<!-- wp:paragraph --> <p>Becoming a data-driven organization is something many companies aspire to, but few are able to obtain. Let’s face it: Data is confusing. It is complicated, dirty, and spread out all over a business. While companies are making big investments in Data Management projects, only a few are seeing the payoff. </p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>New research from Experian shows that despite many ongoing data initiatives, 69 percent of organizations struggle to be data-driven. The struggles are real. Companies face a large data debt, look at data projects through a siloed lens, and still have a large volume of inaccurate data. In fact, 65 percent report inaccurate data is undermining key initiatives. <br></p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>However, the tide is turning. Businesses are starting to adopt data enablement, or a practice of empowering a larger group of individuals within the business to understand and harness the power of data and analytics. Companies that empower wider data usage are better able to comply with regulations, improve decision-making, and, of course, deliver a superior customer experience. Are these the results you’re striving for? </p> <!-- /wp:paragraph --> <!-- wp:paragraph --> <p>Join us to uncover new research from more than 500 Data Management practitioners as we take a deep dive into:</p> <!-- /wp:paragraph --> <!-- wp:list --> <ul><li>The top challenges in becoming a data-driven organization </li><li>Trends and the rise of data enablement </li><li>The profile of a mature organization </li><li>Tips for how you can adopt data enablement practices</li></ul> <!-- /wp:list -->

1. Lead your data revolution:
How to build a foundation of trust
and data governance
Presented by:
Kevin McCarthy, Director of Product Marketing
Erin Haselkorn, Head of Market Research

2. 2 © Experian Public
• Our methodology
• Key findings
• Top challenges in becoming a data-driven organization
• Trends and the rise of data enablement
• Profile of a mature organization
• Questions
What we’ll cover

3. 3 © Experian Public
We spoke to 517 U.S. managers with knowledge and/or visibility of data management
practices at businesses with 250+ employees.
Our methodology
Department Seniority
3%
1%
1%
3%
4%
8%
10%
14%
16%
20%
20%
Other
Innovation
Risk management
Research and development
Customer services
Information Technology (IT)
Sales
Finance
Operations
Data / insight / analytics
Marketing CEO / C-level
23%
Director-level
29%
Manager-level
48%

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61% say it takes
too long to get
actionable
insights from
data.
66% say those
improving data
quality often do
not fully
understand the
needs of the
business.
Data enablement
is a key focus
over the next 12
months for 57%
of respondents.
Key findings
4 © Experian Public
64% say they do
not have enough
talented data
professionals.
69% see
most data
management
initiatives occur in
individual
departments.
69% say despite
many ongoing
data initiatives,
their organization
still struggles to
become
data-driven.

5. 5 © Experian Public
Major takeaways
1. Despite major investments in big data projects, most are
struggling to become data-driven.
2. Most organizations are missing a key cornerstone to data
management success: a foundation built on data quality and
trust.
3. To improve data usage, organizations must supply the right data
talent and technology, while promoting a data culture.

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Lots of data investment,
but few measurable results

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Data is in the driver seat
69% say despite
many ongoing data
initiatives, their
organization
struggles to be
data-driven.
58% say data
management
projects primarily sit
with IT, while 42%
say they primarily
sit with business
users.
80% are actively
pursuing multiple
big data projects.
The focus: data
quality, big data
analytics, and data
governance.

8. 8 © Experian Public
35%
39%
45%
48%
56%
62%
33%
31%
33%
31%
29%
25%
20%
19%
14%
15%
11%
8%
13%
11%
7%
7%
4%
4%
Artificial intelligence
Machine learning
Data literacy
Data governance
Big data analytics
Data quality
Currently undertaking Plan to undertake in next 12 months
On the radar, but with no fixed timeline Not planned / considered
Data management initiatives

9. 9 © Experian Public
Approach to data quality
93% of businesses report progress
with data quality in the last 12
months.
61% say they have traditionally
underinvested in data quality.
Yes, definitely
56%
Yes, possibly
37%
Not particularly
5%
Not at all
1%
Don’t know
1%

10. 10 © Experian Public
Big data analytics
12%
20%
20%
25%
26%
27%
28%
31%
32%
No challenges in leveraging our data for analytics
We don’t trust the information
Our data quality is too poor
Our data is incomplete
We lack necessary skills or human resources
We don’t have the right technology
It takes too long to prepare the data
There is too much data to analyze
We don’t have access to all the information we need
Challenges in leveraging data for analytics
79% are focused on analytics and
how to gain more insight from data.
88% have challenges leveraging
data for analytics.
92% plan to leverage AI or ML.

11. 11 © Experian Public
Approach to data governance
We are taking a holistic approach that involves a
governing body to make decisions, changes in
processes, technology and new data governance
related roles.
29%
We are planning to implement a program
within the next 12 months.
27%
Processes vary based on individual
departments.
26%
We have a data governance board but have not
decided how to move forward with technology or
processes.
16%
We don’t have an
approach to data
governance.
2%

12. 12 © Experian Public
Data governance in practice
29%
41%
45%
48%
48%
51%
52%
We want to eliminate data quality issues and develop trust
We want to monetize our data
We want to be more agile
We need to be data-driven
We want to improve the quality of our decision-making
Compliance with regulations
We want to understand how data is used
16%
1%
20%
21%
26%
30%
32%
32%
We don’t have any challenges with data governance
Other
We don’t know where to get started
We can’t come to a consensus
We lack executive buy-in
We don’t have enough knowledgeable resources
We don’t have the right technology
It is too hard to convince people to follow the new data rules
Reasons for implementing a data governance
program
Challenges in tackling data governance

13. 13 © Experian Public
The data roadblocks,
starting with data debt

14. 14 © Experian Public
Stuck in a data rut
Only 29% say they
take a holistic
approach to data
governance.
65% say inaccurate
data undermines
key initiatives.
69% say despite
ongoing data
initiatives, their
organization
struggles to be
data-driven.

15. 15 © Experian Public15 © Experian
A variety of data management approaches
Each organization is unique in its approach to data. Data management falls to different
business units, there are varying degrees of maturity, and every initiative should not and
cannot be set up the same way. But, we did find common themes:
Department vs enterprise approach
Foundational element of data quality
One-off project vs discipline
Data debt

16. 16 © Experian Public
Departments most advanced in leveraging data
1%
2%
20%
25%
31%
33%
34%
36%
39%
44%
None of the above / we are not advanced in any areas
Other
Call center enablement
Compliance reporting
Marketing campaigns
Sales
Senior Management decision-making
Marketing segmentation
Finance
Logistics and operations

17. 17 © Experian Public
Level of data quality maturity
A - LIMITED
19%
B - EMERGING
32%
C - DEVELOPING
38%
D - MATURE
11%

18. 18 © Experian Public
A (series of)
one-off projects
50%
A continuous
set of
processes
50%
Is data management seen as series of projects or
continuous set of processes?
Project vs discipline

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The accumulated cost that is associated
with the suboptimal governance of data
assets in an enterprise.
Data debt

20. 20 © Experian Public
The rise of data enablement:
Thinking about data in a new way

21. 21 © Experian Public21 © Experian
What is data enablement?
The practice where individuals in the business have the support and
tools they need to responsibly leverage trusted data to achieve real
business outcomes.

22. 22 © Experian Public
Data enablement in practice
Companies need
to focus on hiring
the right talent,
getting the right
technology, and
creating cultural
change.
89% say they have
challenges in
enabling the use of
data.
57% of
organization cite
data enablement
as a key focus
over the next 12
months.

23. 46%
48%
49%
49%
54%
55%
56%
56%
58%
46%
39%
39%
41%
38%
39%
38%
39%
33%
8%
12%
12%
10%
9%
6%
6%
6%
8%
Grow revenue
Enable happier employees
Message / communication personalization
Gain cost efficiencies
Reduce risk
Better understanding of the customer
Improve customer experience
Enable better decision-making
Comply with regulations
Have achieved Will be able to achieve in next 12 months Neither
Outcomes achieved from improved data usage

24. Enabling the use of data
1%
21%
36%
37%
41%
42%
47%
48%
We are not enabling the use of data
Hiring a CDO
Creating centers of data excellence
Creating a true single customer view across the business
Consolidating certain sources of information
Putting data professionals in data-driven departments
Better utilizing data governance to ensure the proper usage of data
Providing standardized data across departments
% saying these actions have resulted in
better outcomes for the business
97%
97%
95%
97%
97%
98%
98%

25. Challenges to enabling data
11%
21%
22%
23%
25%
26%
28%
29%
33%
33%
We don’t have challenges in enabling the use of data
Inadequate senior management support
Poor data strategy
Lack of ownership of data enablement
Inadequacies or a lack of technology
We lack trusted, quality data
Lack of data literacy
Insufficient budget
Lack of communication between departments
Lack of skilled human resources

26. Starting with the right people
4%
20%
30%
31%
35%
38%
39%
43%
We don’t have specialized data roles
Data steward
Data scientist
Data quality analyst
Data governance manager
Chief data officer
Data engineer
Data analyst
Data roles employed to better leverage data assets
64% say they do not have enough
data professionals.
The top challenge to enable data in
the organization is a lack of skilled
human resources.

27. Investing in tools for everyone
43%
47%
51%
53%
54%
56%
59%
64%
71%
45%
41%
40%
38%
38%
32%
35%
28%
22%
12%
12%
9%
9%
8%
12%
6%
8%
6%
Data catalog
Master data management
Business intelligence or analytics platforms
Data governance tools
Data integration
Product information management
Data quality tools
Excel
Data preparation tools
Currently using Plan to use No plans to use
87% report concerns with the tools and technology around data enablement.

28. Cultural changes
Top data enablement challenges include lack of
communication, budget, and data literacy.
28 © Experian
More mature
organizations are
more likely to be
working on data
literacy
Lack of general
understanding of
data across the
business
Lack of scale and
efficiency
Focus on
individual
initiatives, but lack
of communication
between
departments

29. 29 © Experian Public
Profile of a mature business

30. 30 © Experian Public
More likely to undertake all types of
data management projects
More of a focus on data
enablement
More likely to have specialist data
roles in place—especially a CDO
Data management more likely to be
seen as a continuous process
Less likely to see data quality
undermine key initiatives
1
2
4
5
3
Profile of a mature organization
Data quality maturity can give us a good indication of companies that are doing something right
around data management. Companies of all sizes and industries can achieve this level of maturity.

31. 31 © Experian Public
Major takeaways
1. Despite major investments in big data projects, most are
struggling to become data-driven.
2. Most organizations are missing a key cornerstone to data
management success: a foundation built on data quality and
trust.
3. To improve data usage, organizations must supply the right data
talent and technology, while promoting a data culture.

32. 32 © Experian Public
Questions?

33. 33 © Experian Public
Thank you!
For more data
management insight,
view the resources on
edq.com