understand how this profusion of enterprise IT is changing the

broader competitive landscape, imagine that a drugstore chain

like CVS has a number of rivals, most of which also have multiple

stores. Before the advent of enterprise IT, a successful innovation

by a manager at one store could lead to dominance in that

manager’s local market. But because no firm had a monopoly on

good managers, other firms might win the competitive battle in

other local markets, reflecting the relative talent at these other

locations. Sharing and replication of innovations (via analog

technologies like corporate memos, procedures manuals, and

training sessions) would be relatively slow and imperfect, and

overall market share would change little from year to year.

With the advent of enterprise IT, however, not just CVS, but its

competitors have the option to deploy technology to improve

their processes. Some may not exercise this option because they

don’t believe in the power of IT. Others will try and fail. Some will

succeed, and effective innovations will spread rapidly. The firm

with the best processes will win in most or all markets. At the

same time, competitors will be able to strike back much more

quickly: Instead of simply copying the first mover, they will

introduce further IT-based innovations, perhaps instituting

digitally mediated outsourcing or CRM software that identifies

cross- and up-selling opportunities. These innovations will also

propagate widely, rapidly, and accurately because they are

embedded in the IT system. Success will prompt these companies
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to make bolder and more frequent competitive moves, and

customers will switch from one company to another in response

to them.

As a result, performance spread will rise, as the most successful IT

exploiters pull away from the pack. Concentration will increase,

as the losers fall by the wayside. And yet turbulence will actually

intensify, as the remaining rivals use successive IT-enabled

operating-model changes to leapfrog one another over time.

Thus, despite the shakeout, rivalry in the industry will continue

to become more fast-paced, intense, and dynamic than it was

prior to the advent of enterprise technology. These are exactly the

changes we see reflected in the data.

In this Schumpeterian environment, the value of process

innovations greatly multiplies. This puts the onus on managers to

be strategic about innovating and then propagating new ways of

working.

Competing on Digital Processes

To survive, or better yet thrive, in this more competitive

environment, the mantra for any CEO should be, “Deploy,

innovate, and propagate”: First, deploy a consistent technology

platform. Then separate yourself from the pack by coming up

with better ways of working. Finally, use the platform to

propagate these business innovations widely and reliably. In this

regard, deploying IT serves two distinct roles—as a catalyst for

innovative ideas and as an engine for delivering them. Each of the

three steps in the mantra presents different and critical

management challenges, not least of which have to do with

questions of centralization and autonomy.

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The Elements of a Successful IT-Enabled Process

Given the costs of enterprise IT and the risks inherent in

deploying it poorly, it’s especially important that the …

Deployment: the management challenge.

Since the mid-1990s, the commercial availability of enterprise

software packages has added a new item to the list of senior

management’s responsibilities: Determining which aspects of

their companies’ operating models should be globally (or at least

widely) consistent, then using technology to replicate them with

high fidelity. Some top teams have pounced on the opportunity.

Many more, however, have embraced this responsibility only

reluctantly, unwilling to tackle two formidable barriers to

deployment: fragmentation and autonomy.

Historically, regional, product, and function managers have been

given a great deal of leeway to purchase, install, and customize IT

systems as they see fit. But bitter experience has shown that it’s

prohibitively time-consuming and expensive to stitch together a

jumble of legacy systems so they can all use common data, and

support and enforce standardized processes. Even if a company

invests heavily in standardized enterprise software for the entire

organization, it may not remain standard for long, as the software

is deployed in ways other than it was originally intended in

dozens, or even hundreds, of separate instances. When that

happens, it’s almost certain that data, processes, customer

interfaces, and operating models will become inconsistent—thus

defeating the whole competitive purpose of purchasing the

package in the first place.

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That’s what initially happened at networking giant Cisco. In the

mid-1990s, Cisco successfully implemented a single ERP platform

throughout the company. Managers were then given the green

light to purchase and install as many applications as they wanted,

to sit on that platform. Cisco’s IT department helped the various

functions, technology groups, and product lines throughout the

world get their desired programs up and running without

attempting to constrain or second-guess their decisions.

When newly arrived CIO Brad Boston assessed Cisco’s IT

environment in 2001, he found that system, data, and process

fragmentation was an unintended consequence of the company’s

enthusiasm for technology. There were, for example, nine

different tools for checking the status of a customer order. Each

pulled information from different repositories and defined key

terms in different ways. The multiple databases and fuzzy terms

resulted in the circulation of conflicting order-status reports

around the company. Boston’s assessment also revealed that there

were over 50 different customer-survey tools, 15 different

business-intelligence applications, and more than 200 additional

IT projects in progress.

Deployment efforts heighten the tensions—present in every

sizable company—between global consistency and local

autonomy. As the Cisco example shows, however, this conflict

often exists by default rather than by design. Ultimately, the top

team’s focused efforts to manage this tension reaped tremendous

benefits.

Responding to the CIO’s assessment, senior managers decided to

upgrade Cisco’s original ERP system and other key applications to

support standardized data and processes. The upgrade was

budgeted at $200 million over three years. Cisco identified several

key business processes—market to sell, lead to order, quote to

cash, issue to resolution, forecast to build, idea to product, and

hire to retire—and configured its systems to support the

subprocesses involved in each stage. The software updates and

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the strategy discussions the technology engendered eventually

resulted in greater consistency throughout the organization and

contributed to Cisco’s strong performance over the past few years.

At about the same time that Cisco was untangling its legacy

spaghetti, the leader of a much older and more traditional

company was also reimagining the kinds of information systems

his firm would need to compete more successfully. When Ari

Bousbib became president of Otis in 2002, the information

systems of the 149-year-old company were not so much

fragmented as virtually nonexistent. As Harvard Business

School’s F. Warren McFarlan and Brian J. DeLacey recounted in a

2005 case study, the software applications in place were largely

antiquated for implementing the critical processes of gathering

customer requests to install a new elevator system, specifying the

exact configuration of the order, and creating a final proposal. In

many regions, in fact, the processes were still being done entirely

on paper.

Like Cisco, Otis took a hard look at its core processes and ended

up replacing old software with a new enterprise technology

platform the company called e*Logistics. It was designed to

connect sales, factory, and field operations worldwide through

the internet. Otis defined four processes—sales, order fulfillment,

field installation, and job closing—and designed e*Logistics to

ensure that improvements in the way each process was carried

out occurred uniformly, every time, everywhere. Eventually, Otis

realized not only significantly shorter sales-cycle times but higher

revenues and operating profit.

Innovation: IT-enabled opportunities.

Data analytics drawn from enterprise IT applications, along with

collective intelligence and other Web 2.0 technologies, can be

important aides not just in propagating ideas but also in

generating them. They are certainly no replacement for brilliant
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insights from a line manager or a eureka moment during a

meeting, but they can complement and speed the search for

business process innovations.

UK grocery chain Tesco is one company that employs enterprise

IT’s aggregation and analysis capabilities in this way. Like many

retailers around the world, it uses customer-rewards cards to

collect detailed data about individuals’ purchases, to categorize

customers, and to tailor offers accordingly. But the grocer goes a

step further, tracking redemption rates in great detail and

performing experiments to tweak its processes to get a better

response from customers. In an industry where the average

redemption rate for direct-marketing initiatives is about 2%,

Babson professor Tom Davenport has noted, Tesco’s data

analytics help drive its rate to approximately 20%.

Web 2.0 applications that bring collective wisdom to the fore can

also uncover potential business innovations. Jim Lavoie, CEO of

the technology firm Rite-Solutions, built something called a

“Mutual Fun” market within the company’s intranet that has

three indices employees can invest in—Savings Bonds for ideas

on saving costs, Bow Jones for ideas on extending existing

products, and Spazdaq for new product concepts. Any Rite-

Solutions employee can suggest a new idea in any of these

markets. Workers can also view the “prospectus of ideas,” invest

play money in them, and even sign up to complete any tasks

necessary to make those concepts reality. As Lavoie said in a

recent online interview with the nonprofit Business Innovation

Factory: “We believe the next brilliant idea is going to come from

somebody other than senior management, and unless you’re

trying to harvest those ideas, you’re not going to get them….That’s

why we give everybody an equal voice, and a game to provoke

their intellectual curiosity.”

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Propagation: top down and bottom up.

Part of the attraction of enterprise systems has been the

opportunity for management to impose best practices and

standardized procedures universally, as CVS did to great

advantage, and so eliminate the chaos of inconsistent homegrown

practices. There’s really no competitive advantage in having each

department develop and use its own idiosyncratic process for

inventory control, for instance, especially when best practices

already exist.

While an ERP system is an obvious tool for propagation, other

technologies are also important, and they show that innovations

do not necessarily emanate from headquarters. For instance, Web

2.0 applications can help process changes emerge organically

from lower levels in an organization. Within Cisco, for instance, a

community of about 10,000 Macintosh users was dissatisfied with

the level of support they were receiving from the company’s

central IT group. But instead of complaining, they created a wiki

to share ideas about how to use their Macs more effectively. They

posted information, files, links, and applications that could be

edited by any user—tips and tricks that ultimately became huge

productivity enhancers. In this case, process innovations flowed

through the company to its great benefit without central

management direction.

The role of decision rights.

At first glance, the Cisco and Otis examples seem to support the

view that propagating processes using enterprise IT necessarily

leads to more centralized companies—ones in which most of the

important decisions are made at the top and the rest of the

business exists only to execute them. Many of the choices about

core business processes and the systems that support them were

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managers, and the companies’ change efforts appeared to lead to

higher levels of centralization than had previously existed. But

the reality is more complicated.

Even as some decisions become centralized and standardized,

others are pushed outward from headquarters. Senior executives

do play a primary role in identifying and propagating critical

business processes, but line managers and employees often end

up with more discretion within these processes to serve customer

needs and to apply tacit, idiosyncratic, or relationship-specific

information that only they have. To appreciate how important

this distinction is, consider an analogy from government. The

process of writing a constitution is inherently a highly centralized

activity—a small group of framers makes decisions on behalf of

an entire population. It’s perfectly possible, and in fact common,

however, for that constitution to define a highly decentralized

government.

At both Cisco and Otis, local managers and frontline employees

retained critical responsibilities in their companies’ IT-enabled

operating models—and often gained new ones. After e*Logistics

was put in place at Otis, for example, field installation supervisors

became responsible for the first time for certifying that a site was

ready to install an elevator before it would be shipped. (In the old

operating model, the equipment was simply shipped as soon as it

was manufactured.) The new business practice was standardized

throughout the world, but it was not centralized. It actually

placed more responsibility in the hands of frontline employees.

Consider, too, the Spanish clothing company Zara. It has more

than 1,000 stores worldwide, and they all order clothes exactly the

same way, using the same digital form, following a rigid weekly

timetable for placing orders. Most other large apparel retailers

rely on sophisticated forecasting algorithms, executed by

computers at headquarters, to determine which clothes will sell in

each location and in what quantities. Headquarters pushes these

clothes down to stores with virtually no input from their

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managers. Zara’s store managers, however, have almost complete

discretion over which clothes to order; they choose them based on

local tastes and immediate demand.

This sharp difference between Zara’s and other retailers’

approaches to the same challenge highlights a critically important

point: We don’t expect that enterprise IT will inevitably lead to

one best way to execute core processes. In fact, it can prompt a

great deal of experimentation and variation, as companies try to

understand who has the most relevant knowledge to make

decisions and where, ultimately, to site decision rights.

Maximizing Return on Talent

As corporate IT facilitates the implementation and monitoring of

processes, the value of simply carrying out rote instructions will

fall while the value of inventing better methods will rise. In some

cases, this may even lead to a “superstar” effect, as

disproportionate rewards accrue to the very best knowledge

workers. Human resource policies and corporate culture will need

to evolve to support this type of worker. An effective leader and a

well-designed organization will need not only to aggressively seek

out and identify such individuals and the innovations they

generate but also to develop and reward them appropriately.

An analysis of 400 U.S. companies that Erik Brynjolfsson

published with Wharton professor Lorin Hitt in 2005, found that

organizations successfully using IT were significantly more

aggressive in vetting new hires: They considered more applicants.

They scrutinized each one more intensively. They involved senior

management (not just HR) early and often in the interview

process. After identifying top talent, these firms invested

substantially more time and money on both internal and external

training and education. Furthermore, they gave their employees

more discretion in how to do their jobs while linking their

compensation and rewards—including promotions—more tightly

to performance using a suite of metrics that was more detailed

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than competitors’. The costs of managing talent in this way may

be high, but the payoff increases exponentially if you can leverage

the talents of a high-performing manager at one location to

maximize results in thousands of sites worldwide.• • •

The arrival of powerful new information technologies does not

render obsolete all previous assumptions and insights about how

to do business, but it does open up new opportunities to

executives. Our research has led us to three conclusions: First of

all, the data show that IT has sharpened differences among

companies instead of reducing them. This reflects the fact that

while companies have always varied widely in their ability to

select, adopt, and exploit innovations, technology has accelerated

and amplified these differences. Second, line executives matter:

Highly qualified vendors, consultants, and IT departments might

be necessary for the successful implementation of enterprise

technologies themselves, but the real value comes from the

process innovations that can now be delivered on those platforms.

Fostering the right innovations and propagating them widely are

both executive responsibilities—ones that can’t be delegated.

Finally, the competitive shakeup brought on by IT is not nearly

complete, even in the IT-intensive U.S. economy. We expect to see

these altered competitive dynamics in other countries, as well, as

their IT investments grow.

It is not easy for most companies to deploy enterprise IT

successfully. The technologies themselves are complicated to

configure and test, and changing people’s behavior and attitudes

toward technology is even more challenging. Enterprise IT

typically changes many jobs in major ways; this is never an easy

sell to either employees or line managers. As the performance

spread, concentration, and churn increase, management becomes

a distinctly less comfortable profession—more unforgiving of

mistakes, faster to weed out low performers. Even those

executives who are prepared will not necessarily survive the
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inevitable turbulence. But those who do can expect outsize

rewards—at least until another player comes along and uses IT to

propagate a business innovation that’s even better.

A version of this article appeared in the July–August 2008 issue of Harvard

Business Review.

Andrew McAfee is the cofounder of the
Initiative on the Digital Economy in the MIT
Sloan School of Management. His next book,
The Geek Way: The Radical Mindset
Transforming the Future of Business, will be
published by Little, Brown in 2023.

Erik Brynjolfsson is the Jerry Yang and Akiko
Yamazaki Professor and a senior fellow at the
Stanford Institute for Human-Centered AI
(HAI), and is the director of the Stanford Digital
Economy Lab. He also is the Ralph Landau
Senior Fellow at the Stanford Institute for
Economic Policy Research (SIEPR), professor
by courtesy at the Stanford Graduate School of
Business and Stanford Department of
Economics, and a research associate at the
National Bureau of Economic Research.

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