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Attivio Big Data Decision Makers
Survey Findings
May 2016
Methodology
We conducted a 10-minute online survey among n = 150 individuals in data-related roles. The survey was fielded from April
21st- May 5th, 2016.
Audience Definition Sample Size
Data
Leaders
• Work in companies with at least 5,000 employees
• Director-level or above
• Has influence over decisions to leverage big data to inform company business
decisions
• Has influence over decision to partner with business intelligence and big data
software vendors
• Works in a role related to:
o Big Data
o Data Strategy
o Data Management
o Data Integration
o Compliance/ Risk
o Analytics
o Business Intelligence
N=150
2
3
Executive Summary
• Virtually all big data leaders are optimistic that their companies are headed in the right direction when it comes to leveraging big data efficiently—
their companies are dedicating new talent and tools to big data initiatives, and also gaining internal alignment around how big data will be used.
• Companies with big data leaders “very” or “extremely” successful at leveraging big data to make business decisions—however, nearly all plan to
continue investing in resources dedicated to big data and only 51% say their company leverages big data extensively, across all business units.
• The challenges data leaders’ companies face are wide-ranging, but companies have the most room for improvement when it comes to the tools
and technologies dedicated to big data and most respondents say that internal bottlenecks between the information technology and business units
prevent data from being accessed quickly and efficiently.
Key challenges data leaders face include:
o “Shadow analytics” leading to data governance problems
o Business users spending more time gathering data than performing analysis
o Legacy data storage systems requiring too much processing to meet today’s business requirements
o Too heavy a reliance on manual methods when prepping data
• There are a wide-range of resources companies need to leverage big data include better tools, more centralized talent and more information on why
leveraging big data is valuable.
4
We first explored the extent to which data
leaders’ companies are leveraging big data
today and their outlook for the future
Nearly all respondents believe that their company is headed in the right direction
when it comes to leveraging big data efficiently
Headed in the right directionOff on the wrong track
Q2: When it comes to leveraging big data efficiently, do you believe your company is headed
in the right direction or off on the wrong track?
94%6%
5
Respondents cite more investment in new talent and technologies, and further
alignment on big data operations as the key reasons they are optimistic
Investing in Talent Investing in New Technologies Aligning on Big Data
“We hired
professionals with
proven experience in
this area.”
Q3: Why do you say your company is headed in the right direction when it comes to
leveraging big data efficiently?
“We have added
many servers and a
highly functioning
system with many
ways to protect
data/information.”
“Advanced data
software options give
us an edge in the
market place.”
“Our company is
starting to truly
understand the gains
that can be had using
big data. It will be a
priority going
forward.”
“We have many new skilled
workers in our company
who have a great deal of
experience dealing with
traffic commerce and this
frees up any clusters in our
data flow.”
“We are getting the right
parties involved in
addressing this. All too
often, IT goes off on their
own way due to the lack of
assistance from the line of
business units.”
“We have started pilot
programs in certain
departments to see how
big data can inform our
decisions and will use
the results to formulate
a broader strategy.”
6
Virtually all respondents say their company encourages its employees to ground
business decisions in data and evidence
60%
38%
2%
Strongly encouraged
Somewhat encouraged
Not encouraged
Q13: To what extent is it encouraged at your company for employees to ground business
decisions in data and evidence?
7
Perceptions of success are high, although less than one-quarter believe they are
“extremely successful”
23%
39%
30%
8%
0%
Extremely successful Very successful Somewhat successful Not very successful Not at all successful
Q1: How successful do you believe your company is at leveraging big data to make business
decisions today?
8
Despite today’s success, nearly all believe that their company’s investment in big data
resources will increase in the next five years
81%
8%
11%
Investment will increase
Investment will decrease
Investment will stay the same
Q14: How do you believe your company’s investment in resources (e.g., talent, tools and
technologies) to help leverage big data will change in the next five years?
9
10
We gauged where respondents’ companies stand when it comes to three key
components of leveraging big data
Talent TechnologiesProcess
2% 7% 13% 35% 43%
Most respondents (78%) work at companies where there is a member of the C-Suite
responsible for driving their ability to compete on analytics
Q7: Which of the following best describes your company when it comes to the talent it dedicates to managing big data?
My company has one member of the C-
Suite responsible for driving our ability
to compete on analytics; this leader
works seamlessly with other members
of the C-Suite
My company has one
member of the C-Suite
responsible for driving our
ability to compete on
analytics who works
independently to
determine how big data
will be used
My company does not have a
member of the C-Suite
responsible for driving
analytics but has a centralized
team with responsibility for
managing big data across
company functions
My company does not
have a member of the C-
Suite responsible for
driving analytics but some
company divisions employ
talent dedicated to
managing their big data
My company has not
yet employed any
talent exclusively
dedicated to
managing big data
Least Mature Most Mature
Talent Spectrum
Shortened statements used
11
3% 7% 13% 41% 36%
Most respondents (64%) say that bottlenecks prevent big data from being accessed
quickly and efficiently
Q8: Which of the following best describes your company when it comes to how big data is accessed and shared across divisions?
There is a set process for accessing and
sharing big data across divisions at my
company and this process is widely
understood; no bottlenecks exist for
accessing data quickly and efficiently
There is a set process for accessing
and sharing big data across
divisions at my company that is
widely understood across divisions;
however, bottlenecks prevent big
data from being accessed quickly
and efficiently
There is a set process for
accessing and sharing big data
across divisions at my
company, but this process is
not widely understood across
divisions due to the
bottlenecks that exist
Although big data can be
accessed and shared
across divisions at my
company, there is no set
process for doing so as
there are too many
bottlenecks
Bottlenecks at my
company make it
impossible for big
data to be accessed
and shared across
divisions
Least Mature Most Mature
Process Spectrum
Shortened statements used
12
1% 5% 23% 31% 39%
In nearly one-third of respondents’ companies, divisions do not have complete
visibility into data across all big data sources
Q9: Which of the following best describes your company when it comes to the tools and technologies it dedicates to organizing and leveraging big data?
My company uses effective tools to
organize and provide complete visibility
into all big data sources across divisions,
including structured and unstructured
data
My company uses effective tools to
organize and provide complete
visibility into all big data sources
across divisions, including
structured data; today, we do not
have tools to organize and provide
visibility into unstructured data
My company uses tools to
organize big data sources
across divisions, but the
limitations of the tools means
we cannot organize big data
effectively and do not have
complete visibility into all big
data sources
My company does not use
tools to organize big data
across divisions, but some
divisions have their own
tools to organize big data
My company does
not use any tools
to organize big
data today
Least Mature Most Mature
Technology Spectrum
Shortened statements used
13
1% 5% 23% 31% 39%
Respondents are “least mature” when it comes to the technology dedicated to big
data
Least Mature Most Mature
3% 7% 13% 41% 36%
2% 7% 13% 35% 43%
People
Process
Technology
Shortened statements
14
Ultimately, only half of data leaders say that big data is leveraged extensively in their
company, throughout all business units
51%
34%
13%
2% 1%
Big data is leveraged
extensively, throughout all
business units / operations
Big data is leveraged regularly,
but only in some business units
/ operations
Big data is occasionally
leveraged, in a few select cases
My company has not yet
implemented processes to
leverage big data, but plans to
in the future
My company has not yet
implemented processes to
leverage big data, and has no
plans to in the future
Q4: Which of the following best describes your company today when it comes to big data to
inform business decisions?
15
16
Despite optimism and some success,
there are still challenges that data
leaders face
Although most data leaders believe their companies are making a sufficient effort to
leverage big data, a subset say they are not doing enough
69%31%
Making a sufficient effortNot doing enough
Q12: Thinking about your company’s big data management practices, do you think leadership is making
a sufficient effort to leverage big data when making business decisions or are they not doing enough?
17
Respondents report needing better technology, fewer silos between departments, and
more internal buy-in to enable their company to more efficiently leverage big data
Better Technology Fewer Silos Between Departments More Internal Buy-In
Q18. What do you believe would enable your company to more efficiently leverage big data
to make business decisions?
“It boils down to
investments in software
and getting all systems
on the same platform
across the company.”
“Better collaboration
between units. We are
very siloed. I think we
need a comprehensive
standardization of how
we leverage big data.”
“More cross-functional
collaboration.”
“Strategic changes from
the top around
utilization and
implementation of big
data resources.”
“Having board members
better understand the
scope of what we are trying
to accomplish.”
“A general push from
upper management to
ramp up our efforts to
manage, aggregate, and
analyze big data would
be a good first step.”
“More text based data
needs to be utilized and the
manual excel spreadsheets
need to be eliminated in
favor of more automated
analytical software that will
sort the data more
effectively.”
18
Though respondents are optimistic about their ability to leverage big data, few are using
all their data in making business decisions
19%
26%
32%
17%
6%
0%-25% 26%- 50% 51%-75% 76%-90% 91%-100%
Q10: What percent of all the data collected by your company do you think
your company is analyzing and utilizing today to make business decisions?
Only 23% of respondents utilize
over three-quarters of their
available big data
19
. . . and accessing disparate data sources can frequently take a day or longer
Q11: How long does it generally take business users at your company to access disparate big
data sources for a single analysis?
11%
27%
24%
19%
10%
5% 4%
A few
minutes
Under an
hour
A few hours About 24
hours
About one
week or less
About two to
four weeks
More than
four weeks
37% say it takes one day or more to
access big data sources for an analysis
20
49%
42%
28%
17%
17%
14%
66%
59%
42%
Finding and hiring skilled big data analytics
talent is difficult
The value of analytics is understood, but
not being quantified and articulated
adequately enough to secure buy-in
Ad hoc data analysis is not widely used
and valued in our organization
Somewhat agree Strongly agree
Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently?
People Challenges
When it comes to the “people” needed for success, finding and hiring skilled big data
analytics talent is a major challenge
21
40% 39% 35% 33% 29% 25%
19% 20%
17%
15%
17%
19%
59% 59%
52%
49% 45% 44%
“Shadow analytics”
leads to data governance
problems
Business users spend
more time gathering
data than performing
analysis
A great deal of our data
is not being incorporated
into analytics projects
today
Company-wide big data,
data is not put into the
hands of the right
business leaders
Data is siloed and
difficult to find and
leverage
It is not clear to
stakeholders across the
company what big data
is available and to whom
Somewhat agree Strongly agree
The biggest challenges around “process” concern data governance and business users
spending too much time gathering data vs. analysis
Shortened statements
Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently?
Process Challenges
22
Respondents are split on whether big data is easily accessed or siloed within functions
59%41%
Unit leaders can easily access big data, and
it is easy for them to use the data to help
make business decisions quickly
Data is siloed within functions and it is
difficult for unit leaders to access the big
data they need when they need it
Q17: Which of the following best describes your company today when it comes to big data management?
23
35% 33% 31% 34%
22%
24%
15% 17% 13%
11%
59%
48% 48% 47%
33%
Our legacy data storage
systems require too much
processing to meet today’s
business requirements
There is no standard way the
company measures success of
big data initiatives
There is too heavy a reliance
on manual methods and trial-
and-error when preparing
data
We do not leverage enough
text-based content for
analytics
We can’t trust that our data is
accurate and up-to-date
Somewhat agree Strongly agree
The main technology challenge data leaders face is legacy data storage systems
requiring too much processing to meet today’s business requirements
Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently?
Technology Challenges
24
Only one-fifth of data leaders are “extremely satisfied” with the resources their
company dedicates to big data
Q6: What resources (e.g., talent, tools and technologies) do you believe
your company would need to be more successful when it comes to
organizing big data and leveraging it to make business decisions?
Q5: How satisfied are you with the resources (e.g., talent, tools and
technologies) your company currently devotes to organizing big
data and leveraging it to make business decisions?
[Showing “extremely satisfied”]
20%
“We need to scale up our use of
big data once the pilots are done,
which will mean hiring more
talent and giving the tools and
technology to more people.”
“A more defined mission
statement developed and
implemented by talented staff
using the proper technology.”
“To start off with, I would like to
see an increase to the members
of the team who are responsible
for Big Data Capture and Analysis.
They are a bit understaffed to
meet current needs. Two to Three
people with the right training
would make a big difference.”
25
Responses are fragmented when it comes to the resources needed—there is no one
area where big data analytics is “perfect”
42% 46% 45% 49% 35% 46% 38% 36% 39%
35% 31% 32% 26% 40% 29% 37% 37% 21%
77% 77% 77% 75% 75% 75% 75% 73%
60%
Providing more
information on how
big data can help
our company reach
business goals
Providing a better
understanding of
what big data my
company collects
Providing tools that
allow us to leverage
text-based
content—such as
email, social media,
and customer
support notes—for
analytics
Employing
centralized talent to
manage big data
utilization across
functions
Employing more
agile data
management
systems and
software to
organize big data
Providing evidence
proving how big
data has enabled
better business
decisions
Aligning internally
on who is
responsible for
utilizing big data
Providing a “one-
stop-shop” solution
for employees
across functions to
easily access and
use big data
Hiring a Chief Data
Officer (CDO) or
other C-suite data
analytics leader
Somewhat agree Strongly agree
Q19: To what extent do you agree that each of the following would enable your company to more
efficiently leverage big data to make business decisions?
• Respondents are most likely to “strongly agree” that employing more agile data management systems to organize
big data would enable their company to more efficiently leverage big data
26
Looking to the future, respondents agree big data will become more easily accessed
Q20: Thinking to the future of leveraging big data to make business decisions, to what extent do you
agree that each of the following statements will be true in 3 years?
[Showing % who strongly + somewhat agree]
27
67% 64% 63% 61%
The analytic skills necessary to
leverage big data to make
business decisions will be just as
common as word processing
skills are today
Every employee, regardless of
business unit, will be able to
efficiently leverage big data
when making business decisions
that are relevant to their job
The Chief Data Officer will be the
driver of organizational
effectiveness and competitive
success at large companies
Finding and using the correct
data will be as easy as running a
typical Google search
28
Appendix
29
Full statement Shortened Statement
People
Finding and hiring skilled big data analytics talent is difficult Finding and hiring skilled big data analytics talent is difficult
The value of analytics is understood, but not being quantified and articulated adequately
enough to secure buy-in
The value of analytics is understood, but not being quantified and articulated adequately
enough to secure buy-in
Ad hoc data analysis is not widely used and valued in our organization Ad hoc data analysis is not widely used and valued in our organization
Process
Data is siloed and difficult to find and leverage — the right data is not easily accessible to
those who need it
Data is siloed and difficult to find and leverage
It is not clear to stakeholders across the company what big data is available and to whom It is not clear to stakeholders across the company what big data is available and to whom
A great deal of our data is not being incorporated into analytics projects today, leaving us
with a partial business view
A great deal of our data is not being incorporated into analytics projects today, leaving us
with a partial business view
“Shadow analytics” – where business users perform analytics in Excel spreadsheets - leads
to data governance problems
“Shadow analytics” leads to data governance problems
Business users spend more time gathering data to analyze than performing actual analysis Business users spend more time gathering data to analyze than performing actual analysis
Although my company’s information technology group stores and secures company-wide
big data, data is not put into the hands of the right business leaders needed to leverage it
to make business decisions and create value.
Company-wide big data, data is not put into the hands of the right business leaders
Tools & Technology
There is no standard way the company measures success of big data initiatives There is no standard way the company measures success of big data initiatives
There is too heavy a reliance on manual methods and trial-and-error when preparing data
for analytics
There is too heavy a reliance on manual methods and trial-and-error when preparing data
We can’t trust that our data is accurate and up-to-date We can’t trust that our data is accurate and up-to-date
Our legacy data storage systems require too much up-front processing to meet today’s
business requirements
Our legacy data storage systems require too much processing to meet today’s business
requirements
We do not leverage enough text-based content – such as email, social media, customer
support notes – for analytics
We do not leverage enough text-based content for analytics
Challenges: Full and Shortened Statements

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Attivio Big Data Survey

  • 1. 1 Attivio Big Data Decision Makers Survey Findings May 2016
  • 2. Methodology We conducted a 10-minute online survey among n = 150 individuals in data-related roles. The survey was fielded from April 21st- May 5th, 2016. Audience Definition Sample Size Data Leaders • Work in companies with at least 5,000 employees • Director-level or above • Has influence over decisions to leverage big data to inform company business decisions • Has influence over decision to partner with business intelligence and big data software vendors • Works in a role related to: o Big Data o Data Strategy o Data Management o Data Integration o Compliance/ Risk o Analytics o Business Intelligence N=150 2
  • 3. 3 Executive Summary • Virtually all big data leaders are optimistic that their companies are headed in the right direction when it comes to leveraging big data efficiently— their companies are dedicating new talent and tools to big data initiatives, and also gaining internal alignment around how big data will be used. • Companies with big data leaders “very” or “extremely” successful at leveraging big data to make business decisions—however, nearly all plan to continue investing in resources dedicated to big data and only 51% say their company leverages big data extensively, across all business units. • The challenges data leaders’ companies face are wide-ranging, but companies have the most room for improvement when it comes to the tools and technologies dedicated to big data and most respondents say that internal bottlenecks between the information technology and business units prevent data from being accessed quickly and efficiently. Key challenges data leaders face include: o “Shadow analytics” leading to data governance problems o Business users spending more time gathering data than performing analysis o Legacy data storage systems requiring too much processing to meet today’s business requirements o Too heavy a reliance on manual methods when prepping data • There are a wide-range of resources companies need to leverage big data include better tools, more centralized talent and more information on why leveraging big data is valuable.
  • 4. 4 We first explored the extent to which data leaders’ companies are leveraging big data today and their outlook for the future
  • 5. Nearly all respondents believe that their company is headed in the right direction when it comes to leveraging big data efficiently Headed in the right directionOff on the wrong track Q2: When it comes to leveraging big data efficiently, do you believe your company is headed in the right direction or off on the wrong track? 94%6% 5
  • 6. Respondents cite more investment in new talent and technologies, and further alignment on big data operations as the key reasons they are optimistic Investing in Talent Investing in New Technologies Aligning on Big Data “We hired professionals with proven experience in this area.” Q3: Why do you say your company is headed in the right direction when it comes to leveraging big data efficiently? “We have added many servers and a highly functioning system with many ways to protect data/information.” “Advanced data software options give us an edge in the market place.” “Our company is starting to truly understand the gains that can be had using big data. It will be a priority going forward.” “We have many new skilled workers in our company who have a great deal of experience dealing with traffic commerce and this frees up any clusters in our data flow.” “We are getting the right parties involved in addressing this. All too often, IT goes off on their own way due to the lack of assistance from the line of business units.” “We have started pilot programs in certain departments to see how big data can inform our decisions and will use the results to formulate a broader strategy.” 6
  • 7. Virtually all respondents say their company encourages its employees to ground business decisions in data and evidence 60% 38% 2% Strongly encouraged Somewhat encouraged Not encouraged Q13: To what extent is it encouraged at your company for employees to ground business decisions in data and evidence? 7
  • 8. Perceptions of success are high, although less than one-quarter believe they are “extremely successful” 23% 39% 30% 8% 0% Extremely successful Very successful Somewhat successful Not very successful Not at all successful Q1: How successful do you believe your company is at leveraging big data to make business decisions today? 8
  • 9. Despite today’s success, nearly all believe that their company’s investment in big data resources will increase in the next five years 81% 8% 11% Investment will increase Investment will decrease Investment will stay the same Q14: How do you believe your company’s investment in resources (e.g., talent, tools and technologies) to help leverage big data will change in the next five years? 9
  • 10. 10 We gauged where respondents’ companies stand when it comes to three key components of leveraging big data Talent TechnologiesProcess
  • 11. 2% 7% 13% 35% 43% Most respondents (78%) work at companies where there is a member of the C-Suite responsible for driving their ability to compete on analytics Q7: Which of the following best describes your company when it comes to the talent it dedicates to managing big data? My company has one member of the C- Suite responsible for driving our ability to compete on analytics; this leader works seamlessly with other members of the C-Suite My company has one member of the C-Suite responsible for driving our ability to compete on analytics who works independently to determine how big data will be used My company does not have a member of the C-Suite responsible for driving analytics but has a centralized team with responsibility for managing big data across company functions My company does not have a member of the C- Suite responsible for driving analytics but some company divisions employ talent dedicated to managing their big data My company has not yet employed any talent exclusively dedicated to managing big data Least Mature Most Mature Talent Spectrum Shortened statements used 11
  • 12. 3% 7% 13% 41% 36% Most respondents (64%) say that bottlenecks prevent big data from being accessed quickly and efficiently Q8: Which of the following best describes your company when it comes to how big data is accessed and shared across divisions? There is a set process for accessing and sharing big data across divisions at my company and this process is widely understood; no bottlenecks exist for accessing data quickly and efficiently There is a set process for accessing and sharing big data across divisions at my company that is widely understood across divisions; however, bottlenecks prevent big data from being accessed quickly and efficiently There is a set process for accessing and sharing big data across divisions at my company, but this process is not widely understood across divisions due to the bottlenecks that exist Although big data can be accessed and shared across divisions at my company, there is no set process for doing so as there are too many bottlenecks Bottlenecks at my company make it impossible for big data to be accessed and shared across divisions Least Mature Most Mature Process Spectrum Shortened statements used 12
  • 13. 1% 5% 23% 31% 39% In nearly one-third of respondents’ companies, divisions do not have complete visibility into data across all big data sources Q9: Which of the following best describes your company when it comes to the tools and technologies it dedicates to organizing and leveraging big data? My company uses effective tools to organize and provide complete visibility into all big data sources across divisions, including structured and unstructured data My company uses effective tools to organize and provide complete visibility into all big data sources across divisions, including structured data; today, we do not have tools to organize and provide visibility into unstructured data My company uses tools to organize big data sources across divisions, but the limitations of the tools means we cannot organize big data effectively and do not have complete visibility into all big data sources My company does not use tools to organize big data across divisions, but some divisions have their own tools to organize big data My company does not use any tools to organize big data today Least Mature Most Mature Technology Spectrum Shortened statements used 13
  • 14. 1% 5% 23% 31% 39% Respondents are “least mature” when it comes to the technology dedicated to big data Least Mature Most Mature 3% 7% 13% 41% 36% 2% 7% 13% 35% 43% People Process Technology Shortened statements 14
  • 15. Ultimately, only half of data leaders say that big data is leveraged extensively in their company, throughout all business units 51% 34% 13% 2% 1% Big data is leveraged extensively, throughout all business units / operations Big data is leveraged regularly, but only in some business units / operations Big data is occasionally leveraged, in a few select cases My company has not yet implemented processes to leverage big data, but plans to in the future My company has not yet implemented processes to leverage big data, and has no plans to in the future Q4: Which of the following best describes your company today when it comes to big data to inform business decisions? 15
  • 16. 16 Despite optimism and some success, there are still challenges that data leaders face
  • 17. Although most data leaders believe their companies are making a sufficient effort to leverage big data, a subset say they are not doing enough 69%31% Making a sufficient effortNot doing enough Q12: Thinking about your company’s big data management practices, do you think leadership is making a sufficient effort to leverage big data when making business decisions or are they not doing enough? 17
  • 18. Respondents report needing better technology, fewer silos between departments, and more internal buy-in to enable their company to more efficiently leverage big data Better Technology Fewer Silos Between Departments More Internal Buy-In Q18. What do you believe would enable your company to more efficiently leverage big data to make business decisions? “It boils down to investments in software and getting all systems on the same platform across the company.” “Better collaboration between units. We are very siloed. I think we need a comprehensive standardization of how we leverage big data.” “More cross-functional collaboration.” “Strategic changes from the top around utilization and implementation of big data resources.” “Having board members better understand the scope of what we are trying to accomplish.” “A general push from upper management to ramp up our efforts to manage, aggregate, and analyze big data would be a good first step.” “More text based data needs to be utilized and the manual excel spreadsheets need to be eliminated in favor of more automated analytical software that will sort the data more effectively.” 18
  • 19. Though respondents are optimistic about their ability to leverage big data, few are using all their data in making business decisions 19% 26% 32% 17% 6% 0%-25% 26%- 50% 51%-75% 76%-90% 91%-100% Q10: What percent of all the data collected by your company do you think your company is analyzing and utilizing today to make business decisions? Only 23% of respondents utilize over three-quarters of their available big data 19
  • 20. . . . and accessing disparate data sources can frequently take a day or longer Q11: How long does it generally take business users at your company to access disparate big data sources for a single analysis? 11% 27% 24% 19% 10% 5% 4% A few minutes Under an hour A few hours About 24 hours About one week or less About two to four weeks More than four weeks 37% say it takes one day or more to access big data sources for an analysis 20
  • 21. 49% 42% 28% 17% 17% 14% 66% 59% 42% Finding and hiring skilled big data analytics talent is difficult The value of analytics is understood, but not being quantified and articulated adequately enough to secure buy-in Ad hoc data analysis is not widely used and valued in our organization Somewhat agree Strongly agree Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently? People Challenges When it comes to the “people” needed for success, finding and hiring skilled big data analytics talent is a major challenge 21
  • 22. 40% 39% 35% 33% 29% 25% 19% 20% 17% 15% 17% 19% 59% 59% 52% 49% 45% 44% “Shadow analytics” leads to data governance problems Business users spend more time gathering data than performing analysis A great deal of our data is not being incorporated into analytics projects today Company-wide big data, data is not put into the hands of the right business leaders Data is siloed and difficult to find and leverage It is not clear to stakeholders across the company what big data is available and to whom Somewhat agree Strongly agree The biggest challenges around “process” concern data governance and business users spending too much time gathering data vs. analysis Shortened statements Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently? Process Challenges 22
  • 23. Respondents are split on whether big data is easily accessed or siloed within functions 59%41% Unit leaders can easily access big data, and it is easy for them to use the data to help make business decisions quickly Data is siloed within functions and it is difficult for unit leaders to access the big data they need when they need it Q17: Which of the following best describes your company today when it comes to big data management? 23
  • 24. 35% 33% 31% 34% 22% 24% 15% 17% 13% 11% 59% 48% 48% 47% 33% Our legacy data storage systems require too much processing to meet today’s business requirements There is no standard way the company measures success of big data initiatives There is too heavy a reliance on manual methods and trial- and-error when preparing data We do not leverage enough text-based content for analytics We can’t trust that our data is accurate and up-to-date Somewhat agree Strongly agree The main technology challenge data leaders face is legacy data storage systems requiring too much processing to meet today’s business requirements Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently? Technology Challenges 24
  • 25. Only one-fifth of data leaders are “extremely satisfied” with the resources their company dedicates to big data Q6: What resources (e.g., talent, tools and technologies) do you believe your company would need to be more successful when it comes to organizing big data and leveraging it to make business decisions? Q5: How satisfied are you with the resources (e.g., talent, tools and technologies) your company currently devotes to organizing big data and leveraging it to make business decisions? [Showing “extremely satisfied”] 20% “We need to scale up our use of big data once the pilots are done, which will mean hiring more talent and giving the tools and technology to more people.” “A more defined mission statement developed and implemented by talented staff using the proper technology.” “To start off with, I would like to see an increase to the members of the team who are responsible for Big Data Capture and Analysis. They are a bit understaffed to meet current needs. Two to Three people with the right training would make a big difference.” 25
  • 26. Responses are fragmented when it comes to the resources needed—there is no one area where big data analytics is “perfect” 42% 46% 45% 49% 35% 46% 38% 36% 39% 35% 31% 32% 26% 40% 29% 37% 37% 21% 77% 77% 77% 75% 75% 75% 75% 73% 60% Providing more information on how big data can help our company reach business goals Providing a better understanding of what big data my company collects Providing tools that allow us to leverage text-based content—such as email, social media, and customer support notes—for analytics Employing centralized talent to manage big data utilization across functions Employing more agile data management systems and software to organize big data Providing evidence proving how big data has enabled better business decisions Aligning internally on who is responsible for utilizing big data Providing a “one- stop-shop” solution for employees across functions to easily access and use big data Hiring a Chief Data Officer (CDO) or other C-suite data analytics leader Somewhat agree Strongly agree Q19: To what extent do you agree that each of the following would enable your company to more efficiently leverage big data to make business decisions? • Respondents are most likely to “strongly agree” that employing more agile data management systems to organize big data would enable their company to more efficiently leverage big data 26
  • 27. Looking to the future, respondents agree big data will become more easily accessed Q20: Thinking to the future of leveraging big data to make business decisions, to what extent do you agree that each of the following statements will be true in 3 years? [Showing % who strongly + somewhat agree] 27 67% 64% 63% 61% The analytic skills necessary to leverage big data to make business decisions will be just as common as word processing skills are today Every employee, regardless of business unit, will be able to efficiently leverage big data when making business decisions that are relevant to their job The Chief Data Officer will be the driver of organizational effectiveness and competitive success at large companies Finding and using the correct data will be as easy as running a typical Google search
  • 29. 29 Full statement Shortened Statement People Finding and hiring skilled big data analytics talent is difficult Finding and hiring skilled big data analytics talent is difficult The value of analytics is understood, but not being quantified and articulated adequately enough to secure buy-in The value of analytics is understood, but not being quantified and articulated adequately enough to secure buy-in Ad hoc data analysis is not widely used and valued in our organization Ad hoc data analysis is not widely used and valued in our organization Process Data is siloed and difficult to find and leverage — the right data is not easily accessible to those who need it Data is siloed and difficult to find and leverage It is not clear to stakeholders across the company what big data is available and to whom It is not clear to stakeholders across the company what big data is available and to whom A great deal of our data is not being incorporated into analytics projects today, leaving us with a partial business view A great deal of our data is not being incorporated into analytics projects today, leaving us with a partial business view “Shadow analytics” – where business users perform analytics in Excel spreadsheets - leads to data governance problems “Shadow analytics” leads to data governance problems Business users spend more time gathering data to analyze than performing actual analysis Business users spend more time gathering data to analyze than performing actual analysis Although my company’s information technology group stores and secures company-wide big data, data is not put into the hands of the right business leaders needed to leverage it to make business decisions and create value. Company-wide big data, data is not put into the hands of the right business leaders Tools & Technology There is no standard way the company measures success of big data initiatives There is no standard way the company measures success of big data initiatives There is too heavy a reliance on manual methods and trial-and-error when preparing data for analytics There is too heavy a reliance on manual methods and trial-and-error when preparing data We can’t trust that our data is accurate and up-to-date We can’t trust that our data is accurate and up-to-date Our legacy data storage systems require too much up-front processing to meet today’s business requirements Our legacy data storage systems require too much processing to meet today’s business requirements We do not leverage enough text-based content – such as email, social media, customer support notes – for analytics We do not leverage enough text-based content for analytics Challenges: Full and Shortened Statements