Mckinsey Quarterly Issue 42011

Big dataYou have it, now use it.

2011 Number 4

2011 Number 4

This Quarter

Quietly, the volume of data that companies generate

and collect has soared in recent years. While the only

outward sign may be growth in the number of

servers needed to process and store data, the business

implications are profound.

This issue of McKinsey Quarterly provides a state-of-the-art CEOs

guide to navigating the era of big data. Building on McKinsey

Global Institute research released earlier this year, Brad Brown,

Michael Chui, and James Manyika present a series of questions

and thought-provoking examples intended to concentrate busy leaders

minds on the implications of big data. Several intriguing thinkers

and practitionersMassachusetts Institute of Technology professor

Erik Brynjolfsson, Cloudera cofounder Jeff Hammerbacher,

AstraZeneca senior executive Mark Lelinski, and Butler University

mens basketball coach Brad Stevensoffer their perspectives on

competing through data. And for executives ready to start creating a

big data strategy, McKinseys Jacques Bughin, John Livingston, and

Sam Marwaha present a road map for action based on the experiences

of companies on the cutting edge.

Several other quiet but potent forces run through this issue. Santa Fe

Institute professor W. Brian Arthur describes how a second

economy of machine-to-machine interactions is imperceptibly taking

root beneath the surface of the physical world, potentially overtak-

ing it in economic importance within the next 20 years. McKinseys

Joanna Barsh and Lareina Yee present research about the silent

killer of womens careersrarely acknowledged but widely held mind-

sets that often block the path to the C-suiteand suggest some

robust antidotes for companies that are serious about boosting the

number of women in their senior ranks. At a personal level, we all

know that honest feedback from colleagues can help us stay in touch.

But a cone of silence surrounds many CEOs and their top teams,

says Harvard Business School professor Robert S. Kaplan, who has some

pointed advice for turning up the volume.

Finally, a coalition of experts from McKinseys oil and gas, automotive,

strategy, and operations practices explores the implications of

another quiet trend: the historic rise of oil consumption in emerging

markets. While good news in that it reflects economic improvement for

millions, steadily rising demand could strain global supply capacity

in the years ahead. Well-coordinated regulatory and behavioral

changes throughout the world may get us through the crunch, say Scott

Nyquist and his colleagues. But an unexpected oil price spike is

also possible. Presented here are some no-regrets moves companies

can make now to prepare strategically and operationally.

Easy as it is for issues like these to get drowned out by the din of daily

battle, staying ahead of them may well make all the difference in

the years ahead. We hope this issue of the Quarterly helps you keep your

organization focused today on what will matter most tomorrow.

Allen P. Webb

Editor-in-Chief

On the cover

Big dataYou have it, now use it

Are you ready for the era of big data?

Competing through data: Three experts offer their game plans

Brad Brown, Michael Chui, and James Manyika

Radical customization, constant experimentation, and novel business models will be new hallmarks of competition as companies capture and analyze huge volumes of data. Heres what you should know.

MIT professor Erik Brynjolfsson, Cloudera cofounder Jeff Hammerbacher, and Butler University mens basketball coach Brad Stevens reflect on the power of data.

24

36

Features

48

60

Changing companies minds about women

Top executives need feedbackheres how they can get it

Joanna Barsh and Lareina Yee

Robert S. Kaplan

Leaders who are serious about getting more women into senior management need a hard-edged approach to overcome the invisible barriers holding them back.

As executives become more senior, they are less likely to receive constructive feedback on their performance or their strategy. To get it, they should call on their junior colleagues.

90

100

The second economy

The changing shape of US recessionsByron Auguste, Susan Lund, and James Manyika

Digitization is creating a second economy thats vast, automatic, and invisiblethereby bringing the biggest change since the Industrial Revolution.

Recovery time for US employment after recessions has increased dramatically over the last two decades.

Feature

72 Oils uncertain future What you need to know

Its possible, though far from certain,that oil prices will spike in the years ahead. Heres whyand how you can prepare.

Another oil shock?Tom Janssens, Scott Nyquist, and Occo Roelofsen

The automotive sectors road to greater fuel efficiencyRussell Hensley and Andreas Zielke

Anticipating economic headwindsJonathan Ablett, Lowell Bryan, and Sven Smit Building a supply chain that can withstand high oil pricesKnut Alicke and Tobias Meyer

Special report

74

78

84

87

Extra PointBig data for the CEO

Idea ExchangeReaders mix it up with authors of articles from McKinsey Quarterly2011 Number 3

Departments

McKinsey on the WebHighlights from our digital offerings

7 1208

Picture This

W. Brian Arthur

Cybersecurity: A senior executives guide

A new era for commodities

Seizing the potential of big data

Executive perspectiveAstraZenecas big data partnership

Freeing up the sales force for selling

How strategic is our technology agenda?

James Kaplan, Shantnu Sharma, and Allen Weinberg

Richard Dobbs, Jeremy Oppenheim, and Fraser Thompson

Jacques Bughin, John Livingston, and Sam Marwaha

Olivia Nottebohm, Tom Stephenson, and Jennifer Wickland

A changing corporate-technology landscape and more aggressive hackers make safeguarding valuable corporate data a top-management issue, not just an IT problem.

Cheap resources underpinned economic growth for much of the 20th century. The 21st will be different.

Companies are learning to use large-scale data gathering and analytics to shape strategy. Their experiences highlight the principlesand potentialof big data.

Mark Lelinski, an executive at the global drugmaker, explains how the company is using data to build customer relationships that focus on the total cost of care.

Most sales reps spend less than half of their time actually selling. By reshaping sales operations, companies can help them focus on their real job.

CEOs should shake up the technology debate to ensure that they capture the upside of technology-driven threats. Heres how.

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110

115

Leading Edge Applied Insight

A quick chat with the worlds biggest baker

Grupo Bimbo CEO Daniel Servitje ref lects on his companys growth in developed and emerging markets.

16

Sizing the Internets economic impact

Eric Hazan, James Manyika, and Matthieu Pelissie du Rausas

New McKinsey research underscores the magnitude of the Nets impact on global growth and corporate performance.

18

Brad Brown and Johnson Sikes

Editorial

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Spinning off businesses can have real advantages in creating value if executives understand how.

Finding the courage to shrink

McKinsey analyzed the potential impact on 33 industries. Two dimensions stood out: the plans effect on profit pools and on the competitive landscape.

An accompanying interactive exhibit offers a detailed look at industries, grouped by their common exposure to the plans potential impact.

Many boards have improved their structures and processes. But to become truly effective stewards of their companies, they must also instill the right mind-set and boardroom dynamics.

New McKinsey research estimates the impact of Internet search in the global economy, pinpointing the sources of value and the beneficiaries.

Other features:

Measuring the value of search

What Chinas five-year plan

means for business

Boards: When best practice isnt enough

Highlights from our digital offerings

Now available on mckinseyquarterly.com

Readers mix it up with authors of articles from McKinsey Quarterly 2011 Number 3

Idea Exchange8

Were all marketers nowThe cover package of our previous issue focused on the transform- ational changes under way in marketing, including an explosion of digital media, increasingly rich data, and organizational flux as companies seek to engage customers more effectively. Authors Tom French, Laura LaBerge, and Paul Magill of McKinsey continued exploring these issues with readers on mckinseyquarterly.com:

Cy HeidariPresident and CEO, ValueTelligence, New York, New York

While the approach is sensible for large-capitalization companies, it may not apply to small- and midcapitalization companies due to the added operational costs, even if they outsource their marketing activities.

Thinking small

McKinseys Laura LaBerge responds:Youre right to recognize the compressed challenge this environment presents to smaller companies, yet these firms also have unique opportunities. With less hierarchy to stifle cross-functional coordination, its easier for employees at smaller companies to wear several hats and embed marketing thinking across the organization. Its also easier for employees to share experiences with customers, gain clearer insights, and create a shared view of customer-engagement requirements. The need to prioritize more means these companies pick their battlegrounds carefully and leverage close customer relationships to better focus their efforts.

Cross-functional challengesJo MoffattManaging director, Woodreed, United Kingdom

The trouble with internal engagementwhich wasnt mentioned, even though brands help develop employees who can ensure a consistent consumer experienceis that HR and marketing tend to work in silos. They should harness each others strengths, fusing HRs people knowledge with marketings brand and customer expertise.

McKinseys Paul Magill responds:The HRmarketing disconnect is a tragedy at many companies, since the brand is central to both, but we are seeing several create pervasive strategies that bridge the internalexternal divide through planned and unplanned customer interactions. Planned inter-actions help identify top-priority touch points, and we increasingly see marketing working with HR to find frontline employees who arent always marketers but can still deliver a better customer experience. Unplanned interactions lead to the employee branding efforts you describe. A great example is when the two functions design, build, and deploy the brand internally, while marketing embeds the execution in HR. Here, the marketing function takes the kind of organization-wide, multistakeholder view of engage-ment we recommend, then divides up responsibility for executing the strategy.

To centralize or not to centralize?In our previous issue, McKinsey alumnus Andrew Campbell (now director of the London-based Ashridge Strategic Management Centre), along with Sven Kunisch and Gnter Mller-Stewens of the University of St. Gallen Institute of Management, suggested that executives use three questions to focus internal debate about centralization proposals: (1) Is centralization mandated? (2) Does it add 10 percent to market capitalization? (3) Are the risks low? Below, McKinseys Suzanne Heywood suggests some additional considerations, to which Campbell responds:

Suzanne HeywoodPrincipal, McKinsey & Company, London

In our experience, companies need to first determinebased on their sector, strategy, and growth historywhether they have an ingoing bias for or against centralization. Companies should then weigh the potential benefits and drawbacks that might arise from it. With a bias against centralization, some functional activities will still need to be centralized, but the benefits would have to outweigh the risks substantially; the opposite would be true if the bias were for centralization.

Second, its important to recognize that centralization may yield improve-mentssuch as enhancing knowledge sharing or minimizing operating riskthat are difficult to quantify in terms of a market-capitalization bench- mark. Finally, if companies do decide to centralize a function, they should also consider alternatives to structural change. In many cases, making softer changes (for example, standardizing processes, creating functional networks to bring people together) can also result in centralization-related benefits. It is wise to consider these mechanisms first and only implement structural change if they will clearly not be effective.

Andrew Campbell responds:You are right that benefits and drawbacks vary by business model and that many are qualitative. But its because so much of this assessment is qualitative that companies need to use a quantitative hurdle (such as the 10 percent market-capitalization rule) and be confident in the potential gains from centralization before assuming the risks. In my experience, qualitative assessments are too easily unbalanced by subjective arguments, so there is real value in the quantitative nature of question two.

With the softer changes, such as standardizing processes or bringing people together, its implied that these actions are not centralization and do not need to be judged against the same criteria. However, these actions do involve some degree of centralization. Who decides what the standard process should look like? Who decides whom to bring together, how often, and when? We should still bear in mind the three centralization questions and the hurdles this decision should cross when implementing less structural changes.

9

10 2011 Number 4

A rash of highly publicized IT security breaches that have struck sophisticated companies in

recent months has led many senior

executives to worry about how

safe their own corporate environ-

ments really are. Despite these

concerns, executives often

lack a clear sense of how to combat

the growing threats. As a result,

they are placing more pressure on

CIOs and IT security executives

to raise their companies technology

ramparts. But from our experience

and interviews with IT security exec-

utives at 25 top global companies,

we believe that technology tactics

alone are insufficient. To gain

ground against the hackers

in protecting information assets

such as business plans and

intellectual propertywithout

constraining business growth and

flexibilitycompanies must

adopt cybersecurity approaches

that require much more engagement

from the CEO and other senior

executives.

Why IT environments are harder to protectGreater volumes of online

transactions are creating enormous

incentives for cybercriminals.

Companies that mine transaction

data and customer information,

James Kaplan, Shantnu Sharma, and Allen Weinberg

A changing corporate-technology landscape and more aggressive hackers make safeguarding valuable corporate data a top-management issue, not just an IT problem.


Leading EdgeResearch, trends, and emerging thinking

10 13

16 18





11

from outside the IT organization.

They will be vital to help identify and

then champion business practice

changes that create intelligent con-

straints for employees, customers,

and partners. Senior leaders also

may need to arbitrate competing

demands: some business

units naturally might favor lighter

safeguards that raise the risk

of critical-data loss, while overly

stringent controls advocated

by IT leaders will get in the way of

doing business.

At one company we surveyed,

the CEO is now directly involved with

senior security executives in

making key decisions. Elsewhere,

security officers are embedded

in business units to facilitate

dialogue at the most meaningful

level. Some security leaders

now report to the risk committees

of company boards.

Address cybersecurity business

back, not technology forward

Many companies need to reverse

conventional thinking about security.

Rather than focus on vulnerable

technologies at the back end of

processes, they should first decide

which business assets must be

protected. Some large institutions

have launched multiyear programs

to classify their data troves and

better focus such efforts. Before

enhancing plans to collaborate,

other companies are scanning the

full value chain to clarify the

expectations of vendors about how

information will be exchanged.

Still others are starting with

customersthinking through, for

example, how to collect enough

information to verify their identity

for example, create new and

valuable stores of intellectual

property that are attractive targets.

Moreover, employees are demanding

access to corporate networks

from the same mobile devices they

use in their personal lives, creating

new crevices for hackers to exploit.

Another challenge: companies are

eager to optimize supply chains

by inducing vendors and customers

to join their corporate networks.

But in this way, they may be rendering

their own defenses more porous

and only as secure as those

of their weakest partner. One large

company, for example, barred its

employees from using peer-to-peer

software to share sensitive company

documents over the Web, only

to discover that on-site contractors

routinely used this software

to review the same documents.

Approaching security differentlyThe threats will only rise in com-

plexity and virulence, painful as that

may be for leaders to contemplate.

Professional cybercrime organi-

zations, political hacktivists, and

state-sponsored groups are ever

more technologically advanced, in

some cases outstripping the skills

and resources of corporate security

teams. (One hacker group provides

cybercrime as a service, receiving

payment for each end-user

device it infects with malware.) To

make business-led strategies

work, companies must undertake

the following steps.

Engage at the top

Meeting these challenges requires

the involvement of senior executives

12 2011 Number 4

without forcing them to spend too

much time signing on. Getting

this balance right, a critical element

of meeting the cybersecurity

challenge, can serve as a competi-

tive differentiator.

Protect the data, not the perimeter

Motivated attackers will always find

ways to penetrate the most

sophisticated corporate defenses.

Some companies are embracing

this reality by redesigning how they

house and regulate access to

data. If customer credit card infor-

mation, for example, resides in

a single database, a cybercriminal

must breach security only once

to profit. Separating credit card

numbers and expiration dates vastly

complicates a hackers task. At

some companies, plugging a laptop

into the system allows employees

to access only publicly available data;

viewing customer files or working

with corporate applications requires

a more rigorous, multistage

authentication of identity. Since

malicious insiders often pose

the greatest threat of all, some com-

panies limit, by specific roles

and functions, the number of people

who can access core production

systems and data.

Refresh strategies to address

evolving business needs and threats

CEOs fervently want to solve the

security problem, but it would

be more fruitful to acknowledge that

its an ongoing battle, so security

tactics must change constantly.

Advanced companies conduct sim-

ulated cyberattacks to identify

unexpected vulnerabilities and to

build the muscles needed to

manage breaches. Some have built

massive analytic capabilities

to sift though data such as e-mail

headers or to identify unusual IP

traffic patterns that could be warning

signs of emerging threats. Finally,

to ensure that cybersecurity is

sustainable, leaders need to make

it part of their business case

for entering new regions or investing

in new products and other major

initiatives.

Clearly, we are in the early days of

what will be a long war between

cybercriminals and global institutions

of all shapes and sizes. As in any

prolonged struggle, the combatants

will continually react and adapt.

No matter how an organizations

tactics evolve, leaders can boost the

odds of prevailing by developing

approaches that cut across commer-

cial strategy, operations, risk

management, and the legal and

technology functionssupported by

a mandate and active engagement

from the most senior level of

executives.

Allen Weinberg is a director in McKinseys New York office, where

James Kaplan is a principal; Shantnu Sharma is a consultant in the Boston office.

Copyright 2011 McKinsey & Company. All rights reserved. We welcome your comments on this article. Please send them to [email protected].

13Leading Edge

Has the global economy entered an era of persistently high,

volatile commodity prices? Our

research shows that during the past

eight years alone, they have

undone the decline of the previous

century, rising to levels not seen

since the early 1900s (exhibit).

In addition, volatility is now greater

than at any time since the oil-

shocked 1970s because commodity

prices increasingly move in lock-

step. Our analysis suggests that they

will remain high and volatile for

at least the next 20 years if current

trends holdbarring a major

macroeconomic shockas global

resource markets oscillate in

response to surging global demand

and inelastic supplies.

Demand for energy, food, metals,

and water should rise inexorably as

three billion new middle-class

consumers emerge in the next two

decades.1 The global car fleet,

for example, is expected almost to

double, to 1.7 billion, by 2030.

In India, we expect calorie intake per

person to rise by 20 percent during

that period, while per capita meat

consumption in China could

increase by 60 percent, to 80 kilo-

grams (176 pounds) a year. Demand

for urban infrastructure also

will soar. China, for example, could

annually add floor space totaling

2.5 times the entire residential and

commercial square footage of

the city of Chicago, while India could

add floor space equal to another

Chicago every year.

Such dramatic growth in demand

for commodities actually isnt

unusual. Similar factors were at play

throughout the 20th century as

the planets population tripled

and demand for various resources

jumped anywhere from 600 to

2,000 percent. Had supply remained

constant, commodity prices

would have soared. Yet dramatic

improvements in exploration,

extraction, and cultivation techniques

kept supply ahead of ever-

increasing global needs, cutting the

real price of an equally weighted

index of key commodities by

almost half. This ability to access

progressively cheaper resources

underpinned a 20-fold expansion of

the world economy.

There are three differences today.

First, we are now aware of the

Richard Dobbs, Jeremy Oppenheim, and Fraser Thompson

Cheap resources underpinned economic growth for much of the 20th century. The 21st will be different.


14 2011 Number 4

potential climatic impact of carbon

emissions associated with surging

resource use. Without major

changes, global carbon emissions

will remain significantly above

the level required to keep increases

in the global temperature below

2 degrees Celsiusthe threshold

identified as potentially catastrophic.2

Second, its becoming increasingly

difficult to expand the supply

of commodities, especially in the

short run. While there may not

be absolute resource shortages

the perceived risk of one has his-

torically spurred efficiency-

enhancing innovationswe are

at a point where supply is

increasingly inelastic. Long-term

marginal costs are increasing

for many resources as depletion

rates accelerate and new invest-

ments are made in more complex,

less productive locations.

Third, the linkages among resources

are becoming increasingly

important. Consider, for example,

the potential ripple effects

of water shortfalls at a time when

roughly 70 percent of all water

is consumed by agriculture and

12 percent by energy production. In

In little more than a decade, commodity prices have soared from historic lows to new highs.

Q4 2011MGI commoditiesExhibit 1 of 1

McKinsey Global Institute commodity price index (average of 19992001 = 100)1

World War I

World War II 1970s oil shock

Postwar depression Great

Depression

260

1900 1910 19301920 1940 1950 1960 1970 1980 1990 2000 2010 20112

240

220

200

180

160

140

120

100

80

60

0

1 Based on arithmetic average of 4 commodity indexes: food, agricultural raw materials, metals, and energy. Each index was weighted by total world export volumes from 1999 to 2001 at indexed prices (in real terms) over same time period. Energy index excludes gas prices prior to 1922, for which data are unavailable.

2Based on average of first 4 months of 2011.

Source: FAOSTAT (Food and Agriculture Organization of the United Nations); Grilli and Yang commodity price index, 1988; International Monetary Fund (IMF) primary commodity prices; Organisation for Economic Co-operation and Development; Stephan Pfaenzeller et al., A short note on updating the Grilli and Yang commodity price index, World Bank Economic Review, 2007, Volume 21, Number 1, pp. 15163; World Bank commodity price data; UN Comtrade; McKinsey Global Institute analysis

In little more than a decade, soaring commodity prices have erased a century of steady declines.

15Leading Edge

Uganda, water shortages have

led to escalating energy prices, which

led to the use of more wood

fuels, which led to deforestation and

soil degradation that threatened

the food supply.

Higher commodity prices are one

way of bringing supply and demand

nearer to balancebut not a

desirable means for most policy

makers and business leaders,

since lofty prices can drag down

profits and growth (for more,

see Anticipating economic head-

winds, on page 84). Another

approach is to squeeze greater

productivity from natural resources

by, for example, improving mining

recovery rates, making households

more energy efficient, and

capturing and reusing wastewater.

Our researchsummarized

in a forthcoming McKinsey Global

Institute report on the worlds

natural-resource needs in the 21st

centurysuggests that better

resource productivity could single-

handedly meet more than 20 per-

cent of forecast 2030 demand for

energy, steel, water, and land. In

addition, higher long-term resource

prices might create the necessary

incentive for breakthroughs,

especially around energy-related

technologies that could reduce

carbon emissions (for more on this

topic, see Another oil shock? on

page 74). More will need to be done,

of course, and were not suggesting

that its easy; major policy, behavioral,

and institutional barriers must

be addressed. Yet as we enter a new

era for commodities, theres little

choice but to act.

Richard Dobbs is a director of the McKinsey Global Institute

(MGI) and a director in McKinseys

Seoul office; Jeremy Oppenheim is a director in the London office;

Fraser Thompson is a senior fellow at MGI and is based in the

London office.


1 See David Court and Laxman Narasimhan, Capturing the worlds emerging middle class, mckinseyquarterly.com, July 2010.

2 The Stern Review on the Economics of Climate Change, released in 2006, and the International Panel on Climate Change (IPCC) claim that an increase in temperatures of more than 2 degrees Celsius (3.6 degrees Fahrenheit) above those of preindustrial times could cut GDP by up to 20 percent, force more than a billion people to migrate, make many species extinct, threaten major cities as a result of rising seas, and decrease agricultural yields, putting pressure on food (and fuel) supplies. Major changes in energy production and usage could lower carbon emissions to keep temperatures below that threshold.

Grupo Bimbo CEO Daniel Servitje reflects on his companys growth in developed and emerging markets.


What is the worlds largest baker? Guess again if you didnt say Grupo Bimbo, the Mexican

packaged-goods company that has

become a global player in the

food marketplace. Grupo Bimbo has

its highest sales in Mexico and the

United States (penetrated primarily

through a few big acquisitions,

most recently of Sara Lees fresh-

baked-goods unit, for which it is

awaiting regulatory approval). It also

operates throughout Latin America

and in China.

Daniel Servitje, the 52-year-old

son of the companys founder, has

served as CEO since 1997.

During that time, sales have more

than quintupled and profitability

has improved. In this excerpt

from an interview with McKinseys

Alejandro Diaz, Mr. Servitje

discussed Grupo Bimbos geo-

graphical expansion, the challenges

that engendered, and how

the companys origins as a family

business aided its growth.

The Quarterly: How do the companys emerging-market

roots differentiate you from

other multinational companies?

Daniel Servitje: Were probably looking at things from a different

perspective, from the ground upa

little bit more humble and more

focused on economic uncertainties.

We suffered a lot during the

devaluations and economic crises

in the 1980s and 1990s. Thats

still part of our baggage when we

analyze the situation in other

countries. Also, we have always

tried to understand the market

on a local and regional basis; it might

be just one or two cities. Bread

cannot travel for long distances,

which forces us to have a

very localized, fine-tuned view

of markets.

The Quarterly: Grupo Bimbo is testing the waters in China. How

is it going?

Daniel Servitje: Ive been surprised. I thought it was going to

be much more complicated

for a Latin American company to

develop its businessto replicate

our business modelin China.

Surprisingly, it has not been

as difficult as I had expected, and

even less difficult than what we

would find in other Latin American

countries. The challenge in China

is to develop the bread market as a

category. Thats where we are

still doing a lot of work.

The Quarterly: Can you say a little more about the challenges you

have experienced in Latin America?

16 2011 Number 4

Daniel Servitje: When we entered the market in Latin America,

we thought that there were a lot of

similarities to our culture and

our business system. Some things

worked out very well, and many

things were disasters. A few years

ago, we did an acquisition in

Central America that we thought was

a simple one. But it ended up

being very complex; we did not really

achieve the benefits that we had

hoped for. Even though we speak

Spanish and we understand

the culture, the labor rules and the

complexities of each market can

get us to a very different place. We

learned our lessons the hard way in

that case. From that circumstance,

weve tried to develop a more

thorough approach to our M&A due

diligence and to be more sensitive

to the complexities of labor.

Despite the hurdles, we have

become the leading baking player in

Brazil. But our challenge there is

to find the right model to penetrate

the traditional mom-and-pop

segment, which is quite different

from what we find in other Latin

American countries.

The Quarterly: Grupo Bimbo has been a public company

for 30 years but still has a family

business orientation. How is

that an advantage?

Daniel Servitje: We see things with a longer time perspective and

base our decisions on a larger

time horizon. That allows us to view

things with a perspective very

different from the ones that we see

in many multinationals. For

example, we lost money for more

than ten years in our Mexican

snack business. We kept on building

our base, gaining more knowledge

of the business, and scaling up our

company until we turned it around.

Now its a very viable business.

Our company has been growing

by about 10 percent compounded

annually for many yearsfour

to five times the GDP growth of

Mexico and the United States. We

have been blessed because

weve focused on a strict number

of categories and built a very

strong distribution network in many

countries. We also had a high aim

of becoming an international player

and the commitment of our

board to sustain this strategy for

many years. If we had not been

willing to reinvest in the businesses

in difficult times, certainly

this strategy wouldnt have been

successful.

Alejandro Diaz is a director in McKinseys Dallas office.


17Leading Edge

View the full interview, The making of an emerging-market champion, on mckinseyquarterly

.com.

Daniel Servitje CEO of Grupo Bimbo

18 2011 Number 4

Eric Hazan, James Manyika, and Matthieu Pelissie du Rausas

New McKinsey research underscores the magnitude of the Nets impact on global growth and corporate performance.


The Internet has profoundly changed the workings of the global economy. Yet a precise

measure of the magnitude of the

Internets impact, whether at

the level of national economies or

of individual firms, has remained

elusive. In an effort to quantify

the Internets effect on economic

activity, McKinsey examined

national-account data of 13 nations

that account for 70 percent of

global GDP. We also surveyed 4,800

small and medium-sized enter-

prises in 12 countries on their use

of the Internet and its effect on

their performance. Econometric

analyses of both macro- and micro-

economic data provided rein-

forcing evidence of the Internets

sizable and expanding influence on

global and corporate growth.

The growth dividend for countries . . . At the highest level, we found that

the Internet now accounts for 3.4 per-

cent of GDP across the economies

we studied, ranging from highs of

5 to more than 6 percent in Sweden

and the United Kingdom, where

consumers and corporations alike

are heavy users, to less than

1.5 percent in Brazil and Russia,

where adoption is weaker.1

The sources of this activity include

private consumption (from

online commerce to smartphone

purchases); investment by

companies in software, servers,

and communications gear; and

public investments in areas such as

Internet infrastructure. If measured

as a global industry unto itself,

the Internet now contributes more to

GDP than education, agriculture,

or utilities do.

The magnitude of its impact is likely

to increase, because the Internets

contribution to global economic

growth is accelerating: from 2005 to

2009, it accounted for 21 percent

of the combined GDP growth of nine

developed economies we studied.

That was more than double the

growth contribution over a longer

(14-year) period from 1995 to 2009.

The Net is also propelling growth

in less mature economies, such as

China and India, though so far

at a more moderate pace (Exhibit 1).

19Leading Edge

The Internets contribution to global economic growth is accelerating.

Q4 2011Internet growthExhibit 1 of 2

Internets contribution to global GDP growth, %

Nominal GDP growth,1 19952009, %

Mature countries

High-growth countries

1In local currencies.2 Negative growth due to inflation.

Source: Organisation for Economic Co-operation and Development national accounts; McKinsey Global Institute analysis

The Internets contribution to global economic growth is accelerating.

Sweden 3.915 33

Germany 1.914 24

United Kingdom 4.711 23

France 3.410 18

South Korea 7.07 16

United States 4.78 15

Italy 3.44 12

Canada 4.66 10

Japan N/A2 0.3

India 13.145

China 9.533

Brazil 10.722

Russia 26.711

Over 14 years, 19952009

Over more recent 5 years, 200409

Moreover, our study indicates that

the Internets net impact on jobs

has been positive: for every position

eliminated through productivity

gains associated with it, 2.6 are

created. This finding is confirmed in

a detailed study of France, as

well as a survey of 4,800 small and

medium-sized enterprises

we conducted in 12 countries.

Finally, our study also shows that

Internet maturitymeasured

by a variety of factors characterizing

a countrys Internet use, infra-

structure, online expenditures, and

20 2011 Number 4

Small and medium-sized enterprises that use Web technologies extensively are growing more quickly and exporting more widely.

Q4 2011Internet growthExhibit 2 of 2

Small and medium-sized enterprises

Annual growth over last 3 years, %

Enterprises grouped by degree of Web-technology utilization1

Export revenues as % of total sales

1 Based on number of technologies possessed by companies and number of employees, customers, and suppliers with access to those technologies.

Source: May 2011 McKinsey survey of >4,800 small and medium-sized enterprises in 12 countries; McKinsey Global Institute analysis

Small and medium-sized enterprises that use Web technologies extensively are growing more quickly and exporting more widely.

Low (42% of respondents)

6.2 2.5

Medium(31% of respondents)

7.4 2.7

High(27% of respondents)

13.0 5.3

e-commercecorrelates with

standard-of-living improvements,

measured in terms of GDP per

capita. We also found higher growth

rates for labor productivity in

nations such as the United States,

where Internet usage and infra-

structure were more mature, and

a correlation between highly

developed Internet ecosystems and

higher GDP growth rates.

. . . and for companiesOur global research on small and

medium-sized enterprises also

indicates that companies with two

characteristicsemploying larger

numbers of Internet technologies

(such as blogs, social networks,

and e-commerce sites) and

enjoying high rates of adoption

among employees, customers, and

suppliersrecorded revenue

growth of 13 percent over the last

three years, twice the rate of

companies with lower levels of

Internet adoption. Furthermore, the

profit levels of these Internet-

intense companies were 10 percent

higher than those of less intense

Web users, and the rate at which

they added workers was twice as

high. While its impossible

to say definitively which way the

causation runs, our research

does suggest greater efficiency

at the more Internet-intense

companies (their cost of goods sold

and administrative costs were

lower) and, as Exhibit 2 shows,

a stronger ability to expand market

reach (export revenues were

markedly higher).

The 10 percent profitability advan-

tage enjoyed by heavy Internet

users represents a significant global

profit pool. Companies that supply

21Leading Edge

infrastructure, a business environ-

ment that combines moderate

regulation with protections for intel-

lectual capital, and strong

educational and training programs

that foster technical skillshave

more companies among the ranks

of global Internet suppliers.

Each of these four policy areas

offers plenty of space for committed

executives and policy makers to

collaborate for improvements.

The authors would like to thank

Jacques Bughin, Michael Chui,

Vincent Luciani, and Remi Said for

their contributions to this research.

Eric Hazan is a principal in McKinseys Paris office, where

Matthieu Pelissie du Rausas is a director; James Manyika is a director of the McKinsey Global

Institute and a director in the

San Francisco office.


1 The size of the Internet economy represents the sum of Internet consumption (of which service, access, and e-commerce are key elements), private investment, public expenditure, and the trade balance in Web-related goods and services.

2 For more see Michael Chui, Markus Lffler, and Roger Roberts, The Internet of Things, mckinseyquarterly.com, March 2010.

hardware, software, and services to

the global Internet ecosystem claim

one-quarter of that pool. Leading

this Internet supply network of

250 firms are companies in Japan,

Sweden, and the United States.

Rising in influence are China and

India: as they develop more potent

export players, their Internet

supply sectors are growing at four

and five times, respectively, the

rate of the US industry.

Stoking future growth As business leaders establish

strategic priorities amid rapid, Web-

related change, they should look

for opportunities to:

reinventbusinessmodels to capture productivity and perfor-

mance improvements unlocked

by the Internet

exploitemergingWebtrends, such as the Internet of Things,2 in

which chips create highly

efficient networks from almost

any physical product

embracenew,flexibleorgani-zational structures enabled by

Web networks that link

employees, customers, and

business partners

Leaders also should focus on

emerging opportunities in countries

that are still getting up the Internet

growth curve. Those countries

can make big strides toward tapping

into more of the Internet economys

benefits, our research suggests.

We found that countries with four

characteristicseasy access to

start-up capital, a solid broadband

Big dataYou have it, now use it.

22

24

Are you ready for the

era of big data?

Brad Brown, Michael Chui,

and James Manyika

36

Competing through

data: Three experts offer

their game plans

With data flooding into your company

as never before, information is no

longer just an IT issue; its yours as a

senior leader. Maybe your company

is sitting on powerful data assets that

could strengthen its ability to compete,

or perhaps theres a competitor thats

suddenly aiming a big data strategy

right at you. In our first story, find out

why mastering data and analytics is now

mission critical, and ask yourself five

questions that will help you understand

looming competitive challenges. Then

turn to a leading academic expert, a

data entrepreneur, and a top college

basketball coach who zero in on how you

can use data to compete.

23

Art

wor

k by

Cel

ia J

ohns

on

24

The top marketing executive at a sizable US retailer recently

found herself perplexed by the sales reports she was getting. A major

competitor was steadily gaining market share across a range of

profitable segments. Despite a counterpunch that combined online

promotions with merchandizing improvements, her company kept

losing ground.

When the executive convened a group of senior leaders to dig into the

competitors practices, they found that the challenge ran deeper than

they had imagined. The competitor had made massive investments in

its ability to collect, integrate, and analyze data from each store

and every sales unit and had used this ability to run myriad real-world

experiments. At the same time, it had linked this information to

suppliers databases, making it possible to adjust prices in real time, to

reorder hot-selling items automatically, and to shift items from

store to store easily. By constantly testing, bundling, synthesizing, and

making information instantly available across the organization

from the store floor to the CFOs officethe rival company had become

a different, far nimbler type of business.

What this executive team had witnessed first hand was the game-

changing effects of big data. Of course, data characterized the information

age from the start. It underpins processes that manage employees;

it helps to track purchases and sales; and it offers clues about how

customers will behave.

Radical customization, constant experimentation,

and novel business models will be new

hallmarks of competition as companies capture

and analyze huge volumes of data. Heres

what you should know.


Brad Brown, Michael Chui, and James Manyika

25

But over the last few years, the volume of data has exploded. In 15 of

the US economys 17 sectors, companies with more than 1,000

employees store, on average, over 235 terabytes of datamore data

than is contained in the US Library of Congress. Reams of data

still flow from financial transactions and customer interactions but

also cascade in at unparalleled rates from new devices and multiple

points along the value chain. Just think about what could be hap-

pening at your own company right now: sensors embedded in process

machinery may be collecting operations data, while marketers scan

social media or use location data from smartphones to understand teens

buying quirks. Data exchanges may be networking your supply

chain partners, and employees could be swapping best practices on

corporate wikis.

All of this new information is laden with implications for leaders and

their enterprises.1 Emerging academic research suggests that com-

panies that use data and business analytics to guide decision making

are more productive and experience higher returns on equity than

competitors that dont.2 Thats consistent with research weve conducted

showing that networked organizations can gain an edge by opening

information conduits internally and by engaging customers and sup-

pliers strategically through Web-based exchanges of information.3

Over time, we believe big data may well become a new type of corporate

asset that will cut across business units and function much as a

powerful brand does, representing a key basis for competition. If thats

right, companies need to start thinking in earnest about whether

they are organized to exploit big datas potential and to manage the

threats it can pose. Success will demand not only new skills but also

new perspectives on how the era of big data could evolvethe widening

circle of management practices it may affect and the foundation it

represents for new, potentially disruptive business models.

1 For more, see the McKinsey Global Institute report Big data: The next frontier for innovation, competition, and productivity, available free of charge online at mckinsey.com/mgi.

2 See Erik Brynjolfsson, Lorin M. Hitt, and Heekyung Hellen Kim, Strength in numbers: How does data-driven decisionmaking affect firm performance? Social Science Research Network (SSRN), April 2011. In this study, the authors found that effective use of data and analytics correlated with a 5 to 6 percent improvement in productivity, as well as higher profitability and market value. For more, see the forthcoming e-book by Brynjolfsson and coauthor Andrew McAfee, Race Against the Machine: How the digital revolution accelerates innovation, drives productivity, and irreversibly transforms employment and the economy (Digital Frontier Press, October 2011).

3 See Jacques Bughin and Michael Chui, The rise of the networked enterprise: Web 2.0 finds its payday, mckinseyquarterly.com, December 2010.

26 2011 Number 4

Five big questions about big data

In the remainder of this article, we outline important ways big data

could change competition: by transforming processes, altering

corporate ecosystems, and facilitating innovation. Weve organized the

discussion around five questions we think all senior executives

should be asking themselves today.

At the outset, well acknowledge that these are still early days for big

data, which is evolving as a business concept in tandem with the under-

lying technologies. Nonetheless, we can identify big datas key ele-

ments. First, companies can now collect data across business units and,

increasingly, even from partners and customers (some of this is truly

big, some more granular and complex). Second, a flexible infrastructure

can integrate information and scale up effectively to meet the surge.

Finally, experiments, algorithms, and analytics can make sense of all

this information. We also can identify organizations that are making

data a core element of strategy. In the discussion that follows and else-

where in this issue, we have assembled case studies of early movers in

the big data realm (see Seizing the potential of big data, on page 103,

and the accompanying sidebar, AstraZenecas big data partnership,

on page 104).

In addition, wed suggest that executives look to history for clues about

whats coming next. Earlier waves of technology adoption, for example,

show that productivity surges not only because companies adopt new

technologies but also, more critically, because they can adapt their man-

agement practices and change their organizations to maximize the

potential. We examined the possible impact of big data across a number

of industries and found that while it will be important in every sector

and function, some industries will realize benefits sooner because they

are more ready to capitalize on data or have strong market incentives

to do so (see sidebar, Parsing the benefits: Not all industries are

created equal).

The era of big data also could yield new management principles. In

the early days of professionalized corporate management, leaders dis-

covered that minimum efficient scale was a key determinant of

competitive success. Likewise, future competitive benefits may accrue

to companies that can not only capture more and better data but

also use that data effectively at scale. We hope that by ref lecting on

such issues and the five questions that follow, executives will be

27Are you ready for the era of big data?

better able to recognize how big data could upend assumptions

behind their strategies, as well as the speed and scope of the change

thats now under way.

What happens in a world of radical transparency, with data widely available? As information becomes more readily accessible across sectors, it can

threaten companies that have relied on proprietary data as a com-

petitive asset. The real-estate industry, for example, trades on infor-

mation asymmetries such as privileged access to transaction data

and tightly held knowledge of the bid and ask behavior of buyers. Both

require significant expense and effort to acquire. In recent years,

however, online specialists in real-estate data and analytics have started

to bypass agents, permitting buyers and sellers to exchange perspec-

tives on the value of properties and creating parallel sources for real-

estate data.

Beyond real estate, cost and pricing data are becoming more accessible

across a spectrum of industries. Another swipe at proprietary infor-

mation is the assembly by some companies of readily available satellite

imagery that, when processed and analyzed, contains clues about

competitors physical facilities. These satellite sleuths glean insights

into expansion plans or business constraints as revealed by facility

capacity, shipping movements, and the like.

One big challenge is the fact that the mountains of data many companies

are amassing often lurk in departmental silos, such as R&D, engi-

neering, manufacturing, or service operationsimpeding timely exploi-

tation. Information hoarding within business units also can be a

problem: many financial institutions, for example, suffer from their own

failure to share data among diverse lines of business, such as financial

markets, money management, and lending. Often, that prevents these

companies from forming a coherent view of individual customers or

understanding links among financial markets.

Some manufacturers are attempting to pry open these departmental

enclaves: they are integrating data from multiple systems, inviting

collaboration among formerly walled-off functional units, and even

seeking information from external suppliers and customers to

cocreate products. In advanced-manufacturing sectors such as auto-

motive, for example, suppliers from around the world make thou-

1

(continued on page 30)

Parsing the benefits: Not all industries are created equal

Even as big data changes the

game for virtually every sector, it

also tilts the playing field, favoring

some companies and industries,

particularly in the early stages of

adoption. To understand those

dynamics, we examined 20 sectors

in the US economy, sized their

contributions to GDP, and devel-

oped two indexes that estimate

each sectors potential for value

creation using big data, as well

as the ease of capturing that value.1

As the accompanying sector map

shows (exhibit), financial players

get the highest marks for value crea-

tion opportunities. Many of these

companies have invested deeply in

IT and have large data pools to

exploit. Information industries, not

surprisingly, are also in this league.

They are data intensive by nature,

and they use that data innovatively

to compete by adopting sophis-

ticated analytic techniques.

The public sector is the most fertile

terrain for change. Governments

collect huge amounts of data, trans-

act business with millions of

citizens, and, more often than not,

suffer from highly variable perform-

ance. While potential benefits are

large, governments face steep bar-

riers to making use of this trove:

few managers are pushed to exploit

the data they have, and govern-

ment departments often keep data

in siloes.

Fragmented industry structures

complicate the value creation poten-

tial of sectors such as health

care, manufacturing, and retailing.

The average company in them is

relatively small and can access only

limited amounts of data. Larger

players, however, usually swim in

bigger pools of data, which they

can more readily use to create value.

The US health care sector, for

example, is dotted by many small

companies and individual physi-

cians practices. Large hospital

chains, national insurers, and

drug manufacturers, by contrast,

stand to gain substantially through

the pooling and more effective

analysis of data. We expect this

trend to intensify with changing

regulatory and market conditions.

In manufacturing, too, larger

companies with access to much

internal and market data will be

able to mine new reservoirs of value.

Smaller players are likely to benefit

only if they discover innovative

ways to share data or grow through

industry consolidation. The same

goes for retailing, wheredespite

a healthy strata of data-rich

chains and big-box stores on

the cutting edge of big data

28 2011 Number 4


most players are smaller, local

businesses with a limited ability to

gather and analyze information.

A final note: this analysis is a snap-

shot in time for one large country.

As companies and organizations

sharpen their data skills, even

low-ranking sectors (by our gauges

of value potential and data capture),

such as construction and education,

could see their fortunes change.

Q4 2011Big data sidebar on sector productivityExhibit 1 of 1

Big

dat

a: e

ase-

of-

cap

ture

ind

ex1

Big data: value potential index1

The ease of capturing big datas value, and the magnitude of its potential, vary across sectors.

Utilities

Manufacturing

Health care providersNatural resources

Example: US economy

Professional services

Construction

Administrative services

Management of companies

Computers and other electronic products

Transportation and warehousing

Real estate

Wholesale trade

Finance and insurance

Information

Other services

Retail trade

Accommodation and food

Educational services

Arts and entertainment

Government

High

Low High

1 For detailed explication of metrics, see appendix in McKinsey Global Institute full report Big data: The next frontier for innovation, competition, and productivity, available free of charge online at mckinsey.com/mgi.

Source: US Bureau of Labor Statistics; McKinsey Global Institute analysis

Size of bubble indicates relative contribution to GDP

29

1 The big data value potential index takes into account a sectors competitive conditions, such as market turbulence and performance variability; structural factors, such as transaction intensity and the number of potential customers and business partners; and the quantity of data available. The ease-of-capture index takes stock of the number of employees with deep analytical talent in an industry, baseline investments in IT, the accessibility of data sources, and the degree to which managers make data-driven decisions.

30 2011 Number 4

sands of components. More integrated data platforms now allow com-

panies and their supply chain partners to collaborate during the

design phasea crucial determinant of final manufacturing costs.

If you could test all of your decisions, how would that change the way you compete? Big data ushers in the possibility of a fundamentally different type

of decision making. Using controlled experiments, companies can

test hypotheses and analyze results to guide investment decisions

and operational changes. In effect, experimentation can help managers

distinguish causation from mere correlation, thus reducing the var-

iability of outcomes while improving financial and product performance.

Robust experimentation can take many forms. Leading online companies,

for example, are continuous testers. In some cases, they allocate a set

portion of their Web page views to conduct experiments that reveal what

factors drive higher user engagement or promote sales. Companies

selling physical goods also use experiments to aid decisions, but big data

can push this approach to a new level. McDonalds, for example, has

equipped some stores with devices that gather operational data as they

track customer interactions, traffic in stores, and ordering patterns.

Researchers can model the impact of variations in menus, restaurant

designs, and training, among other things, on productivity and sales.

Where such controlled experiments arent feasible, companies can use

natural experiments to identify the sources of variability in perfor-

mance. One government organization, for instance, collected data on

multiple groups of employees doing similar work at different sites.

Simply making the data available spurred lagging workers to improve

their performance.

A next-generation retailer will be able to track the behavior of individual customers from Internet click streams, update their preferences, and model their likely behavior in real time.

2


Leading retailers, meanwhile, are monitoring the in-store movements

of customers, as well as how they interact with products. These retailers

combine such rich data feeds with transaction records and conduct

experiments to guide choices about which products to carry, where to

place them, and how and when to adjust prices. Methods such as

these helped one leading retailer to reduce the number of items it stocked

by 17 percent, while raising the mix of higher-margin private-label

goodswith no loss of market share.

How would your business change if you used big data for widespread, real-time customization?Customer-facing companies have long used data to segment and target

customers. Big data permits a major step beyond what until recently

was considered state of the art, by making real-time personalization pos-

sible. A next-generation retailer will be able to track the behavior of

individual customers from Internet click streams, update their preferences,

and model their likely behavior in real time. They will then be able

to recognize when customers are nearing a purchase decision and nudge

the transaction to completion by bundling preferred products, offered

with reward program savings. This real-time targeting, which would also

leverage data from the retailers multitier membership rewards pro-

gram, will increase purchases of higher-margin products by its most

valuable customers.

Retailing is an obvious place for data-driven customization because

the volume and quality of data available from Internet purchases,

social-network conversations, and, more recently, location-specific

smartphone interactions have mushroomed. But other sectors,

too, can benefit from new applications of data, along with the growing

sophistication of analytical tools for dividing customers into more

revealing microsegments.

One personal-line insurer, for example, tailors insurance policies for

each customer, using fine-grained, constantly updated profiles of

customer risk, changes in wealth, home asset value, and other data inputs.

Utilities that harvest and analyze data on customer segments can

markedly change patterns of power usage. Finally, HR departments

that more finely segment employees by task and performance are

beginning to change work conditions and implement incentives that

improve both satisfaction and productivity.4

3

4 See Nora Gardner, Devin McGranahan, and William Wolf, Question for your HR chief: Are we using our people data to create value? mckinseyquarterly.com, March 2011.

32 2011 Number 4

How can big data augment or even replace management? Big data expands the operational space for algorithms and machine-

mediated analysis. At some manufacturers, for example, algorithms

analyze sensor data from production lines, creating self-regulating

processes that cut waste, avoid costly (and sometimes dangerous) human

interventions, and ultimately lift output. In advanced, digital oil

fields, instruments constantly read data on wellhead conditions, pipe-

lines, and mechanical systems. That information is analyzed by clus-

ters of computers, which feed their results to real-time operations centers

that adjust oil flows to optimize production and minimize downtimes.

One major oil company has cut operating and staffing costs by 10 to

25 percent while increasing production by 5 percent.

Products ranging from copiers to jet engines can now generate data

streams that track their usage. Manufacturers can analyze the incoming

data and, in some cases, automatically remedy software glitches or

dispatch service representatives for repairs. Some enterprise computer

hardware vendors are gathering and analyzing such data to schedule

preemptive repairs before failures disrupt customers operations. The

data can also be used to implement product changes that prevent

future problems or to provide customer use inputs that inform next-

generation offerings.

Some retailers are also at the forefront of using automated big data

analysis: they use sentiment analysis techniques to mine the huge

streams of data now generated by consumers using various types

of social media, gauge responses to new marketing campaigns in real

time, and adjust strategies accordingly. Sometimes these methods

cut weeks from the normal feedback and modification cycle.

But retailers arent alone. One global beverage company integrates

daily weather forecast data from an outside partner into its demand

and inventory-planning processes. By analyzing three data points

temperatures, rainfall levels, and the number of hours of sunshine on

a given daythe company cut its inventory levels while improving

its forecasting accuracy by about 5 percent in a key European market.

The bottom line is improved performance, better risk management,

and the ability to unearth insights that would otherwise remain hidden.

As the price of sensors, communications devices, and analytic soft-

ware continues to fall, more and more companies will be joining this

managerial revolution.

4


Could you create a new business model based on data?Big data is spawning new categories of companies that embrace

information-driven business models. Many of these businesses play

intermediary roles in value chains where they find themselves

generating valuable exhaust data produced by business transactions.

One transport company, for example, recognized that in the course

of doing business, it was collecting vast amounts of information on

global product shipments. Sensing opportunity, it created a unit

that sells the data to supplement business and economic forecasts.

Another global company learned so much from analyzing its own

data as part of a manufacturing turnaround that it decided to create

a business to do similar work for other firms. Now the company

aggregates shop floor and supply chain data for a number of manu-

facturing customers and sells software tools to improve their

performance. This service business now outperforms the companys

manufacturing one.

Big data also is turbocharging the ranks of data aggregators, which

combine and analyze information from multiple sources to generate

insights for clients. In health care, for example, a number of new

entrants are integrating clinical, payment, public-health, and behavioral

data to develop more robust illness profiles that help clients manage

costs and improve treatments.

And with pricing data proliferating on the Web and elsewhere, entre-

preneurs are offering price comparison services that automatically

compile information across millions of products. Such comparisons

can be a disruptive force from a retailers perspective but have created

substantial value for consumers. Studies show that those who use the

services save an average of 10 percenta sizable shift in value.

Confronting complications

Up to this point, we have emphasized the strategic opportunities big

data presents, but leaders must also consider a set of complications.

Talent is one of them. In the United States alone, our research shows,

the demand for people with the deep analytical skills in big data

(including machine learning and advanced statistical analysis) could

outstrip current projections of supply by 50 to 60 percent. By 2018,

as many as 140,000 to 190,000 additional specialists may be required.

5

34 2011 Number 4

Also needed: an additional 1.5 million managers and analysts with a

sharp understanding of how big data can be applied. Companies must

step up their recruitment and retention programs, while making sub-

stantial investments in the education and training of key data personnel.

The greater access to personal information that big data often demands

will place a spotlight on another tension, between privacy and con-

venience. Our research, for example, shows that consumers capture a

large part of the economic surplus that big data generates: lower

prices, a better alignment of products with consumer needs, and life-

style improvements that range from better health to more fluid social

interactions.5 As a larger amount of data on the buying preferences,

health, and finances of individuals is collected, however, privacy

concerns will grow.

Thats true for data security as well. The trends weve described often

go hand in hand with more open access to information, new devices

for gathering it, and cloud computing to support big datas weighty

storage and analytical needs. The implication is that IT architectures

will become more integrated and outward facing and will pose greater

risks to data security and intellectual property. For some ideas on how

leaders should respond, see Cybersecurity: A senior executives guide,

on page 10.

Although corporate leaders will focus most of their attention on big

datas implications for their own organizations, the mosaic of company-

level opportunities we have surveyed also has broader economic

5 See Jacques Bughin, The Webs 100 billion surplus, mckinseyquarterly.com, January 2011.


implications. In health care, government services, retailing, and manu-

facturing, our research suggests, big data could improve productivity

by 0.5 to 1 percent annually. In these sectors globally, it could produce

hundreds of billions of dollars and euros in new value.

In fact, big data may ultimately be a key factor in how nations, not just

companies, compete and prosper. Certainly, these techniques offer

glimmers of hope to a global economy struggling to find a path toward

more rapid growth. Through investments and forward-looking poli-

cies, company leaders and their counterparts in government can capi-

talize on big data instead of being blindsided by it.


Brad Brown is a director in McKinseys New York Office; Michael Chui

is a senior fellow with the McKinsey Global Institute (MGI) and is

based in the San Francisco office; James Manyika is a director of MGI

and a director in the San Francisco office.

36

Competing through data: Three experts offer their game plans

As big data creates new opportunities

and threats, it also demands new mind-sets from

senior executives about the role of information

in business and even the nature of competitive

advantage. The perspectives that follow may

help shake up your thinking and forge that new

frame of mind.

Massachusetts Institute of Technology (MIT)

professor Erik Brynjolfsson explores the implica-

tions of intriguing new research about the

relationship among data, analytics, productivity,

and profitability. Jeff Hammerbacher, co-

founder of the data-oriented start-up Cloudera,

provides a view from the front lines about

what it takes to harness the flood of data now at

companies collective fingertips. Finally, basketball

coach Brad Stevens describes how, on a tight

budget, he uses data thats powerful (even if not

extraordinarily big) to help his Butler University

squad punch above its weight. Presented here are

edited versions of interviews with each, conducted

by McKinseys Michael Chui and Frank Comes.

Erik Brynjolfsson

Professor of management

science at the Massachusetts

Institute of Technologys

Sloan School of Management

Jeff Hammerbacher

Cofounder and chief scientist

of Cloudera

Brad Stevens

Butler University mens

basketball coach

37

The data advantageMost great revolutions in science are preceded by revolutions in measure-

ment. We have had a revolution in measurement, over the past few

years, that has allowed businesses to understand in much more detail

what their customers are doing, what their processes are doing, what

their employees are doing. That tremendous improvement in measure-

ment is creating new opportunities to manage things differently.

Erik Brynjolfsson is the Schussel Family

Professor of Management Science

at the Massachusetts Institute of Technologys

Sloan School of Management, director of

the MIT Center for Digital Business, and one

of the worlds leading researchers on

how IT affects productivity.

Too many managers are not opening their eyes to this opportunity and understanding what big data can do to change the way they compete.

The professor Erik Brynjolfsson

Ste

ve D

unw

ell

38 2011 Number 4

Our research has found a shift from using intuition toward using data

and analytics in making decisions. This change has been accompanied

by measurable improvement in productivity and other performance

measures. Specifically, a one-standard-deviation increase toward data

and analytics was correlated with about a 5 to 6 percent improvement

in productivity and a slightly larger increase in profitability in those same

firms. The implication for companies is that by changing the way

they make decisions, theyre likely to be able to outperform competitors.

Becoming data drivenThe prerequisite, of course, is the technological infrastructure: the ability

to measure things in more detail than you could before. The harder

thing is to get the set of skills. That includes not just some analytical

skills but also a set of attitudes and an understanding of the business.

Then the third thing, which is the subtlest but perhaps the most important,

is cultural change about how to use data. A lot of companies think

theyre using data, and you often see bar charts and pie charts and num-

bers in management presentations. But, historically, that kind of data

was used more to confirm and support decisions that had already been

made, rather than to learn new things and to discover the right answer.

The cultural change is for managers to be willing to say, You know, thats

an interesting problem, an interesting question. Lets set up an

experiment to discover the answer.

I think this revolution in measurement, starting with the switch from analog to digital data, is as profound as, say, the development of the microscope and what it did for biology and medicine.

Too many managers are not opening their eyes to this opportunity and

understanding what big data can do to change the way they compete.

They have to be ready to show some vulnerability and say, Look, were

open to the data and not go in there saying, Hey, Im gonna manage

from the gut. I have years of experience and I know the answers to this

going in. I think, historically, a lot of managers have been implicitly

or explicitly rewarded for that kind of confidence. You have to have a

different kind of confidence to be willing to let the data speak.

39Competing through data: Three experts offer their game plans

One CEO told me that when he pushed this attitude, he had to change

over 50 percent of his senior-management team because they just

didnt get it. Obviously, that was a painful thing to have to do. But the

results have been very successful. And they require that level of

aggressiveness by top management, if it really wants to end up in that

group of leaders as opposed to the laggards.

Required skillsHaving enough data to get a statistically significant result is not a prob-

lem. Theres plenty of data. So the skills often have more to do with

sampling methodologies, designing experiments, and working these

very, very large data sets without becoming overwhelmed. If you look

inside companies, you also see a transformation in the functions that

are using data. CIOs are discovering that, more and more, its the

marketing people and the people working with customerscustomer

relationship managementwho have the biggest data needs. These

are the people CIOs are working with most closely. This is part of a

broader revolution as we move from just financial numerical data

toward all sorts of nonfinancial metrics.

Often, the nonfinancial metrics give a quicker and more accurate

measure of whats happening in the business. I was talking to Gary

Lovemanthe CEO of Caesars Entertainment, formerly Harrahs,

and a PhD graduate of MIT. Hes used some of these techniques to

revolutionize whats happening in that industry. But, interestingly,

increasingly what he measures is customer satisfaction and a lot of

other intermediate metrics. He said that customer satisfaction met-

rics were much quicker and more precise metrics of what was happening

in response to some of the policy changes that he put in place.

Think of it this way. If customers end up satisfied or dissatisfied, that

will affect the probability of their coming back next year. Now, next

years financial results will be affected as a result. And you could, in

principle, try to match up the experience the customer had this

year with future years return rates. But a much quicker way of getting

feedback on which processes are working is to look at customer

satisfaction when you put process changes in place.

The new landscapeI think this revolution in measurement, starting with the switch from

analog to digital data, is as profound as, say, the development of the

microscope and what it did for biology and medicine. Its not just big

data in the sense that we have lots of data. You can also think of it as

40 2011 Number 4

nano data, in the sense that we have very, very fine-grained dataan

ability to measure things much more precisely than in the past. You

can learn about the preferences of an individual customer and person-

alize your offerings for that particular customer.

One of the biggest revolutions has involved enterprise information

systems, like ERP, enterprise resource planning; CRM, customer

relationship management; or SCM, supply chain managementthose

large enterprise systems that companies have spent hundreds of

millions of dollars on. You can use the data from them not just to manage

operations but to gain business intelligence and learn how they could

be managed differently. A common pattern that were seeing is that three

to five years after installing one of these big enterprise systems, com-

panies start saying, Hey, we need some business intelligence tools to

take advantage of all this data. Its up to managers now to seize that

opportunity and take advantage of this very fine-grained data that just

didnt exist previously.

The path aheadTheres some good news and theres some not-so-good news. The good

news is that technologys not slowing down, and the pie is getting

bigger. Productivity is accelerating. And that should make us all better

off. However, its not making us all better off. Over the past 20 years

or so, median wages in the United States have stagnated because a lot

of people dont have the skills to take full advantage of this technology.

And, unfortunately, I dont see that changing any time soon unless

we have a much bigger effort to change the kinds of skills that are avail-

able in the workforce and have a set of technologies that people can

tap into more readily.

This flood of data and analytical opportunities creates more value for

people who can be creative in seeing patterns and for people who

can be entrepreneurial in creating new business opportunities that take

advantage of these patterns. My hope is that the technology will

create a platform that people can tap into to create new entrepreneurial

venturessome of them, perhaps, huge hits like Facebook or Zynga

or Google. But also, perhaps equally important for the economy, hun-

dreds of thousands or millions of small entrepreneurial ventures,

eBay based or app based, would mean millions of ordinary people can

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