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A report from the Economist Intelligence Unit
Big data and the democratisation of decisions
Sponsored by
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20121
Preface 2
Introduction 3
Orchestrating the big data strategy 4
Making cross-functional teams big data strategy architects 6
Leveraging key data and departments 8
A paradigm shift 9
Appendix: survey results 10
Contents
1
2
3
4
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20122
Preface
Big data and the democratisation of decisions is an Economist Intelligence Unit research report, sponsored
by Alteryx. Our thanks go to all survey respondents and interviewees for their time and insight. The author
was Carolyn Whelan and the editor was Riva Richmond. The fi ndings and views expressed in the report do
not necessarily refl ect the views of the sponsor.
October 2012
In August 2012 the Economist Intelligence Unit
conducted a survey sponsored by Alteryx of 241
global executives to gauge their perceptions of big
data adoption. Fifty-three percent of respondents
are board members or C-suite executives,
including 66 CEOs, presidents or managing
directors. Those polled are based in North America
(34%), the Asia-Pacifi c region (27%), Western
Europe (25%), the Middle East and Africa (6%),
Latin America (5%) and Eastern Europe (4%). Half
of executives work for companies with revenue
that exceeds US$500m. Executives hail from
18 sectors and represent 14 functional roles,
including general management (30%), strategy
and business development (18%), fi nance (17%)
and marketing and sales (10%).
About the survey
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20123
Much as the Internet upended industry during the
last two decades, big data’s potential to provide
companies with deeper insight into their
businesses seems destined to generate both
upheaval and endless opportunity. The tumble and
roll should only increase as the data heap grows.
Abundant data and the technology to crunch
them are now enabling more fi rms, large and small,
to extract value from fresh insights. The data swell
is fed by billions of transactions, web clicks and
sensor readings, and the buzzing of smartphones
and social media sites. Thanks to cheap servers for
storing data and affordable supercomputers,
algorithms and visualisation tools for mining it,
companies around the world are better able to spot
and act on new trends and intelligence.
This expansion of corporate access to “big data”
is now being met by a democratisation of which
employees inside companies are able to tap data,
draw lessons and make business decisions. The
tyranny of technology and data specialists is
breaking down. Now, players from many
departments are harnessing data to make better
tactical decisions about how to respond to
emerging trends, fi nd new business opportunities,
retain more customers—and goose their
companies’ bottom lines.
According to a survey of 241 global executives,
conducted by the Economist Intelligence Unit and
sponsored by Alteryx, nearly half (48%) of
respondents say someone other than the chief
information offi cer (CIO) drives big data processes.
This trend should accelerate as corporations work
to capture more value from their information
assets. Over three-quarters of respondents say
businesses must empower more employees to
access and make decisions using big data.
“[We] rely on data for most things,” says one
respondent from the publishing industry. “Our
biggest challenge is to get info in the hands of
those who can use it to grow the business.”
Survey respondents believe that tapping big
data will aid decision-making around seizing
market opportunities (66%), holding on to
customers (55%), competing with rivals more
effectively (41%) and boosting fi nancial
performance (35%). They also believe that
allowing more workers to harness big data will help
them make better and faster decisions (63%),
illuminate business opportunities that were not
previously apparent (45%) and identify and exploit
opportunities more quickly (37%).
Tellingly, the data most available to executives—
internal information—are also what they most
value, our research shows. To extract the most value
from big data, companies’ fi rst order of business
may be to eliminate data silos between departments
and fi nd better ways to work together.
Introduction {{Nearly half (48%) of respondents say someone other than the chief information offi cer drives big data processes.||
70%
say a positive
outcome resulted
from their last
major decision in
which data played
a pivotal role,
while
45%
say more big data
would have helped.
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20124
Orchestrating the big data strategy1Some large organisations have long leveraged
giant data sets. For decades household names like
Wal-Mart, Tesco and Kroger—and successful fi rms
in industries like fast food, fi nancial services and
healthcare—have sifted through transactional
information, US Census Bureau records, company
e-mails and even genomic patterns to help inform
decisions. This has helped guide actions around
stocking shelves and opening new stores, battling
fraud and gauging the probability of success or
failure for a new drug.
Many of these trailblazers offer useful lessons.
The most important is to start with a highly focused
problem, question or business priority. From there,
managers empower teams to get answers and apply
fi ndings. For example, a question like “Where do
people walk within a store?’ can be answered with
the help of facial-recognition software. Then a
marketing team can improve product displays and
selections.
At most companies, democratisation of data-
driven decision-making is largely aspirational.
Though our survey respondents acknowledge the
importance of big data and its link to driving better
performance, only 17% of respondents consider
themselves leaders in this area. Forty percent say
their organisations are adequate at the collection
and analysis of big data, while a startling 41% say
they are somewhat or completely inadequate. “It’s
about access but also about understanding,” says
one survey respondent. “We all need to get better
at amalgamating and analysing disparate data
sources.”
Often “it’s the hammer looking for the nail,”
says Venkat Rao, a research associate with the
Leading Edge Forum at Computer Sciences Corp, a
technology systems integrator. Executives try to
‘bang out’ insights from a raft of data rather than
let business problems or priorities dictate the
research. “Most people are trying to wrap their
heads around this,” he says.
Many fi rms are hamstrung by the lack of a
cohesive big data strategy. Costly legacy
technology infrastructures, rigid technology teams
and old ways of working that prize intuition and
experience over data-driven decisions are also
common obstacles.
“In the Don Draper era, the person who could
convince someone of something was in charge. In a
data-driven world, whoever can ask the right
questions is the leader,” explains Alistair Croll, an
analyst at Solve for Interesting, a fi rm that studies
emerging technologies. “Data make everything
very much a meritocracy. It’s OK to be wrong if it’s
quick and you learn each time. Organisations that
can’t increase the speed at which they learn will
die. The cycle time is scary.”
Despite the imperative to act, investment is
lagging. Nearly half (47%) of respondents say they
do not expect to invest in expanding their ability to
use big data in decision-making in the next three
years, with fi nancial constraints cited as the
biggest barrier (37%). Larger fi rms are a step
ahead, perhaps because of deeper pockets. Survey
respondents who work for companies with revenue
of US$5bn-10bn are more likely (39%) to consider
{{In the Don Draper
era, the person
who could
convince someone
of something was
in charge. In a
data-driven world,
whoever can ask
the right
questions is the
leader.
||
Alistair Croll, analyst at
Bitcurrent
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20125
themselves industry leaders; 86% of this group
believes it is important to empower employees with
more data to make better business decisions.
Corporate culture can also get in the way.
Interestingly, North American respondents
consider culture to be the top obstacle to sharing
big data more widely (it ranked second globally).
Some executives fret that employees will be
overwhelmed by a tsunami of messy information
that may confuse or distract already overloaded
departments. After all, the volume, variety and
velocity of information are both empowering and
intimidating. A lack of consensus at leadership
levels can impede the creation of a cohesive overall
strategy, as can concerns about privacy and
security breaches.
Even fi rms willing to channel funds into better
big data capabilities struggle with talent
acquisition. Data specialists are in short supply and
often lack industry expertise. “There are not
enough foot soldiers to fi ght the war,” says CSC’s
Mr Rao.
Often, rank-and-fi le employees are stepping in,
on their own, to do battle. As with the Arab Spring,
much of the democratisation of data use is emerging
from the grassroots, as employees seeking ways to
do their jobs better, fi nd and mine data with tools of
their own. “Marketing departments are going
rogue,” says Solve for Interesting’s Mr Croll,
describing shadow data-collection systems that use
tools like Google Analytics.
To avoid duplication, use data effi ciently and
conserve resources, the C-suite would be wise to
commit to a thoughtful big data strategy—and to
leverage this entrepreneurial mindset across the
enterprise.
Four years ago, computer giant Dell asked
executives worldwide to make their data available
to other business units. But there was resistance.
Executives were reluctant to share proprietary
information that had been costly to collect and
process, and little sharing occurred.
That changed quickly when Chief Executive
Michael Dell took charge, illustrating the
importance of executive leadership in creating
an environment that gives employees autonomy
to leverage big data for better decision-making.
He required executives to supply data and issue
regular reports. Next, he embedded data scientists
in each business unit to decentralise access to the
data and action on new insights.
“Disparate systems didn’t speak the same
language,” recalls Rob D Schmidt, executive
director for business intelligence in the CIO’s
offi ce. “We had to break down barriers around data
ownership [and] technology and defi ne a common
model. Only when Michael [Dell] required everyone
to standardise on a single reporting format did we
get there. Now we are very much aligned.”
Today, Dell pushes data from businesses
and regions around the globe onto a common
platform. It collects and acts on intelligence about
the activities of prospective buyers on its global
websites to assess tastes and response times. It
watches for intruders, to detect and stop security
breaches. Some 9,000 servers send regular reports
to technicians who fi x problems. And it tracks key
social media infl uencers who are applauding or
complaining about products or services, so Dell can
respond in real time.
Revenue and effi ciency gains have totalled many
millions of dollars, Mr Schmidt says. And efforts to
extract more value from additional data types are
under way.
Taking big data across Dell: leadership matters
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20126
Making cross-functional teams big data strategy architects 2
Pioneers in the use of big data task mid-level
manager teams with strategy development that is
rooted in unanswered questions and business
problems. Marcia Tal, founder of consultancy Tal
Solutions and a former executive at Citi who was
responsible for building and leading the company’s
global decision-management system, recommends
creating cross-functional teams that use data and
analytics to develop products and services that
solve problems. Together, they can prioritise their
most pressing data needs while focusing on data
that are accurate, relevant and actionable.
Based on the collective judgment of the team,
data, analytic fi ndings and insights can be applied
to business decisions, she says. But to get there,
vision, strategy and investment are required.
“You need connectors—people that can
translate the business strategies, intentions and
opportunities to the particular program
initiatives,” Ms Tal explains. “Corporations need to
blend art and science, employing creative ‘data
artists’ that draw the picture, which data scientists
have discovered. In a structured but challenged
department that needs to meet its numbers, it’s
EMI Music wants even its most junior employees to
be able to make quick decisions about how to best
promote its artists around the world. “It’s their
job to combine their skills and judgment with the
vision of the artist and the cold, hard data to come
up with a plan,” says David Boyle, senior vice-
president of insight at EMI Music. At a company like
EMI, “relying on analysts or data experts to make
decisions using data doesn’t scale.”
Employees’ fi rst task is to identify the audience
for an artist or piece of music using EMI’s own
consumer research of a million in-depth interviews
with consumers around the world. Then, ten
web-based applications—accessible to all on
PCs, and iPads during meetings—help them make
decisions about products, pricing, sales channels
and marketing approaches. For instance, if an
employee promoting The Beatles in France decides
the best targets are cash-strapped young people
and gadget lovers, she might offer digital products
and promote them on social networks.
Mr Boyle says his top challenge has been to
provide employees with high-level information at
a glance and the ability to go deep to answer tough
questions. “I want quick, but I want complex. And
that’s incredibly diffi cult,” he says. One trick: colour
coding. For instance, blue highlights excellence—
and a lack of blue signals the need to dig deeper.
Finding a balance has paid off. Many employees
make well-supported data-based decisions daily
and with confi dence and speed. Partners get on
board more quickly, product and pricing choices
are smarter, and marketing is more focused and
effective—and EMI artists are better served.
EMI’s success by numbers
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20127
hard for people to get their arms around that.
These are diffi cult discussions.”
“Are you learning as fast as the world is
changing?” she asks. Because traditional “data and
management structures are not usually set up to
create value across business entities.” For these
transformational shifts to take root, “we need
leaders to recognise the importance of analytic
business leaders within an organisation,” she says.
When formulating a big data strategy, tapping
business-unit managers who are already capturing
value from actionable insights may also yield useful
guidance about key issues like risks, pricing and
customer behaviour.
Democracy, of course, is on a continuum, and
leadership styles and cultures shape how data are
shared. These styles can range from democratic to
autocratic, says Jeffrey Stanton, a big data expert
at Syracuse University. Most organisations work
more effectively when senior management
articulates a vision for how data should be used, he
says. “But that vision should be compatible with
the organisation’s mission and culture.”
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20128
Leveraging key data and departments 3Internal data sit high atop our survey respondents’
ranking of the most benefi cial big data types (61%).
Signifi cantly, fewer respondents cite external
website content as benefi cial (50%), and even
fewer cite much-hyped social media content (39%),
though it remains early days for social media.
Much of today’s data-driven decision-making
also incorporates targeted, discrete data revealing
market dynamics bought from external data
aggregators. The sweet spot for sharing and
spreading useful information seems to be in the
product-line area. There, executives on the front
lines are combining a keen understanding of their
customers with internal big data and relevant
external information about broader product trends
purchased for relatively small sums. The
combination means more effective decisions about
which products to offer.
Indeed, our research shows that analysing big
data sets, whether from internal databases or
culled from the Internet, are most valuable when
viewed in the context that outside market and
customer data can provide. More than half of our
survey respondents believe there is particular
value in analysing internal data alongside
competitive intelligence, customer-segment
information and market-condition models that
companies normally purchase.
According to our survey, the job functions that
stand to benefi t the most from big data analysis
capabilities are customer service, marketing, strategy
and business development, general management,
and information and research. Customer-service and
marketing departments have long profi led current
and potential customers by dissecting demographic,
relational and contextual data. So it comes as no
surprise that over half of our respondents single out
customer retention and spotting new market
opportunities as business decisions that most benefi t
from tapping big data.
The empowerment of employees to access and
analyse data must be accompanied by freedom to
act on their insights. “Data empowerment is
completely toothless unless you combine it with
empowerment to take risks,” Mr Rao says.
And of course, companies need to protect
sensitive data. “Not everyone should be—nor has
the skills to be—stewards, observers or analysts of
big data,” cautions Ms Tal. “This requires very
specialised skills.” Companies should take steps to
ensure that they control who sees and uses what
information.
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 20129
Unleashing the power of big data enables
innovative executives and employees to fi nd new
market niches, tweak product offerings, reduce
inventory and boost profi t margins. But capturing
value from actionable insights requires a paradigm
shift in culture and execution.
Through a cohesive, integrated strategy that is
backed by the C-suite, designed by cross-
functional teams and executed by line managers
who are permitted to experiment and take
calculated risks, companies can discover exciting
new opportunities and take the swift and savvy
decisions that deliver triumphs.
A paradigm shift 4
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 201210
Appendix:survey results
Percentages may not add to 100% owing to rounding or the ability of respondents to choose
multiple responses.
Industry leading (my company has a comprehensive strategy for gathering and gaining insight from a broad range of data sources)
Adequate (my company has a basic approach for gathering and gaining insight from a limited number of data sources)
Somewhat inadequate (my company has a limited ability for gathering and gaining insight from data. Only a select few executives or specialists have this ability)
Completely inadequate (my company has no formal way to gather and gain insight from more than a few data sources)
Don’t know
Based on your observations, how does your company’s ability to gather and analyse big data compare to that of competitors within your industry? (% respondents)
17
40
31
10
2
Strongly agree Agree Neither agree nor disagree
Disagree Strongly disagree
Don’t know
Typically, businesses must empower more employees with access to big data so they can make informed business decisions
In general, the more data that are shared within an organisation, the more effective the decision making process
The biggest barrier to getting useful insights and results from big data is the available technology
In most cases, if data results are incomplete or inconclusive, it’s the fault of the data source
The CIO drives all of our big data processes
To what extent do you agree with the following statements: (% respondents)
26 51 15 6 1
27 47 15 10 1 0
9 34 24 28 4 1
5 15 31 37 11 2
5 18 24 36 12 5
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 201211
Customer service
Human resources
General management
Strategy and business development
Legal
Marketing
Finance
Risk/Security
Operations and production
Regulatory compliance
Sales
Information and research
R&D
Supply-chain management
Procurement
IT
Operations, real estate planning
Other
None of the above
Which job functions do you feel currently have the least extensive big data capabilities or limited developed data systems?Please select the top 4.
(% respondents)
40
32
28
28
24
22
20
20
19
18
18
16
14
13
13
10
8
0
4
Customer service
Marketing
Strategy and business development
General management
Information and research
Finance
Sales
Operations and production
R&D
Risk/Security
Human resources
Procurement
Supply-chain management
IT
Regulatory compliance
Legal
Operations, real estate planning
Other
None of the above
Which job functions need to benefit from big data capabilities today? Please select the top 4.
(% respondents)
41
41
33
27
26
24
24
23
18
16
13
13
12
10
9
8
5
0
2
Market opportunity and segmentation
Customer retention
Product and service mix
Competitor performance
Financial performance
Capital investments
Risk mitigation
Customer purchase
Geographic market
Fraud mitigation
What kinds of business decisions in your organisation would benefit the most from the inclusion of big data? Please select all that apply.
(% respondents)
66
55
44
41
35
29
29
26
26
19
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 201212
Internal data
External website content
Social media data
Internet connected device data
Location-based data
Internal log files
RFID data
Sensor-generated data
Other
None of the above
Which of the following types of big data would your company benefit from the most in making strategic decisions? Please select all that apply.
(% respondents)
61
50
39
34
34
21
19
17
3
3
Competitive intelligence
Customer segment data
Market condition models and data
Sales results and forecast data
Internal customer data
Third party market data (eg, Demographics)
Point of sale data
Other
None of the above
Which of the following data types would be most useful to analyze in combination with the above big data types in making strategic decisions? Please select all that apply.
(% respondents)
66
65
54
43
39
37
30
2
1
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Think about the last major decision your team made. Approximately what percentage of internal and external big data did you take into account?(% respondents)
12
14
20
17
15
9
7
3
2
2
Positive
Negative
No effect (the decision had no impact)
Now think about the result of that decision. What was the outcome?(% respondents)
70
5
25
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 201213
Yes
No
Do you feel you had enough internal and external big data to make the decision?(% respondents)
55
45
Strongly agree
Agree
Neither agree nor disagree
Disagree
Strongly disagree
Not applicable (data did not play a part in the decision/outcome)
If you did not feel you had enough internal and external big data to make the decision, to what extent do you agree with the following statement: Adding more sources of data would have helped ensure a positive business decision and outcome. (% respondents)
16
60
15
3
1
5
Yes
No
Over the next three years, do you expect your company to invest more in expanding big data decision capabilities to more employees?(% respondents)
53
47
Financial (high costs are prohibitive)
Cultural (not an executive priority)
Talent (skilled worker shortage)
Security (too many variables)
Technical (too complex to integrate)
Organisational (not everyone would benefit)
Logistical (too many data sources)
Time (data capabilities take too long)
What would you consider the biggest obstacles to expanding big data capabilities to more employees? Please select the top 2.
(% respondents)
37
32
27
22
22
20
17
11
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 201214
Better decisions are being made faster
Identifying business opportunities that were not previously apparent
Identifying opportunities and exploiting them faster
Planning scenarios with greater confidence
Managing risks more effectively
Increasing revenues
Bringing products and services to market faster
Adapting to change is easier
Predicting outcomes with greater accuracy
Maximising business processes is easier
Reducing costs
Measuring outcomes has improved
Responding to third parties is more effective (suppliers, partners, customers, etc)
Other
Don’t know/Cannot predict
What do you consider to be the most important outcomes if your company expanded big data capabilities to more workers? Please select the top 4.
(% respondents)
63
45
37
31
31
29
28
23
18
18
10
10
8
1
2
United States of America
Canada
India
United Kingdom
Australia
Hong Kong, China, Singapore
Italy, Netherlands, Belgium, Brazil, France, Greece, Russia
Germany, New Zealand, Switzerland, Denmark, Hungary, Indonesia, Ireland, Malaysia, Mexico, Nigeria, Poland, Portugal, Romania, South Africa, Taiwan
In which country are you personally located?(% respondents)
25
9
8
6
4
3
2
1
North America
Asia-Pacific
Western Europe
Middle East and Africa
Latin America
Eastern Europe
In which region are you personally located?(% respondents)
34
27
25
6
5
4
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 201215
49
11
17
6
16
$500m or less
$500m to $1bn
$1bn to $5bn
$5bn to $10bn
$10bn or more
What are your organisation’s global annual revenues in US dollars?(% respondents)
Board member
CEO/President/Managing director
CFO/Treasurer/Comptroller
CIO/CTO/Technology director
Other C-level executive
SVP/VP/Director
Head of Business Unit
Head of Department
Manager
Other
Which of the following best describes your title?(% respondents)
5
27
10
2
9
14
8
7
12
7
Professional services
Financial services
IT and technology
Healthcare, pharmaceuticals and biotechnology
Manufacturing
Entertaining, media and publishing
Consumer goods
Energy and natural resources
Education
Chemicals
Automotive
Government/Public sector
Retailing
Transportation, travel and tourism
Telecoms
Construction and real estate
Agriculture and agribusiness
Logistics and distribution
What is your primary industry?(% respondents)
14
12
11
11
9
5
5
5
4
3
3
3
3
3
2
2
2
2
General management
Strategy and business development
Finance
Marketing and sales
IT
Operations and production
R&D
Information and research
Supply-chain management
Customer service
Legal
Risk/Security
What is your main functional role?(% respondents)
30
18
17
10
5
5
4
4
2
1
1
1
Democratisation of big data decisions
© The Economist Intelligence Unit Limited 201216
Whilst every effort has been taken to verify the accuracy of this
information, neither The Economist Intelligence Unit Ltd. nor the
sponsor of this report can accept any responsibility or liability
for reliance by any person on this white paper or any of the
information, opinions or conclusions set out in the white paper.
Cover: Shutterstock
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