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Sponsored by:

New strategies for
better decision-making

THE
DATA-DRIVEN
ENTERPRISE:

Page 2

2
THE DATA-DRIVEN ENTERPRISE:

New strategies for better decision-making

© The Economist Intelligence Unit Limited 2020

The volume, variety and usability of data
have expanded at an unprecedented rate
over the past decade. At the same time,
the ability to quickly generate decisions
based on data alone, sometimes through
automation, is increasing. Industries
have been made and remade thanks to
a rigorous emphasis on acquiring and
exploiting data—or a failure to do so.

In January-March 2020 The Economist
Intelligence Unit interviewed 24 top
executives with direct responsibility for
data strategy at enterprises in a range of
industries across four major regions of the
world. This white paper presents the many
insights we gleaned from their expertise.

The Economist Intelligence Unit would
like to thank the following individuals who
participated in the interview programme:

North America

• Alvaro del Pozo,
VP international marketing, Adobe

• Colin Parris,
SVP and CTO, GE Digital

• Kylan Lundeen,
global head of marketing, Qualtrics

• Karen Jones, EVP and CMO, and
Rajeev Ravindran, SVP and CIO, Ryder System

• Stan Pavlovsky, CEO, Shutterstock

• Mike Taylor, CTO, World Wide Technology
Eric Laursen is the author of the report
and Gilda Stahl is the editor.

About this report

Europe

• Morag Watson, CDIO, BP

• Lisa Fiondella, CDO, Finastra

• Jason Goodall, CEO, NTT Ltd

• Mohammed Sijelmassi, CTO, Sopra Steria

• Iris Meijer, CMO, and David Gonzalez,
head of big data and advanced analytics,
Vodafone Business

• Rodrigue Schaefer,
Director Digital Foundation, Zalando

Asia-Pacific

• Clemens Philippi,
CEO ASEAN, Euler Hermes

• Unique Kumar, head digital innovation
and cybersecurity, Max Healthcare

• Parthasarathy Mandayam,
CEO, Mindshare South Asia

• Donald MacDonald, head of group
customer analytics and decisioning, and
Ken Wong, head of AI Lab, OCBC Bank

• C. R. Srinivasan, EVP & CDO,
Tata Communications

Brazil

• Tatiana Mazza, CDO, Carrefour Brazil

• Ricardo Guerra, CIO, Itaú Unibanco

• Felipe Tadeu de Souza Lima,
head of business analytics, and
Guilherme Stefanini,
director new business, Stefanini

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THE DATA-DRIVEN ENTERPRISE:

New strategies for better decision-making

© The Economist Intelligence Unit Limited 2020

The most time-consuming aspect of any action-
oriented analytics exercise is data prep, says
Ms Fiondella at Finastra. “If you want to use
data in decision-making, you better make sure
you’ve got good data to work with.” This is more
difficult for some processes than for others.

“A loan application has some pretty set fields of
data, and as it goes into the system, it’s going to
be relatively clean,” Ms Fiondella says. “Whereas
a CRM [customer relationship management]
system is populated by salespeople who are
putting in data associated with their selling
activities with a particular prospect. They may
put some things in notes. They may not be using
the fields correctly. There may be drop-downs,
and maybe they picked the wrong drop-down.
So that data is more subject to human error and
is inherently going to be ‘dirtier’ than loan data.”

The problem is compounded at companies with
a global reach. “We have 50,000 people speaking
numerous different languages around the world,
and if you don’t get the accuracy and timeliness of
the data right, it’s garbage in, garbage out,” says Mr
Goodall at NTT Ltd. “The amount and the rigour
of the process that you need around ensuring the
quality and the integrity of the data is massive.”

At WWT, Mr Taylor notes that data insights are
built on complex data webs that extend from the
end-customer through a company’s entire supply
chain—and this affects data quality as well.

“Partnership is so essential to providing unique
solutions and capabilities to the customers that

we serve,” he says. “We sit squarely between
a group of innovative technology providers
and customers that want to use and consume
that technology to better their businesses. Our
strength in that is we’re really good at partnering
with companies. So designing systems, processes
and data architectures that understand from
the get-go that we’re going to have data
sources coming in from other partners—that
have to be augmented and rationalised to our
own data—is critically important for us.”

Data consolidation is one way to push back.
At Tata, master data is sourced from a single
master data-management tool. “Every system
we have in the company looks to this source
for all information,” says Mr Srinivasan. “That
means the customer master, the HR master,
the location master—any master database
being accessed by different systems. And these
can only be modified through a controlled
process. So we can do analytics on top of that
without having to worry about one line of
data not being of the quality that we need.”

Improving and maintaining the quality of data

If you want to use data in decision-
making, you better make sure
you’ve got good data to work with.”

Lisa Fiondella, CDO, Finastra

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THE DATA-DRIVEN ENTERPRISE:

New strategies for better decision-making

© The Economist Intelligence Unit Limited 2020

Another significant challenge is one that many
companies may not even be aware of: making
full use of their data. More than half (55%) of
respondents to the EIU’s 2018 global survey
worried that they were not making optimal use
of digital technologies within their organisation.

“I think the biggest problem, which all companies
face, is you don’t know what data you have,”
says Parthasarathy Mandayam, CEO of
Mindshare South Asia. “The second is you
don’t know how data set A talks to or impacts
data set B. So the very first step is to actually
audit the available data, to tag it correctly, and
to try to establish some kind of relationship
between the various data sets that you have.”

“Data is so important to us because it helps us
to be more efficient, more productive, more
accurate in our positions,” says Mr Srinivasan at
Tata. “We are a global network company. Those
networks spit out a lot of data. Earlier, we used
to discard quite a bit of those bits and bytes,
which means we processed only the critical alerts
and didn’t process the rest. Today, we are able

to process 100% of that data, look at real-time
network statistics and analytics and are able to
predict certain patterns even before they happen.
That helps us to be a more knowledgeable, more
proactive, more technology-driven company.”

“Expertise data” is one valuable but often-
overlooked category, says Mr Parris at GE:
“You may have data in documents that the
designers have created that says, ‘When we did
this design, we ran these simulations, we ran
these tests, and we see this in these extreme
cases’. There may be logs written by people
who have done different tests for different
parts of the fleet. You want to incorporate that
information in your analytics as well. There are
design notes. There are other notes—and we
want to pull this in as well on the data side.”

But to make use of all available data, the holders
of that data must be motivated to share it.
“I know that I have to get data that’s across
multiple silos,” says Mr Parris, “so now I have to
convince people across silos that I need to access
their data and I need it cleaned in this way.”

Making full use of your data

Today, we are able to process 100% of
that data, look at real-time network
statistics and analytics and are able to
predict certain patterns even before
they happen. That helps us to be a
more knowledgeable, more proactive,
more technology-driven company.”

C. R. Srinivasan, EVP and CDO, Tata Communications

We are not making optimal use of digital
technologies within our organisation
(% respondents)

23

33

17

16

11
Strongly disagree

Somewhat disagree

Neutral

Somewhat agree

Strongly agree

Source: The Economist Intelligence Unit survey, 2018.

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THE DATA-DRIVEN ENTERPRISE:

New strategies for better decision-making

© The Economist Intelligence Unit Limited 2020

In a knowledge-based economy, the ability to
generate data-driven insights will align more and
more with companies’ overall competitiveness.
More than two-thirds of companies the EIU
surveyed in 2018 said their profitability had
increased over the past three years thanks to
their digital strategy and nearly three-quarters
expect it to rise in the next three years.

“The role of data in everyday decision-making
is becoming more and more normal, reinforcing
the use of data and the use of very strong
analytical tools in the process,” says Guilherme
Stefanini, director of new business at Stefanini,
a Brazilian software and service provider.

The volume and cost of data will grow too,
of course, especially as AI and ML assume
a more prominent role. Companies in data-
heavy businesses like healthcare provision are
already coming to grips with this problem.

Repeatedly, however, our interviewees referred
to their quest to build more of their decision-
making at all levels on data-driven insights as
a “journey”. Some companies we spoke to are
still focused on product-level predictivity—
such as which audience its market ought to
pursue based on geography, income level or
other indicators—while others are looking to
apply data analytics to more strategic matters.
Curiously, however, as the importance of data
and analytics grows it is broadly agreed that the
critical factor will be people rather than numbers.

“You have to almost do a change management
process within the organisation,” says Mr Goodall
at NTT, “and create awareness about the value
of the data, the importance of putting it in
accurately and keeping it up-to-date, supported
by process and orders and the right toolset. But
a large part of it is, once again, human behaviour,
where the salesperson realises it’s important to
change the email address of the contact at the
company because that data is going to be used
for different things across the organisation.”

Garbage in, garbage out, in other words.

The results will never be perfect, or perfectly
up to date. “There are sets of data that we
don’t have fully integrated,” says Mr Srinivasan
at Tata. “Organisations that go through this
journey will always have some sets of data
that are not fully analysed and fully used.
Some of this is because technologies get
obsolete and you need to move on.”

The way to consistently overcome these
hurdles is to develop a data-driven culture
at all levels of the organisation. “The best
takeaway here”, says Mr Gonzalez at Vodafone
Business, “is that having all your teams working
together under the same data strategy—
finance, marketing, strategy—and celebrating
the technology, is the only way forward.”

Conclusion:
The journey to a data-driven culture

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THE DATA-DRIVEN ENTERPRISE:

New strategies for better decision-making

© The Economist Intelligence Unit Limited 2020

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