Attivio Survey of Big Data Decision Makers

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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 Integrationo Compliance/ Risko Analyticso Business Intelligence

N=150

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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 unitsprevent 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.

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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 directionwhen it comes to leveraging big data efficiently

Headed in the right direction Off 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%

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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.”

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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?

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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?

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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?

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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


Process Spectrum


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


Technology Spectrum


1% 5% 23% 31% 39%

Respondents are “least mature” when it comes to the technology dedicated to big data


3% 7% 13% 41% 36%

2% 7% 13% 35% 43%

People

Process

Technology

Shortened statements14

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 leveragedextensively, throughout allbusiness units / operations

Big data is leveraged regularly,but only in some business units

/ operations

Big data is occasionallyleveraged, in a few select cases

My company has not yetimplemented processes to

leverage big data, but plans toin the future

My company has not yetimplemented processes to

leverage big data, and has noplans 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 effort Not 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?

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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.”

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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

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. . . 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 fewminutes

Under anhour

A few hours About 24hours

About oneweek or less

About two tofour weeks

More thanfour 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 analyticstalent is difficult

The value of analytics is understood, butnot being quantified and articulatedadequately enough to secure buy-in

Ad hoc data analysis is not widely usedand 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 spendmore time gatheringdata than performing

analysis

A great deal of our datais not being incorporated

into analytics projectstoday

Company-wide big data,data is not put into the

hands of the rightbusiness leaders

Data is siloed anddifficult to find and

leverage

It is not clear tostakeholders across thecompany what big data

is available and to whom


The biggest challenges around “process” concern data governance and business users spending too much time gathering data vs. analysis

Shortened statements


Process Challenges

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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?

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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 thecompany measures success of

big data initiatives

There is too heavy a relianceon manual methods and trial-

and-error when preparingdata

We do not leverage enoughtext-based content for

analytics

We can’t trust that our data is accurate and up-to-date


The main technology challenge data leaders face is legacy data storage systems requiring too much processing to meet today’s business requirements


Technology Challenges

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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.”

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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 moreinformation on how

big data can helpour company reach

business goals

Providing a betterunderstanding ofwhat big data mycompany collects

Providing tools that allow us to leverage

text-based content—such as

email, social media, and customer

support notes—for analytics

Employingcentralized talent to

manage big datautilization across

functions

Employing moreagile data

managementsystems andsoftware to

organize big data

Providing evidenceproving how bigdata has enabledbetter business

decisions

Aligning internallyon who is

responsible forutilizing big data

Providing a “one-stop-shop” solution

for employees across functions to easily access and

use big data

Hiring a Chief DataOfficer (CDO) or

other C-suite dataanalytics leader


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

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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]

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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

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Appendix

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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

ProcessData 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 analyticsWe do not leverage enough text-based content for analytics

Challenges: Full and Shortened Statements

Date post:	15-Jan-2017
Category:	Technology
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