Transcript

May 31, 2016

Dresner Advisory Services, LLC

2016 Edition

Wisdom of Crowds®

Business Intelligence Market Study

Licensed to TIBCO

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

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Disclaimer

This report should be used for informational purposes only. Vendor and product selections should be made

based on multiple information sources, face-to-face meetings, customer reference checking, product

demonstrations, and proof-of-concept applications.

The information contained in all Wisdom of Crowds® Market Study Reports reflects the opinions expressed in

the online responses of individuals who chose to respond to our online questionnaire and does not represent

a scientific sampling of any kind. Dresner Advisory Services, LLC shall not be liable for the content of

reports, study results, or for any damages incurred or alleged to be incurred by any of the companies

included in the reports as a result of the content.

Reproduction and distribution of this publication in any form without prior written permission is forbidden.

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Business Intelligence: A Definition Business intelligence (BI) is “knowledge gained through the access and analysis of business information.

Business intelligence tools and technologies include query and reporting, OLAP (online analytical

processing), data mining and advanced analytics, end-user tools for ad hoc query and analysis, and

dashboards for performance monitoring.”

Howard Dresner, The Performance Management Revolution: Business Results Through Insight and Action

(John Wiley & Sons, 2007)

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Introduction This year we celebrate the ninth anniversary of Dresner Advisory Services! Our thanks

to all of you for your continued support and ongoing encouragement.

Since our founding in 2007, we have worked hard to set the “bar” high—challenging

ourselves to innovate and lead the market—offering ever greater value with each

successive year.

Our first market report in 2010 set the stage for where we are today. Since that time we

have expanded our agenda and have added new research topics every year since. For

2016 we’re on track to release 15 major reports, including, this, our BI flagship report—

in its seventh year of publication!

In addition to our ongoing coverage of key topics such as embedded BI, big data

analytics and advanced and predictive analytics, we have added new topics including

Collective InsightsTM (blending collaboration and governance) and systems integrators.

This latest installment of our flagship business intelligence market study also continues

to evolve. This year we have added a new section examining the chief analytics and

chief data officer roles. And, as with every year, we have begun tracking additional

technologies and initiatives including governance, streaming data analysis, and data

storytelling.

We hope you enjoy this report!

Best,

Howard Dresner Chief Research Officer Dresner Advisory Services

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Contents Business Intelligence: A Definition .................................................................................. 3

Introduction ..................................................................................................................... 4

Benefits of the Study ..................................................................................................... 10

Consumer Guide ........................................................................................................ 10

Supplier Tool .............................................................................................................. 10

External Awareness ................................................................................................ 10

Internal Planning ..................................................................................................... 10

About Howard Dresner and Dresner Advisory Services ................................................ 11

About Jim Ericson ......................................................................................................... 12

Survey Method and Data Collection .............................................................................. 13

Data Collection ........................................................................................................... 13

Data Quality ............................................................................................................... 14

New for 2016 ................................................................................................................. 14

Executive Summary ...................................................................................................... 16

Study Demographics ..................................................................................................... 17

Geography ................................................................................................................. 17

Functions ................................................................................................................... 18

Vertical Industries ...................................................................................................... 19

Organization Size ....................................................................................................... 20

Analysis and Trends ...................................................................................................... 22

Departments/Functions Driving Business Intelligence ............................................... 22

Functions Driving Business Intelligence by Major Geography ................................ 25

Functions Driving Business Intelligence by Vertical Industry .................................. 26

Functions Driving Business Intelligence by Organization Size ............................... 27

User Roles Targeted for Business Intelligence .......................................................... 28

Targeted Users for Business Intelligence by Geography ........................................ 30

User Targets for Business Intelligence by Organization Size ................................. 31

User Targets for Business Intelligence by Vertical Industries ................................. 32

Objectives for Business Intelligence .......................................................................... 33

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Business Intelligence Objectives by Geography ..................................................... 34

Business Intelligence Objectives by Function ......................................................... 35

Business Intelligence Objectives by Vertical Industry ............................................. 36

Business Intelligence Objectives by Organization Size .......................................... 37

Penetration of Business Intelligence Solutions .......................................................... 38

Expansion Plans for Business Intelligence Through 2018 ...................................... 39

Current Business Intelligence Penetration by Geography ...................................... 40

Planned Business Intelligence Penetration by Geography ..................................... 41

Business Intelligence Penetration by Function ....................................................... 42

Current Business Intelligence Penetration by Vertical Industry............................... 44

Planned Business Intelligence Penetration by Vertical Industry ............................. 45

Current Business Intelligence Penetration by Organization Size ............................ 46

Planned Business Intelligence Penetration by Organization Size ........................... 47

Chief Data and Chief Analytics Officers ..................................................................... 48

Enterprises with Chief Data or Chief Analytics Officers.............................................. 48

Enterprises with Chief Data or Chief Analytics Officers by Geography ...................... 49

Enterprises with Chief Data or Chief Analytics Officers by Industry ........................... 50

Enterprises with Chief Data or Chief Analytics Officers by Organization Size ............ 51

Enterprises with Chief Data and Chief Analytics Officers Reporting Structure ........... 52

Chief Data Officer and Success with BI by Reporting Structure................................. 53

Chief Analytics Officer and Success with BI by Reporting Structure .......................... 54

Number of Business Intelligence Tools in Use ........................................................... 55

Number of Business Intelligence Tools in Use 2014 to 2016 .................................. 55

Number of Business Intelligence Tools by Geography ........................................... 56

Number of Business Intelligence Tools by Function ............................................... 57

Number of Business Intelligence Tools by Vertical Industry ................................... 58

Number of Business Intelligence Tools by Organization Size ................................. 59

Technologies and Initiatives Strategic to Business Intelligence ................................. 60

Technology Priority Changes from 2013 ................................................................. 61

Technologies and Initiatives Strategic to Business Intelligence by Geography ...... 63

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Technologies and Initiatives Strategic to Business Intelligence by Function .......... 64

Technologies and Initiatives Strategic to Business Intelligence by Vertical Industry

................................................................................................................................ 65

Technologies and Initiatives Strategic to Business Intelligence by Organization Size

................................................................................................................................ 66

Business Intelligence and the State of Data............................................................... 67

Business Intelligence and the State of Data by Geography .................................... 69

Business Intelligence and the State of Data by Function ........................................ 70

Business Intelligence and the State of Data by Vertical Industry ............................ 71

Business Intelligence and the State of Data by Organization Size ......................... 72

Business Intelligence and Action on Insight ............................................................... 73

Business Intelligence and Action on Insight by Geography .................................... 75

Business Intelligence and Action on Insight by Function ........................................ 76

Business Intelligence and Action on Insight by Vertical Industry ............................ 77

Business Intelligence and Action on Insight by Organization Size .......................... 78

Success with Business Intelligence ........................................................................... 79

Reasons Why Business Intelligence Succeeds ...................................................... 80

Reasons Why Business Intelligence Fails .............................................................. 81

Success with Business Intelligence by Organization Size ...................................... 82

Success with Business Intelligence by BI Objectives ............................................. 83

Success with Business Intelligence by Targeted Users .......................................... 84

Success with Business Intelligence and Technology Priorities ............................... 85

Success with Business Intelligence and Number of BI Tools ................................. 86

Success with Business Intelligence and the State of Data ..................................... 87

Success with Business Intelligence and Action on Insight ...................................... 88

Success with Business Intelligence and Penetration of Users ................................ 89

Industry and Vendor Analysis ........................................................................................ 91

Scoring Criteria .......................................................................................................... 91

Industry Performance ................................................................................................. 92

Sales/Acquisition Experience ................................................................................. 92

Value ...................................................................................................................... 93

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Quality and Usefulness of Product.......................................................................... 94

Technical Support ................................................................................................... 95

Consulting ............................................................................................................... 96

Integrity ................................................................................................................... 97

Recommended ....................................................................................................... 98

Performance Improvements ................................................................................... 99

Vendor Ratings ........................................................................................................... 101

Business Intelligence Market Models .......................................................................... 102

Customer Experience Model .................................................................................... 102

Vendor Credibility Model .......................................................................................... 104

Detailed Vendor Ratings ............................................................................................. 106

Birst Detailed Score .............................................................................................. 107

Dell Detailed Score ............................................................................................... 108

Dimensional Insight Detailed Score ...................................................................... 109

Domo Detailed Score ............................................................................................ 110

Dundas Detailed Score ......................................................................................... 111

GoodData Detailed Score ..................................................................................... 112

IBM Detailed Score ............................................................................................... 113

Infor Detailed Score .............................................................................................. 114

Information Builders Detailed Score ..................................................................... 115

Jedox Detailed Score ............................................................................................ 116

Klipfolio Detailed Score ......................................................................................... 117

Logi Analytics Detailed Score ............................................................................... 118

Looker Detailed Score .......................................................................................... 119

Microsoft Detailed Score ....................................................................................... 120

MicroStrategy Detailed Score ............................................................................... 121

OpenText Detailed Score ..................................................................................... 122

Oracle Detailed Score ........................................................................................... 123

Pentaho Detailed Score ........................................................................................ 124

Pyramid Analytics Detailed Score ......................................................................... 125

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Qlik Detailed Score ............................................................................................... 126

RapidMiner Detailed Score ................................................................................... 127

Salesforce Detailed Score .................................................................................... 128

SAP Detailed Score .............................................................................................. 129

SAS Detailed Score .............................................................................................. 130

SiSense Detailed Score ........................................................................................ 131

Tableau Software Detailed Score ......................................................................... 132

TIBCO Software Detailed Score ........................................................................... 133

Yellowfin Detailed Score ....................................................................................... 134

Other Dresner Advisory Services Research Reports .................................................. 135

Dresner Advisory Services - 2016 Wisdom of Crowds Survey .................................... 136

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Benefits of the Study The Wisdom of Crowds® Business Intelligence Market Study provides a wealth of

information and analysis—offering value to both consumers and producers of Business

Intelligence technology and services.

Consumer Guide

As an objective source of industry research, consumers use the Wisdom of Crowds®

Business Intelligence Market Study to understand how their peers leverage and invest

in business intelligence and related technologies.

Using our trademark 33-criteria vendor performance measurement system, users glean

key insights into BI software supplier performance, enabling:

Comparisons of current vendor performance to industry norms

Identification and selection of new vendors

Supplier Tool

Vendor Licensees use the Wisdom of Crowds® Business Intelligence Market Study in

several important ways such as:

External Awareness

- Build awareness for the business intelligence market and supplier brand, citing

Wisdom of Crowds® business intelligence Market Study trends and vendor

performance

- Create lead and demand-generation for supplier offerings through association with

Wisdom of Crowds® Business Intelligence Market Study brand, findings, webinars,

etc.

Internal Planning

- Refine internal product plans and align with market priorities and realities as

identified in Wisdom of Crowds® Business Intelligence Market Study

- Better understand customer priorities, concerns, and issues

- Identify competitive pressures and opportunities

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About Howard Dresner and Dresner Advisory Services The Wisdom of Crowds® Business Intelligence Market Study was conceived, designed

and executed by Dresner Advisory Services, LLC—an independent advisory firm—and

Howard Dresner, its President, Founder and Chief Research Officer.

Howard Dresner is one of the foremost thought leaders in business intelligence and

performance management, having coined the term “Business Intelligence” in 1989. He

has published two books on the subject, The Performance

Management Revolution – Business Results through Insight

and Action (John Wiley & Sons, Nov. 2007) and Profiles in

Performance – Business Intelligence Journeys and the

Roadmap for Change (John Wiley & Sons, Nov. 2009). He

lectures at forums around the world and is often cited by the

business and trade press.

Prior to Dresner Advisory Services, Howard served as chief

strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he

led its business intelligence research practice for 13 years.

Howard has conducted and directed numerous in-depth primary research studies over

the past two decades and is an expert in analyzing these markets.

Through the Wisdom of Crowds® Business Intelligence market research reports, we

engage with a global community to redefine how research is created and shared. Other

research reports include:

- Advanced and Predictive Analytics

- Big Data Analytics

- Business Intelligence Competency Center

- Cloud Computing and Business Intelligence

- Collective InsightsTM

- Embedded Business Intelligence

- End User Data Preparation

- Internet of Things and Business Intelligence

- Location Intelligence

Howard (www.twitter.com/howarddresner) conducts a weekly Twitter “tweetchat” on

Fridays at 1:00 p.m. ET. The hashtag is #BIWisdom. During these live events the

#BIWisdom community discusses a wide range of business intelligence topics.

You can find more information about Dresner Advisory Services at

www.dresneradvisory.com.

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About Jim Ericson Jim Ericson is a research director with Dresner Advisory Services.

Jim has served as a consultant and journalist who studies end-user management

practices and industry trending in the data and information management fields.

From 2004 to 2013 he was the editorial director at Information Management magazine

(formerly DM Review), where he created architectures for user and

industry coverage for hundreds of contributors across the breadth of

the data and information management industry.

As lead writer he interviewed and profiled more than 100 CIOs,

CTOs, and program directors in a 2010-2012 program called “25

Top Information Managers.” His related feature articles earned

ASBPE national bronze and multiple Mid-Atlantic region gold and

silver awards for Technical Article and for Case History feature

writing.

A panelist, interviewer, blogger, community liaison, conference co-chair, and speaker in

the data-management community, he also sponsored and co-hosted a weekly podcast

in continuous production for more than five years.

Jim’s earlier background as senior morning news producer at NBC/Mutual Radio

Networks and as managing editor of MSNBC’s first Washington, D.C. online news

bureau cemented his understanding of fact-finding, topical reporting, and serving broad

audiences.

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Survey Method and Data Collection As in our original Wisdom of Crowds® Business Intelligence Market Study, we

constructed a survey instrument to collect data and used social media and crowd-

sourcing techniques to recruit participants.

We also include our own research community of over 3,500 organizations (versus 3,000

in 2015) as well as vendors’ customer communities.

Data Collection

Our survey base in 2016 includes 1,524 respondents who offered their time to complete

our extensive annual survey. In the years since our first report, interest in the study in

the form of completed surveys has more than tripled.

Figure 1 - Number of survey respondents 2010 to 2016

458

633

856

1182

1283

1495 1524

0

200

400

600

800

1000

1200

1400

1600

1800

2010 2011 2012 2013 2014 2015 2016

Numbers of Survey Respondents 2010 to 2016

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Data Quality

We carefully scrutinized and verified all respondent entries to ensure that the study

includes only qualified participants.

New for 2016 For 2016, we again expanded our research objectives substantially. As with 2015, this

is particularly evident in the area of user trending. This year’s study adds:

Five additional technologies and initiatives strategic to business intelligence

(reporting, governance, streaming data analysis, cognitive BI and edge

computing) to extend our study to a total of 30 areas.

New polling of the penetration of chief data officers (CDOs) and chief analytics

officers (CAOs) within organizations along with cross-tabular analysis (maturity,

geography, organization size, success, etc.)

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Executive

Summary

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Executive Summary User Analysis:

- For the first time, operations moved ahead of executives as the leading driver of

BI. BICC and strategic planning lost the most influence (pp. 22-27).

- Executives and middle managers remain the most-targeted audiences for BI

though both have seen declines over time (pp. 28-32).

- "Making better decisions" remains the top BI objective, followed by operational,

revenue and customer service improvements (pp. 33-37).

- Penetration of BI has grown noticeably in 2016 and near-term penetration growth

appears achievable, with small organizations leading the way (pp. 38-47).

- The current uptake and maturity of chief data and chief analytics officers is

modest, with fewer than 15 percent of (mostly large) organizations adopting the

title(s). Most report to the CEO, fewer to IT and finance (pp. 48-54).

- Most organizations continue to employ one, two or three BI tools. Manufacturing

uses the fewest, healthcare the most (pp. 55-59).

- Fundamental BI technologies—reporting, dashboards and self-service—top the

2016 list; cognitive BI and IoT are "fringe" priorities (pp. 60-66).

- Organizations say their "state of data" organization is very good: 64 percent

report either "data as truth" or a “common view of data” (pp. 67-72).

- Organizational ability to take "action on insight" is very high: 83 percent of

respondents report either "closed loop" or ad hoc capabilities (pp.73-78).

- The core measure of success with business intelligence showed a small net gain.

Small organizations are most likely to be "completely" successful. Successful

organizations are most broadly involved and penetrated with executive

leadership and with fewer tools (pp. 79-86).

- Advanced "states of data" (views/capabilities), ability to "act on insight," and high

employee penetration correlate profoundly with levels of success with business

intelligence (pp. 87-89).

Industry Analysis:

- Overall industry performance reflects vendor attention to weaknesses, yielding

improved customer reviews (pp. 92-99). Professionalism / product knowledge

keep the highest and most consistent scores in sales/acquisition, while

responsiveness, flexibility, business practices, and follow-up have improved (p.

92). End users believe they are getting high and improving value from industry

vendors over time (p. 93). Product quality and usefulness have improved across

most measures (p. 94). Technical support performed well in the most important

parameters (p. 95). Vendor consulting trailed only one area (p. 96).

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Study Demographics Our 2016 survey base provides a cross-section of data across geographies, functions,

organization sizes, and vertical industries. We believe that, unlike other industry

research, this supports a more representative sample and better indicator of true market

dynamics. We have constructed cross-tab analyses using these demographics to

identify and illustrate important industry trends.

Geography

Slightly more than one-half of respondents work at North America-based organizations

(including the United States, Canada, and Puerto Rico). EMEA accounts for about 30

percent of respondents; the remainder are distributed across Asia Pacific and Latin

America (fig. 2).

Figure 2 – Geographies represented

56.4%

29.1%

10.4%

4.1%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

North America Europe, Middle East andAfrica

Asia Pacific Latin America

Geographies Represented

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Functions

In 2016, our functional base is somewhat more balanced than in previous years with

more respondents outside information technology roles. IT accounts for the largest

group but is well offset by an almost equal number of executive respondents. BICC,

finance and marketing and sales are the next largest groups taking part in this year’s

study

Tabulating results across functions helps us develop analyses that reflect the

differences and influence of different departments within organizations.

Figure 3 - Functions represented

29% 28%

9% 8%

6% 4% 4%

3% 2%

8%

0%

5%

10%

15%

20%

25%

30%

Functions Represented

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Vertical Industries

In 2016, vertical industry distribution is similar to prior studies, led by consulting, technology, and healthcare (fig. 4). Higher education, financial services, business services, and manufacturing are the next most represented. Tabulating results across industries helps us develop analyses that reflect the maturity and direction of different business sectors.

Figure 4 - Vertical industries represented

12%

10% 9%

7% 6% 6% 5%

4% 3% 3% 2%

2% 2% 1% 1% 1% 1% 1% 1% 1% 1% 1%

19%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

18.0%

20.0%

Vertical Industries Represented

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Organization Size

Participation by organizations of different sizes (global employee head count) is well

balanced in 2016. Small organizations (1-100 employees) represent about 30 percent of

respondents, mid-size organizations (101-1,000 employees) represent 29 percent, and

large organizations (>1,000 employees) account for the remaining 40 percent (fig. 5).

Tabulating results by organization size reveals important differences in practices, planning, and maturity.

Figure 5 - Organization sizes represented

30% 29%

8% 8%

6%

17%

0%

5%

10%

15%

20%

25%

30%

35%

1 - 100 101 - 1,000 1,001 - 2,000 2,001 - 5,000 5,001 - 10,000 More than10,000

Organization Sizes Represented

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Analysis and

Trends

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Analysis and Trends

Departments/Functions Driving Business Intelligence

We asked respondents which functional areas drive business intelligence “always,”

“often,” “sometimes,” “rarely,” or “never” (fig. 6). Our results show a breadth of influence;

but for the first time, operations is the leading choice among survey respondents. (We

also note that departmental functions, e.g., marketing, sales, supply chain, all have

operational activities within.) By this measure, we might conclude that business

operations are becoming more engaged with BI or that BI is more of a “baked in” or day-

to-day tactical activity within operations. Executive management, traditionally the

leading driver, is the second-most cited functional driver in 2016. Finance and sales are

also strong drivers that “always” or “often” drive BI in more than half of organizations

responding.

Figure 6 - Functions driving business intelligence

0% 20% 40% 60% 80% 100%

Operations

Executive management

Finance

Sales

Information Technology (IT)

Marketing

Strategic planning function

Research and development (R&D)

Business Intelligence Competency Center

Supply chain

Human resources

Faculty (education)

Manufacturing

Clinical (Healthcare)

Functions Driving Business Intelligence

Always Often Sometimes Rarely Never

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As noted in fig. 6, operations has, over time, supplanted executive management as the

leading driver of business intelligence in 2016 (fig. 7). Saturation of BI could account for

some of this shift, but we note generally that frontline business users appear to be

taking more active responsibility among themselves as influential drivers (as IT and

strategic planning taper somewhat). R&D and faculty in higher education also sustained

interest, possibly hinting at future spreading or democratization of business intelligence.

Figure 7 - Functions driving business intelligence 2013 to 2016

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Functions Driving Business Intelligence 2013 to 2016

2013 2014 2015 2016

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Another instructive view of year-over-year office and departmental influence is depicted

in fig. 8. Along with an industry-specific gain in education, operations emerged as a

stronger driver of business intelligence in 2016 (countered by a similar decrease in

executive management influence). BICC and strategic planning were the functions that

lost the most influence, another indication that business might be taking greater

ownership and responsibility for business intelligence. R&D, sales, marketing, and

finance were flat or saw small decreases.

Figure 8 - Change in functions driving BI

-12%

-9%

-8%

-8%

-7%

-5%

-5%

-4%

-3%

-3%

-1%

0%

4%

6%

-14% -12% -10% -8% -6% -4% -2% 0% 2% 4% 6% 8%

Business Intelligence Competency Center

Strategic planning function

Supply chain

Human resources

Manufacturing

Information Technology (IT)

Executive management

Finance

Marketing

Clinical (Healthcare)

Sales

Research and development (R&D)

Faculty (Education)

Operations

Change in Functions Driving BI

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Functions Driving Business Intelligence by Major Geography

Operations is the strongest functional driver of business intelligence in all regions, most

notably in Latin America (fig. 9). Executive management is the second choice in all

geographies. Sales and IT are close to equally influential as executive management as

a BI driver in Asia Pacific. Along with Asia Pacific, EMEA appears to have the best

functional balance in BI drivers and, along with North America, the highest influence

from finance. BICC is the weakest driver of BI among functions studied across all

geographies.

Figure 9 - Functions driving business intelligence by geography

1

1.5

2

2.5

3

3.5

4

4.5

5

North America Asia Pacific Latin America Europe, Middle Eastand Africa

Functions Driving Business Intelligence by Geography

Operations Executive management

Finance Sales

Information Technology (IT) Marketing

Strategic planning function Business Intelligence Competency Center

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Functions Driving Business Intelligence by Vertical Industry

The importance of functional drivers of business intelligence is somewhat predictable

across industries (fig. 10). The influence of sales and supply chain are strongest in

manufacturing, and marketing leads the advertising industry. Industries are well

clustered around operations influence in the range of 3.4 to 3.9 ("sometimes" to "often"

drivers). The influence of executive management is more distributed: highest in

insurance and healthcare and lowest in advertising and higher education.

Figure 10 - Functions driving business intelligence by vertical industry

2.0

2.5

3.0

3.5

4.0

4.5Operations

Executive management

Finance

Sales

Information Technology (IT)

Marketing

Strategic planning function

Research and development(R&D)

Business IntelligenceCompetency Center

Supply chain

Human resources

Faculty (education)

Manufacturing

Clinical (Healthcare)

Functions Driving Business Intelligence by Vertical Industry

Manufacturing Healthcare Education (Higher Ed) Business services

Financial services Advertising Insurance

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Functions Driving Business Intelligence by Organization Size

Overall, executive management and operations are the most likely drivers of business

intelligence across organizations of different sizes (fig. 11). In small (1-100 employees)

organizations, sales is the third-strongest influencer, while finance ranks second at

organizations with 1,001-10,000 employees and third in midsized (101-1,001

employees) organizations. BICC is less influential among small and midsized

responding organizations, though we would not normally expect to see a business

intelligence competency center (BICC) in smaller businesses and institutions.

Functional drivers are more diversified at very large organizations of 10,000 or more

employees where departmental oversight and separate budgets are common.

Marketing holds above-average sway in both small and very large (> 10,000

employees) organizations.

Figure 11 - Functions driving business intelligence by organization size

1

1.5

2

2.5

3

3.5

4

4.5

5

1 - 100 101 - 1,000 1,001 - 10,000 More than 10,000

Functions Driving Business Intelligence by Organization Size

Executive management Finance

Sales Operations

Information Technology (IT) Marketing

Strategic planning function Research and development (R&D)

Business Intelligence Competency Center Supply chain

Human resources Faculty (education)

Manufacturing Clinical (Healthcare)

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User Roles Targeted for Business Intelligence

In 2016, executives and middle managers are about 93 percent likely to be targeted as

primary or secondary users of business intelligence (fig. 12). Middle managers are less

often seen as primary users but are as likely overall as executives to be targeted. Line

managers are targeted as primary or secondary users at three-quarters of respondent

organizations and individual contributors draw only slightly less attention. Fewer than

half of respondent organizations (26 percent primary, 21 percent secondary) currently

target customers.

Figure 12 - Targeted users for business intelligence

0% 20% 40% 60% 80% 100%

Executives

Middle managers

Line managers

Individual contributors & professionals

Customers

Suppliers

Targeted Users for Business Intelligence

Primary Secondary Not targeted

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29

Across three years of data, executives and middle managers have remained the most-

targeted audiences for business intelligence, though both have seen year-over-year

declines of 3 to 4 percent, possibly due to saturation (fig. 13). Targeting of line

managers saw a one-year decrease of 4 percent. Individual contributors, customers,

and suppliers have remained mostly flat year over year.

Figure 13 - Targeted users for business intelligence 2014 to 2016

0%

10%

20%

30%

40%

50%

60%

70%

80%

Executives MiddleManagers

Line Managers IndividualContributors

andProfessionals

Customers Suppliers

Targeted Users for Business Intelligence 2014 to 2016

2014

2015

2016

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30

Targeted Users for Business Intelligence by Geography

Executives are the most likely targets for business intelligence across all geographies,

especially Latin America, where targeting is 80 percent compared to 60-plus percent in

other regions (fig. 14). Middle managers are most targeted in North America (56

percent) followed by EMEA (54 percent) and Latin America (54 percent). Middle and

line managers are less so but more equally targeted in Asia-Pacific organizations (37 to

42 percent). Latin American respondents in our 2016 sample rarely or never report

targeting individual contributors and professionals.

Figure 14 - Targeted users for business intelligence by geography

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

North America Asia Pacific Latin America Europe, Middle Eastand Africa

Targeted Users for Business Intelligence by Geography

Executives Middle managers

Line managers Individual contributors & professionals

Customers Suppliers

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31

User Targets for Business Intelligence by Organization Size

Large organizations (>1,000 employees) are somewhat less likely to target executive

management than smaller organizations, which might simply reflect overall headcount

(fig. 15). Large organizations of 1,001 to 10,000 employees are most likely to target

middle managers, and at a rate equal or greater than executives. Very large

organizations (> 10,000 employees) are slightly more likely to target line managers and

individual contributors and professionals. Small organizations of one to 100 employees

are most likely to target customers (31 percent).

Figure 15 - Targeted business intelligence users by organization size

0%

10%

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40%

50%

60%

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100%

1 - 100 101 - 1,000 1,001 - 10,000 More than 10,000

Targeted Users for Business Intelligence by Organization Size

Executives Middle managers

Line managers Individual contributors & professionals

Customers Suppliers

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32

User Targets for Business Intelligence by Vertical Industries

Our 2016 sample shows differences among vertical industries targeting users for

business intelligence (fig. 16). Respondents in retail place the highest emphasis on

executives and middle managers, paying less attention to rank-and-file managers and

individual contributors and more-than-average attention to suppliers. Respondents in

food and beverage, advertising, financial services, and insurance have the highest

targeting of individual contributors. Business services, financial services, insurance, and

food and beverage are more likely to emphasize customer enablement of BI (likely for

services and applications addressing portfolio analysis, claims, and records). Suppliers

are broadly underrepresented in every industry, even manufacturing.

Figure 16 - Targeted business intelligence users by vertical industry

0%

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50%

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70%

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Targeted Users for Business Intelligence by Vertical Industry

Executives Middle managersLine managers Individual contributors & professionalsCustomers Suppliers

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33

Objectives for Business Intelligence

In 2016, the anecdotal and arguably philosophical goal of “making better decisions”

again topped the list of business intelligence objectives (fig. 17). We have traditionally

associated this goal with organizations seeking general improvements through the use

of business intelligence wherever they are available. In perhaps another reflection of the

2016 emphasis on operations, improved operational efficiency was the second choice,

followed by revenue growth, increased competitive advantage, and enhanced customer

service. Just 7 percent or fewer respondents consider any of the offered BI objectives

"unimportant."

Figure 17 - Business intelligence objectives

0% 20% 40% 60% 80% 100%

Better decision-making

Improved operational efficiency

Growth in revenues

Increased competitive advantage

Enhanced customer service

Business Intelligence Objectives

Critical Very important Important Somewhat important Unimportant

Better decision making

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34

Business Intelligence Objectives by Geography

“Better decision making” is the mantra for BI objectives across all geographical regions

in 2016 and to a slightly greater extent in North America and Latin America (fig. 18).

North American respondents also have the highest goals for improved operational

efficiency, (the second most important objective in all regions except Asia Pacific where

increased competitive advantage is slightly more important). Enhanced customer

service is the trailing objective in all regions.

Figure 18 - Business intelligence objectives by geography

1

1.5

2

2.5

3

3.5

4

4.5

5

North America Asia Pacific Latin America Europe, Middle Eastand Africa

Business Intelligence Objectives by Geography

Better decision making Improved operational efficiency

Growth in revenues Increased competitive advantage

Enhanced customer service

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35

Business Intelligence Objectives by Function

In 2015, emphasis toward business intelligence objectives varies by function (fig. 19).

Not surprisingly, the greatest emphasis on revenue growth through the use of BI is

highest among executives and is the clear standout objective for sales respondents.

Finance respondents have high interest in better decision making and improved

operational efficiency but below-average interest in revenues, competitive advantage,

and customer service. Respondents in the BICC have high interest in all objectives and

standout interest in the most neglected, in this case competitive advantage and

customer service; this perhaps hints at future areas of expansion and investment.

Interest in greater operational efficiency is a constant across all functions sampled.

Figure 19 - Business intelligence objectives by function

1

1.5

2

2.5

3

3.5

4

4.5

5

Better decision-making Improved operationalefficiency

Growth in revenues Increased competitiveadvantage

Enhanced customerservice

Business Intelligence Objectives by Function

Executive Management Marketing and Sales

Information Technology (IT) Finance

Business Intelligence Competency Center Mean

Better decision making

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36

Business Intelligence Objectives by Vertical Industry

Better decision making is the BI objective respondents most strongly identify with across

all industries in 2016, particularly insurance, healthcare, retail, and advertising (fig. 20).

Healthcare (followed by food and beverage and financial services) is the most

interested in improving operational efficiency. Retail and wholesale, with traditionally

thin margins, takes the highest interest in revenue growth. Competitive advertising and

churn-sensitive financial services organizations have the highest interest in increased

competitive advantage. Customer service is most emphasized by business services and

financial services.

Figure 20 - Business intelligence objectives by vertical industry

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Better decision-making Improved operationalefficiency

Growth in revenues Increased competitiveadvantage

Enhanced customerservice

Business Intelligence Objectives by Vertical Industry

Insurance Financial services

Healthcare Business services

Retail & wholesale Food, beverage and tobacco

Advertising Mean

Better decision making

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37

Business Intelligence Objectives by Organization Size

Organizations of different sizes all place the highest emphasis on better decision

making with similar mean importance of 4.2 to 4.4 (above "very important") (fig. 21).

Improved operational efficiency is the next most important to all organizations and

increases noticeably as organization headcount increases. Small organizations (1-100

employees) have a positive attitude toward multiple objectives and above-average

interest in (customer-oriented) increased revenues and competitive advantage. Very

large (> 10,000 employees) organizations place a similar above-average emphasis on

revenues and competitive advantage and the strongest emphasis on enhanced

customer services.

Figure 21 - Business intelligence objectives by organization size

1

1.5

2

2.5

3

3.5

4

4.5

5

1 - 100 101 - 1,000 1,001 - 10,000 More than 10,000

Business Intelligence Objectives by Organization Size

Improved operational efficiency Growth in revenues

Increased competitive advantage Better decision-making

Enhanced customer service

Better decision making

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38

Penetration of Business Intelligence Solutions

In a positive development, penetration of business intelligence (as a percentage of total

employees) appears to have grown noticeably between 2015 and 2016 (fig. 22).

Percentages of lower penetration (< 10 percent, 11-20 percent, 21-40, 41-60) all

declined while the highest levels (61- 80 percent, > 81 percent) improved by similar

amounts. The linear trending of this finding gives us some confidence that BI

enablement and democratization is showing improvement over time.

Figure 22 – Business intelligence penetration 2015 to 2016

0%

5%

10%

15%

20%

25%

30%

35%

40%

Under 10% 11 - 20% 21 - 40% 41 - 60% 61 - 80% 81% or more

Business Intelligence Penetration 2015 to 2016

2015

2016

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39

Expansion Plans for Business Intelligence Through 2018

Respondents very often describe bullish plans for expanding BI in future timeframes,

and we usually consider the 12-month period the most likely to be supportable and

budgeted (fig. 23). In this context, 20 percent of respondents (compared to 18 percent

current) expect greater than 81 percent of penetration in the coming year, and 8 percent

(versus 4 percent current) expect 61 percent to 80 percent penetration. This may be

achievable under current reported year-over-year growth. Longer timeframes predict

slightly greater, if not wild rates of growth in BI penetration and a stubborn small

minority (about 13 percent) with very low BI penetration of less than 10 percent.

Figure 23 - Expansion plans for business intelligence through 2019

0% 20% 40% 60% 80% 100%

In 36 months

In 24 months

In 12 months

Expansion Plans for Business Intelligence through 2019

81% or more 61 - 80% 41 - 60% 21 - 40% 11 - 20% Under 10%

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40

Current Business Intelligence Penetration by Geography

Globally, the highest levels of current BI penetration are reported in North America and

EMEA where solutions have generally been more available and widespread (fig. 24). In

contrast, the highest level of > 81 percent penetration is 10 percent in Latin America and

Asia Pacific (compared to 17 to18 percent in EMEA and North America). Latin America

and Asia Pacific also report significantly larger segments of low penetration (< 10

percent, 11-20 percent, 21-40, 41-60) than do respondents in North America and

EMEA.

Figure 24 - Business intelligence user penetration today by geography

0%

10%

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50%

60%

70%

80%

90%

100%

North America Europe, Middle Eastand Africa

Asia Pacific Latin America

Penetration of Business Intelligence Solutions Today by Geography

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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41

Planned Business Intelligence Penetration by Geography

A comparative view of future plans by geography supports the theme of somewhat

steady and growing expectations for expanding business intelligence in 12, 24 and 36-

month timeframes (fig. 25). Penetration of the highest rates (> 81 percent, 61-80

percent) are likewise highest in North America, followed by EMEA, Latin America, and

Asia Pacific. Thirty-six-month penetration of 40 percent or more is predicted to be

between 66 and 77 percent in all geographies.

Figure 25 - Planned business intelligence user penetration through 2019 by geography

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North America Asia Pacific Latin America Europe, Middle Eastand Africa

Expansion Plans for Business Intelligence through 2019 by Geography

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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42

Business Intelligence Penetration by Function

Executives report the most aggressive levels of BI penetration by function (fig. 26). At

the opposite end of this spectrum, finance is the most conservative when it comes to

adopting BI solutions. Somewhat surprisingly, sales and marketing ranks toward the

bottom of this order, behind IT and BICC, with only about 50 percent reporting 21

percent or more penetration.

Figure 26 – Business intelligence penetration today by function

0%

10%

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40%

50%

60%

70%

80%

90%

100%

ExecutiveManagement

InformationTechnology (IT)

BusinessIntelligenceCompetency

Center

Marketing andSales

Finance

Penetration of Business Intelligence Solutions Today by Function

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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43

All functions expect to increase BI penetration over time (fig. 27). Executives report the

most aggressive plans for coming timeframes, though the highest level of penetration

(81 percent or greater) will grow only 2 to 3 percent per year. Growth expectations for

very high penetration are similar for other functions, which place higher expectations for

improvement on middle ranked or modestly penetrated audiences.

Figure 27 – Expansion plans for business intelligence through 2019 by function

0%

10%

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ExecutiveManagement

Marketing andSales

InformationTechnology (IT)

Finance BusinessIntelligenceCompetency

Center

Expansion Plans for Business Intelligence through 2019 by Function

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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44

Current Business Intelligence Penetration by Vertical Industry

Higher levels of BI penetration vary inconsistently across different vertical industries

(ranked by descending mean value in fig. 28). In our 2016 sample, business services

reports the highest levels of 81 percent or greater penetration while midlevel BI

penetration is higher in financial services. Low levels of penetration may be more

informative, as in the case of healthcare, education, and manufacturing where 30

percent or fewer organizations report BI penetration greater than 20 percent.

Figure 28 – Penetration of business intelligence solutions today by selected vertical industry

0%

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100%

Penetration of Business Intelligence Solutions Today by Selected Vertical Industry

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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45

Planned Business Intelligence Penetration by Vertical Industry

In our 2016 sample, financial services and business services are the industries

expecting the highest BI expansion plans in future timeframes (fig. 29). Healthcare

education and manufacturing are progressively less aggressive in 12, 24 and 36-month

timeframes. In manufacturing and education for example, fewer than 40 percent of

organizations expect greater than 20 percent penetration 12 months from now.

Figure 29 - Expansion plans for business intelligence through 2019 by industry

0%

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Healthcare Financialservices

Businessservices

Education(Higher Ed)

Manufacturing

Expansion Plans for Business Intelligence through 2019 by Industry

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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46

Current Business Intelligence Penetration by Organization Size

As we have reported in every year of our study, small organizations of one to 100

employees have significantly higher BI penetration than larger peers (fig. 30). In the

modern context, we might expect small organizations, likely to be newer and comprised

of more information workers, would find fewer barriers of cost or deployment and more

immediate benefits than larger and older companies. As we have also seen in earlier

studies, very high penetration rates tend to decrease with organization size, though

headcount would offset this difference.

Figure 30 - Penetration of business intelligence solutions today by organization size

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 - 100 101 - 1,000 1,001 - 10,000 More than 10,000

Penetration of Business Intelligence Solutions Today by Organization Size

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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47

Planned Business Intelligence Penetration by Organization Size

Along with being the most mature BI users today, small organizations (1-100) have the

steepest expectations for high future penetration of business intelligence in coming

timeframes (fig. 31). Midsized organizations (101-1,000 employees) expect the next-

highest number of highly penetrated (> 60 percent) user audiences. Large and very

large (> 10,000 employees) organizations have somewhat lower expectations (which

may be colored by overall rank and file headcount not considered audiences for

business intelligence).

Figure 31 - Expansion plans for business intelligence through 2019 by organization size

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1 - 100 101 - 1,000 1,001 - 10,000 More than 10,000

Expansion Plans for Business Intelligence through 2019 by Organization Size

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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48

Chief Data and Chief Analytics Officers

For the first time, in 2016 we asked our audience whether their organization had

appointed a chief data officer (CDO) or chief analytics officer (CAO). We understand

that these appointments can represent significant evolutionary updates in the

technology and business architecture of organizations and also that these roles and

titles are relatively new, fluid by definition and evolving.

Enterprises with Chief Data or Chief Analytics Officers

The ongoing uptake and maturity of chief data and chief analytics officers is modest to

date, with fewer than 15 percent of respondent organizations having adopted the title(s)

(figs. 32, 33). Among those with one (or both) titles in the organization, maturity ranges

fairly evenly between spans of less than one year to more than five years. We note that

both titles have similar adoption and acceptance in organizations to date.

Figures 32; 33 - Enterprises with chief data or chief analytics officers

86.3%

3.6%

3.9% 2.0%

4.3%

Enterprises with a Chief Data Officer

Not applicable For less than 1 year

1 -3 years 3 - 5 years

More than 5 years

86.5%

3.4%

3.6% 2.8% 3.6%

Enterprises with a Chief Analytics Officer

Not applicable For less than 1 year

1 -3 years 3 - 5 years

More than 5 years

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49

Enterprises with Chief Data or Chief Analytics Officers by Geography

The title of chief data officer has the greatest overall penetration and the most new

activity in EMEA, followed by Asia Pacific (fig. 34). This finding might be surprising on

the surface, though the (albeit minority) CDO audience does have the greatest long-

term standing in North America. The title of chief analytics officer has the greatest

overall penetration in Asia Pacific and the largest number of new appointments of one-

year or less. EMEA has similar adoption rates for both CDOs and CAOs, while North

America is somewhat more likely to adopt the CDO versus the CAO. Latin American

respondents have comparatively small adoption of either title.

Figure 34 - Enterprises with chief data or chief analytics officers by geography

0%

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4%

6%

8%

10%

12%

14%

16%

18%

20%

NorthAmerica

AsiaPacific

LatinAmerica

Europe,Middle

East andAfrica

NorthAmerica

AsiaPacific

LatinAmerica

Europe,Middle

East andAfrica

Chief Data Officer Chief Analytics Officer

Enterprises with Chief Data or Chief Analytics Officers by Geography

More than 5 years

3 - 5 years

1 -3 years

For less than 1 year

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50

Enterprises with Chief Data or Chief Analytics Officers by Industry

The financial services industry plainly leads appointment rates for chief data officers at a

rate approaching twice the overall average (fig. 35). This statistical finding resonates

with anecdotal evidence in studies and presentations in the public domain so far. Most

new activity occurs in insurance, business services, and technology. Conversely, the

healthcare industry trails the vertical audience for CDOs, which may reflect the historical

state of information fragmentation in healthcare (at the same time it presents a glaring

business case). Longstanding appointments of chief analytics officers are predictably

highest in the insurance industry, though most new CAO appointments appear in

business services.

Figure 35 - Enterprises with chief data or chief analytics officers by industry

0%

5%

10%

15%

20%

25%

30%

Tech

nolo

gy

Hea

lth

care

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Chief Data Officer Chief Analytics Officer

Enterprises with Chief Data or Chief Analytics Officers by Industry

More than 5 years

3 - 5 years

1 -3 years

For less than 1 year

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51

Enterprises with Chief Data or Chief Analytics Officers by Organization Size

Appointments of chief data officers and chief analytics officers are, not surprisingly, a

mostly large-organization phenomenon (fig. 36). Small organizations of one to 100

employees, including startups, might selectively need the CDO title, though we expect

this might be inclusive of other duties and not a dedicated position (again depending on

definition). Chief analytics officer appears a more appropriate title at small organizations

more likely to focus on core processes, though new activity is strongest for both titles at

small organizations. Midsized organizations of 101 to 1,000 employees are less active

than smaller and larger peers.

Figure 36 - Enterprises with chief data or chief analytics officers by organization size

0%

5%

10%

15%

20%

25%

30%

1 - 100 101 -1,000

1,001 -10,000

Morethan

10,000

1 - 100 101 -1,000

1,001 -10,000

Morethan

10,000

Chief Data Officer Chief Analytics Officer

Enterprises with Chief Data or Chief Analytics Officers by Organization Size

More than 5 years

3 - 5 years

1 -3 years

For less than 1 year

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52

Enterprises with Chief Data and Chief Analytics Officers Reporting Structure

Among organizations with a CDO or CAO, both titles are most likely to report in to the

CEO (fig. 37). In the case of the CAO, this is especially the case—an indication of the

true or perceived business strategy implications of analytical expertise versus the

traditional wrangling of data. In this regard, CAOs are more likely to report to finance

than to IT, while CDOs have a pronounced IT reporting flavor.

Figure 37 - Chief data and chief analytics officer reporting structure

0%

5%

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15%

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25%

30%

35%

Chief Data Officer Chief Analytics Officer

Chief Data and Chief Analytics Officers Reporting Structure

CEO CFO CMO CIO Other

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53

Chief Data Officer and Success with BI by Reporting Structure

Organizations with a chief data officer that are also successful with business intelligence

are most likely by far to report into the CEO or CIO, followed by finance (fig. 38).

Organizations with a CDO that are unsuccessful with BI are most likely to report to IT or

the chief marketing officer. By this measure, we might suggest that CDOs at most

successful BI organizations are broadly connected to high-level business resources

(senior executives, successful IT departments, and finance), and not dedicated to siloed

programs or campaigns.

Figure 38 - Chief data officer and success with BI by reporting structure

0%

5%

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35%

Successful with BI Unsuccessful with BI

Chief Data Officer and Success with BI by Reporting Structure

CEO

CFO

CMO

CIO

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54

Chief Analytics Officer and Success with BI by Reporting Structure

Like CDOs, chief analytics officers at organizations that are successful with business

intelligence are most likely to report into the CEO (fig. 39). Notably, businesses and

institutions with a chief analytics officer that reports to IT are considerably more likely to

be organizations that perform poorly at business intelligence. Chief analytic officers in

successful BI organizations that report to marketing are more likely to experience

success than their CDO peers.

Figure 39 - Chief analytics officer and success with BI by reporting structure

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Successful with BI Unsuccessful with BI

Chief Analytics Officer and Success with BI by Reporting Structure

CEO

CFO

CMO

CIO

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Number of Business Intelligence Tools in Use

Number of Business Intelligence Tools in Use 2014 to 2016

Over time, we see some shifting in the number of business intelligence tools in use by

organizations accompanied by somewhat improved awareness (fewer "don't know") in

the organizational BI environment (fig. 40). It remains most likely (even more so in

2016) that organizations will continue to employ one, two, or three BI tools. The number

of organizations using four, five, or more tools has flattened by comparison, though we

would not yet suggest an obvious consolidation of tool use.

Figure 40 - Number of business intelligence tools in use 2014 to 2016

0%

5%

10%

15%

20%

25%

30%

Don't know 1 2 3 4 5 More than 5

Numbers of Business Intelligence Tools in Use 2014 to 2016

2014

2015

2016

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Number of Business Intelligence Tools by Geography

North America and EMEA organizations are more likely than respondents in other

geographies to use multiple business intelligence tools (fig. 41). While geographical

differences remain, they are less distinctive than in earlier studies. Asia-Pacific

respondents now have high tool usage compared to other geographies, and a majority

of Latin American respondents report using more than one BI tool.

Figure 41 - Numbers of business intelligence tools in use by geography

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Latin America

Asia Pacific

Europe, Middle East and Africa

North America

Number of Business Intelligence Tools in Use by Geography

One Two Three to six Seven or more Don't know

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Number of Business Intelligence Tools by Function

Executive management is most likely to report one or two business intelligence tools in

use and the most BI tool awareness (fig. 42). Marketing and sales is 80 percent likely to

report one, two, or three to six tools in use. BICCs, IT, and even finance departments

(perhaps in budgetary oversight) are likely to report high tool proliferation.

Figure 42 - Numbers of business intelligence tools in use by function

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Information Technology (IT)

Finance

Executive Management

Research and Development (R&D)

Business Intelligence Competency Center

Marketing and Sales

Number of Business Intelligence Tools in Use by Function

One Two Three to six Seven or more Don't know

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Number of Business Intelligence Tools by Vertical Industry

By function, manufacturing reports the lowest average number of business intelligence

tools in use, likely tied to existing material resource planning and asset management

investments (fig. 43). Business services is even more conservative in tool use, which

may reflect sample organization size. Healthcare, with multiple fragmented systems and

financial services report the highest number of business tools in use.

Figure 43 - Numbers of business intelligence tools in use by vertical industry

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Healthcare

Financial services

Education (Higher Ed)

Business services

Manufacturing

Number of Business Intelligence Tools in Use by Vertical Industry

One Two Three to six Seven or more Don't know

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Number of Business Intelligence Tools by Organization Size

Organization size historically and currently correlates to the number of business

intelligence tools in use (fig. 44). Organizations of 100 or fewer employees (closely

followed by midsized organizations of 101 - 1,000 employees) are most likely to report

one or two BI tools in use. Just 9 percent of very large (>10,000 employees)

organizations have one business intelligence tool in use and another 17 percent use

only two tools. Awareness to the number of tools in use decreases predictably as

organization size increases.

Figure 44 - Numbers of business intelligence tools in use by organization size

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

More than 10,000

1,001 - 10,000

101 - 1,000

1 - 100

Number of Business Intelligence Tools in Use by Organization Size

One Two Three to six Seven or more Don't know

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Technologies and Initiatives Strategic to Business Intelligence

Fundamental business intelligence technologies—reporting, dashboards, end-user self-

service, and advanced visualization—top our 2016 list of technologies and initiatives

among 30 topics currently under study (fig. 45). Enterprise data warehousing fell from

the top five to sixth place behind data discovery. Second-tier initiatives include data

mining, enterprise planning, mobile BI, and embedded BI. Compared to longstanding BI

assets, some “hot button” topics including cognitive BI, social media analytics, and the

Internet of Things still remain fringe priorities among respondents.

Figure 45 - Technologies and initiatives strategic to business intelligence

0% 20% 40% 60% 80% 100%

Reporting

Dashboards

End-user "self-service"

Advanced visualization

Data discovery

Data warehousing

Data mining, advanced algorithms, predictive

Integration with operational processes

Data storytelling

Enterprise planning/budgeting

Mobile device support

Embedded BI (contained within an application,…

Governance

Collaborative support for group-based analysis

End-user data preparation and blending

Search-based interface

Software-as-a-service and cloud computing

In-memory analysis

Ability to write to transactional applications

Location intelligence/analytics

Big Data (e.g., Hadoop)

Pre-packaged vertical/functional analytical…

Text analytics

Streaming data analysis

Open source software

Social media analysis (SocialBI)

Cognitive BI (e.g., Artificial Intelligence-based BI)

Complex event processing (CEP)

Internet of things (IoT)

Edge computing

Technologies and Initiatives Strategic to Business Intelligence

Critical

Very important

Important

Somewhatimportant

Not important

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Technology Priority Changes from 2013

Technology priority rankings have remained fairly consistent since 2013 (fig. 46).

Reporting debuted atop priorities; dashboards and advanced visualization gained some

momentum as data warehousing declined slightly as previously noted. Enterprise

planning and embedded BI declined as did lower priorities of location intelligence, pre-

packaged applications, and the Internet of Things. If the past is precedent, these

declines and lower priorities may come to rebound in future studies as more use cases

and maturity arrive.

Figure 46 - Technology priorities 2014 to 2016

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Technology Priorities 2014 to 2016

2014 2015 2016

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Another instructive view of year-over-year changes in business intelligence priorities is

shown in figure 47. In this view, ability to write to transactional applications grew most

by percentage, while cognitive BI and data discovery made leapfrog improvements.

Open source software and search-based interface gains are also worth noting.

Sentiment declined most notably toward location intelligence and prepackaged

analytical applications (for a second consecutive year), followed by operational

integration. As noted, data warehousing and IoT declined, while SaaS/cloud flattened

and reversed losses in prior years. Momentum adds color to our overall rankings, but

short-term swings in sentiment may or may not confirm trends.

Figure 47 - Technology priority changes 2015 to 2016

-11% -6% -1% 4% 9%

Location intelligence/analytics

Pre-packaged analytical applications

Integration with operational processes

Internet of Things

In-memory analysis

"Embedded" BI

Data warehousing

Complex event processing (CEP)

Mobile device support

End-user data preparation and blending

Enterprise planning

Data mining, advanced algorithms, predictive

Social media analysis (Social BI)

End-user "self-service"

Software-as-a-service and cloud computing

Text analytics

Big data (e.g., Hadoop)

Dashboards

Advanced visualization

Collaborative support for group-based analysis

Search-based interface

Open source software

Data discovery

Cognitive BI

Ability to write to transactional applications

Technology Priority Changes 2015 to 2016

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Technologies and Initiatives Strategic to Business Intelligence by Geography

By region, North America has the greatest interest in reporting, dashboards, end-user

self-service, data discovery, data storytelling, and software as a service/cloud (fig. 48).

Asia Pacific shares equal or high interest in these same areas and leads current

demand for data warehousing, integration with operational systems, governance,

collaborative support, in-memory, and several lesser categories. Latin American

respondents have comparatively high interest in mobile device support, governance,

end-user data preparation, and search-based interest. EMEA respondents do not lead

any categories and generally report average or less interest in specific objectives.

Figure 48 - Technologies and initiatives strategic to business intelligence objectives by geography

2

2.5

3

3.5

4

4.5Reporting

DashboardsEnd-user "self-service"

Advanced visualization

Data discovery

Data warehousing

Data mining, advanced…

Integration with operational…

Data storytelling

Enterprise planning/budgeting

Mobile device support

Embedded BI (contained within…

Governance

Collaborative support for group-…End-user data preparation and…

Search-based interfaceSoftware-as-a-service and cloud…

In-memory analysis

Ability to write to transactional…

Location intelligence/analytics

Big Data (e.g., Hadoop)

Pre-packaged…

Text analytics

Streaming data analysis

Open source software

Social media analysis (SocialBI)

Cognitive BI (e.g., Artificial…

Complex event processing (CEP)

Internet of things (IoT)Edge computing

Technologies and Initiatives Strategic to Business Intelligence Objectives by Geography

North America Asia Pacific Latin America Europe, Middle East and Africa

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Technologies and Initiatives Strategic to Business Intelligence by Function

Functional attitudes toward BI technologies and initiatives generally relate to specific

daily roles and responsibilities (fig. 49). The BICC, responsible for support services

across BI objectives, leads prioritization of many or most categories. On-the-go

marketing/sales, followed by executive management users depend on dashboards.

Marketing and sales also shows high interest in data storytelling and search-based

interface while finance expectedly leads interest in enterprise planning initiatives.

Figure 49 - Technologies and initiatives strategic to business intelligence by function

1

1.5

2

2.5

3

3.5

4

4.5Reporting

DashboardsEnd-user "self-service"

Advanced visualization

Data discovery

Data warehousing

Data mining, advanced…

Integration with operational…

Data storytelling

Enterprise planning/budgeting

Mobile device support

Embedded BI (contained within…

Governance

Collaborative support for group-…End-user data preparation and…

Search-based interfaceSoftware-as-a-service and cloud…

In-memory analysis

Ability to write to transactional…

Location intelligence/analytics

Big Data (e.g., Hadoop)

Pre-packaged vertical/functional…

Text analytics

Streaming data analysis

Open source software

Social media analysis (SocialBI)

Cognitive BI (e.g., Artificial…

Complex event processing (CEP)

Internet of things (IoT)Edge computing

Technologies and Initiatives Strategic to Business Intelligence by Function

Executive Management Marketing and Sales

Information Technology (IT) Finance

Business Intelligence Competency Center

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Technologies and Initiatives Strategic to Business Intelligence by Vertical Industry

Vertical industries describe a range of interest in their different 2016 business

intelligence initiatives and priorities (fig. 50). Manufacturing and healthcare show the

most interest in reporting, while advertising and healthcare lead interest in dashboards.

Manufacturing also reports high interest in advanced visualization, integration with

operational systems, cloud, and location intelligence. Insurance predictably leads

interest in data warehousing and data mining, while advertising has relatively singular

interest in data storytelling. Financial services leads interest in mobile device support

and governance. Business services shows only average interest in most or all

initiatives, and higher education is least interested generally.

Figure 50 - Technologies and initiatives strategic to business intelligence by vertical industry

2.0

2.5

3.0

3.5

4.0

4.5Reporting

DashboardsEnd-user "self-service"

Advanced visualization

Data discovery

Data warehousing

Data mining, advanced…

Integration with operational…

Data storytelling

Enterprise planning/budgeting

Mobile device support

Embedded BI (contained within…

Governance

Collaborative support for group-…End-user data preparation and…

Search-based interfaceSoftware-as-a-service and cloud…

In-memory analysis

Ability to write to transactional…

Location intelligence/analytics

Big Data (e.g., Hadoop)

Pre-packaged vertical/functional…

Text analytics

Streaming data analysis

Open source software

Social media analysis (SocialBI)

Cognitive BI (e.g., Artificial…

Complex event processing (CEP)

Internet of things (IoT)Edge computing

Technologies and Initiatives Strategic to Business Intelligence by Vertical Industry

Financial services Advertising Manufacturing Business services

Insurance Healthcare Education (Higher Ed)

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Technologies and Initiatives Strategic to Business Intelligence by Organization Size

Business intelligence priorities vary by organization size, though generally, very large

organizations lead interest in most technologies and initiatives under study in 2016 (fig.

51). That said, at the top of the list, midsized organizations of 101 to 1,000 employees

actually lead demand for reporting, and small (1-100 employees) organizations slightly

lead demand for dashboards. We note that though these top two responses are tightly

grouped with comparatively high importance compared to all others. An exception to

large organization leadership is found in software as a service and cloud, where small

businesses lead adoption. At a lower level, small organizations are more likely to pursue

open source software and social BI.

Figure 51 - Technologies and initiatives strategic to business intelligence by organization size

1

1.5

2

2.5

3

3.5

4

4.5Reporting

DashboardsEnd-user "self-service"

Advanced visualization

Data discovery

Data warehousing

Data mining, advanced…

Integration with operational…

Data storytelling

Enterprise planning/budgeting

Mobile device support

Embedded BI (contained within…

Governance

Collaborative support for group-…End-user data preparation and…

Search-based interfaceSoftware-as-a-service and cloud…

In-memory analysis

Ability to write to transactional…

Location intelligence/analytics

Big Data (e.g., Hadoop)

Pre-packaged vertical/functional…

Text analytics

Streaming data analysis

Open source software

Social media analysis (SocialBI)

Cognitive BI (e.g., Artificial…

Complex event processing (CEP)

Internet of things (IoT)Edge computing

Technologies and Initiatives Strategic to Business Intelligence by Organization Size

1 - 100 101 - 1,000 1,001 - 10,000 More than 10,000

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Business Intelligence and the State of Data

Beginning in 2014, we polled respondents for attitudes and behaviors reflective of the

“state of data” in their organizations (fig. 52). As the choices describe, a good majority

(64 percent) of organizations say they either see data as “truth” or maintain a common

enterprise view of data limited by parochial views and semantics. Twenty-four percent

report consistent department-level data and 12 percent report the worst state of data,

multiple inconsistent data sources with conflicting semantics and data.

Figure 52 - Business intelligence and the state of data

26%

38%

24%

12%

0% 5% 10% 15% 20% 25% 30% 35% 40%

Data as "truth" - A common view of enterprise datais available with common application of data,

filters, rules, and semantics.

A common view of enterprise data is available.However, parochial views and semantics are used

to support specific positions

Consistent data is available at a departmental level.Conflicting, functional views of data causes

confusion and disagreement

We have multiple, inconsistent data sources withconflicting semantics and data. Information is

generally unreliable and distrusted

Business Intelligence and the State of Data

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In the last two years, respondents’ opinions of their “state of data” has shifted to a

slightly more skeptical point of view (fig. 53). While 2 percent more see the highest level

of data as “truth,” 4 percent fewer describe a common view of data and 2 percent more

respondents say consistent data is available at a department level. The percentage of

organizations with multiple inconsistent sources of data is unchanged.

Figure 53 - Business intelligence and the state of data 2015 to 2016

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Data as "truth" - Acommon view ofenterprise data is

available with commonapplication of data,

filters, rules, andsemantics.

A common view ofenterprise data is

available. However,parochial views and

semantics are used tosupport specific

positions

Consistent data isavailable at a

departmental level.Conflicting, functionalviews of data causes

confusion anddisagreement

We have multiple,inconsistent data

sources with conflictingsemantics and data.

Information is generallyunreliable and distrusted

Business Intelligence and The State of Data 2015 to 2016

2015

2016

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Business Intelligence and the State of Data by Geography

Estimations of organizational data maturity vary by regional geography (fig. 54). EMEA

is most comfortable with the quality and use of their data, followed by Asia Pacific and

North America, which reports the lowest self-estimation of "data as truth." Latin America

trails the state of data reported in other regions, though not significantly.

Figure 54 - Business intelligence and the state of data by geography

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Europe,Middle Eastand Africa

Asia Pacific North America Latin America

Business Intelligence and the State of Data by Geography

Data as "truth" - A common viewof enterprise data is available withcommon application of data,filters, rules, and semantics.

A common view of enterprise datais available. However, parochialviews and semantics are used tosupport specific positions

Consistent data is available at adepartmental level. Conflicting,functional views of data causesconfusion and disagreement

We have multiple, inconsistentdata sources with conflictingsemantics and data. Information isgenerally unreliable anddistrusted

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Business Intelligence and the State of Data by Function

Executive management is most likely to report the highest common view of data as

“truth” or a common view of enterprise data (fig. 55). The BICC, however, is most likely

to affirm the highest state of data achievement. Marketing and sales, often BI

frontrunners, are the next most-mature functions. IT and finance report higher levels of

department-level or inconsistent data.

Figure 55 - Business intelligence and the state of data by function

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

ExecutiveManagement

BusinessIntelligenceCompetency

Center

Marketingand Sales

InformationTechnology

(IT)

Finance

Business Intelligence and the State of Data by Function

Data as "truth" - A commonview of enterprise data isavailable with commonapplication of data, filters,rules, and semantics

A common view of enterprisedata is available. However,parochial views and semanticsare used to support specificpositions

Consistent data is available at adepartmental level. Conflicting,functional views of data causesconfusion and disagreement

We have multiple, inconsistentdata sources with conflictingsemantics and data.Information is generallyunreliable and distrusted

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Business Intelligence and the State of Data by Vertical Industry

By industry, 70 percent of insurance respondents are most likely to report the two

highest levels of their organizations' state of data (fig. 56). Business services, higher

education, and healthcare are next most likely to predict high states of data, followed by

financial services and manufacturing.

Figure 56 - Business intelligence and the state of data by selected vertical industry

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Business Intelligence and the State of Data by Selected Vertical Industry

Data as "truth" - A common viewof enterprise data is available withcommon application of data,filters, rules, and semantics

A common view of enterprise datais available. However, parochialviews and semantics are used tosupport specific positions

Consistent data is available at adepartmental level. Conflicting,functional views of data causesconfusion and disagreement

We have multiple, inconsistentdata sources with conflictingsemantics and data. Information isgenerally unreliable anddistrusted

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Business Intelligence and the State of Data by Organization Size

Smaller organizations that, on average, manage a smaller scope of data than larger

peers are most likely to “have their act together” with a more mature state of data than

larger peers (fig. 57). Moving left to right, we see the state of data tends to become less

coordinated and more fragmented as organization headcount increases. Less than 17

percent of organizations of any size report the lowest state on multiple, inconsistent

data sources.

Figure 57 - Business intelligence and the state of data by organization size

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 - 100 101 - 1,000 1,001 - 10,000 More than10,000

Business Intelligence and the State of Data by Organization Size

Data as "truth" - A common viewof enterprise data is available withcommon application of data,filters, rules, and semantics

A common view of enterprisedata is available. However,parochial views and semantics areused to support specific positions

Consistent data is available at adepartmental level. Conflicting,functional views of data causesconfusion and disagreement

We have multiple, inconsistentdata sources with conflictingsemantics and data. Informationis generally unreliable anddistrusted

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Business Intelligence and Action on Insight

In 2014, we introduced “action on insight,” a high-level self-assessment of best (and

worst) practices in organizational use of data. In 2016, respondents paint a very positive

picture of their data usage (fig. 58). Eighty-three percent of respondents say they have

either "closed loop" or ad hoc action on insights, meaning that they actively share BI-

derived insights with colleagues. Just 12 percent report uncoordinated or parochial

action and only 5 percent say insights are rarely leveraged.

Figure 58 - Business intelligence and action on insight

28%

55%

12%

5%

0%

10%

20%

30%

40%

50%

60%

"Closed loop" -Information is shared,teams work to process

and act in a timelyfashion. No formal

boundaries

Ad hoc (informal) actionon insights across

functions

Uncoordinated/parochial action

(sometimes at theexpense of others)

Insights are rarelyleveraged

Business Intelligence and Action on Insight

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Across three years of data, we have seen a slightly negative trend in estimations of

organizational ability to take action on insight (fig. 59). While we see a 2 percent year-

over-year improvement in "closed loop" success, somewhat more negative views have

increased slightly. With that said, a very small minority of 5 percent of respondents are

fully doubtful of their organizational ability to take action on insight.

Figure 59 – Business intelligence and action on insight 2014 to 2016

24%

62%

10%

4%

26%

60%

11%

4%

28%

55%

12%

5%

0%

10%

20%

30%

40%

50%

60%

70%

“Closed-loop processes for action” - Information is shared,

teams work to process and act in a timely fashion. No formal boundaries

Ad hoc (informal)action on insightsacross functions

Uncoordinated/parochial action

(sometimes at theexpense of others)

Insights are rarelyleveraged

Business Intelligence and Action on Insight 2014 to 2016

2014

2015

2016

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Business Intelligence and Action on Insight by Geography

Organizational estimations of the ability to take action on insight run strongest in Asia

Pacific, followed by EMEA (fig. 60). This geographical finding jibes with our 2016 state

of data also (fig. 54, p. 70). North America respondents are slightly less confident and

Latin America respondents trails in perceived ability to execute with data insights.

Figure 60 - Business intelligence and action on insight by geography

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Asia Pacific Europe,Middle Eastand Africa

North America Latin America

Business Intelligence and Action on Insight by Geography

"Closed loop" - Information isshared, teams work to processand act in a timely fashion. Noformal boundaries

Ad hoc (informal) action oninsights across functions

Uncoordinated/ parochial action(sometimes at the expense ofothers)

Insights are rarely leveraged

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Business Intelligence and Action on Insight by Function

BICC respondents, with the broadest account of business intelligence users, are most

likely to claim ability to take action on insight, particularly at the highest level of closed-

loop processes (fig. 61). "On-the-go" users in sales/marketing and executive ranks are

the next most likely to say they are adept at taking action on data insights. Of the

functions studied, IT and finance are least likely to coordinate action on insight in 2016.

Figure 61 - Business intelligence and action on insight by function

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

BusinessIntelligenceCompetency

Center

Marketingand Sales

ExecutiveManagement

Finance InformationTechnology

(IT)

Business Intelligence and Action on Insight by Function

"Closed loop" - Information isshared, teams work to processand act in a timely fashion. Noformal boundaries

Ad hoc (informal) action oninsights across functions

Uncoordinated/ parochialaction (sometimes at theexpense of others)

Insights are rarely leveraged

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Business Intelligence and Action on Insight by Vertical Industry

Industries generally exhibit high confidence in their ability to take action on insight (fig.

62). In our 2016 sample, respondents in financial services, insurance, and business

services are the most confident in their ability to act on data. Manufacturing and higher

education trail in this ranking and are most likely to report uncoordinated or unleveraged

insights.

Figure 62 - Business Intelligence and action on insight by vertical industry

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Business Intelligence and Action on Insight by Vertical Industry

"Closed loop" - Information isshared, teams work to processand act in a timely fashion. Noformal boundaries

Ad hoc (informal) action oninsights across functions

Uncoordinated/ parochial action(sometimes at the expense ofothers)

Insights are rarely leveraged

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Business Intelligence and Action on Insight by Organization Size

Though small (1-100 employees) and very large (>10,000 employees) organizations

fare best, organization size does not bear greatly on the ability to take action on insights

(fig. 63). Close to or well more than 80 percent of organizations claim "closed loop" or

ad hoc abilities; 6 percent or fewer organizations of any size say insights are rarely

leveraged.

Figure 63 - Business intelligence and action on insight by organization size

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 - 100 101 - 1,000 1,001 - 10,000 More than10,000

Business Intelligence and Action on Insight by Organization Size

"Closed loop" - Information isshared, teams work to processand act in a timely fashion. Noformal boundaries

Ad hoc (informal) action oninsights across functions

Uncoordinated/ parochial action(sometimes at the expense ofothers)

Insights are rarely leveraged

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Success with Business Intelligence

In 2016, our core measure of success with business intelligence showed a small net

gain but no dramatic movement (fig. 64). The number of respondents that say their

organizations are “successful” with Bl increased 3 percent, rebounding from a trough in

2015. This success was offset by 3 percent fewer who responded "somewhat

successful" in our poll. Respondents reporting "somewhat unsuccessful" and

"unsuccessful" are essentially flat year over year.

Figure 64 - Success with business intelligence 2013 to 2016

41%

48%

8%

3%

41%

49%

8%

2%

35%

53%

10%

2%

38%

50%

9%

3%

0%

10%

20%

30%

40%

50%

60%

Successful Somewhat successful Somewhat unsuccessful Unsuccessful

Success with Business Intelligence 2013 to 2016

2013 2014 2015 2016

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Reasons Why Business Intelligence Succeeds

Tag cloud analysis of BI success flows through classic expectations of “business,”

“data,” "information," and “customers” (fig. 65). "Analytics" and "tools" found growing

importance as emphasis on particular roles softened. Positive expectations ("more,"

"good," "successful") reflect the general tone in 2016.

Primary reasons for success with BI carried over from 2015 and include senior

management view BI as strategic, a stable organization, focus on critical opportunities

and the requisite skills to deliver solutions.

Figure 65 - Reasons for success with business intelligence

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Reasons Why Business Intelligence Fails

Asked for reasons why business intelligence fails, respondents point to "data" as a

moving target of quality, integration, security, etc. and their "lack" of ability to access,

manipulate, and use data (fig. 66). They see shortfalls of "resources" and "analytics"

and are not convinced that "management" has grasped issues surrounding "support,"

"training," "adoption," and "use."

Primary reasons for failure carry over from 2015 and include cumbersome processes,

too much focus upon technology versus solving business problems and a lack of skills

and resources to deliver solutions.

Figure 66 - Reasons why business intelligence fails

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Success with Business Intelligence by Organization Size

The smallest organizations are most likely (47 percent) to consider themselves

“completely successful,” and more than 90 percent say they are at least “somewhat

successful” with business intelligence (fig. 67). In larger organizations, between 30

percent and 36 percent are likely to claim complete success. As we see elsewhere in

our survey data, reports of success tend to decline with organizational size until they

rebound slightly with the very largest. Nonetheless, organizations of more than 100

employees are between 84 percent and 87 percent likely to say they are, at minimum,

“somewhat successful” with BI.

Figure 67 - Success with business intelligence by organization size

1

1.5

2

2.5

3

3.5

4

4.5

5

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Success with Business Intelligence by Organization Size

Completely agree

Agree somewhat

Disagree somewhat

Disagree

Mean

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Success with Business Intelligence by BI Objectives

Organizations that are successful with business intelligence focus on the full range of

objectives we sampled in 2016 (fig. 68). The most popular objective of successful BI

organizations is “better decision making” followed in somewhat equal measure by

improved operational efficiency, revenue growth, and increased competitive advantage.

Organizations that consider themselves unsuccessful are less emphatic in all areas,

likely to focus most on better decision making, operational improvements, and

customers, and pay less attention to revenue growth or competitive advantage.

Figure 68 - Success with business intelligence by BI objectives

1

1.5

2

2.5

3

3.5

4

4.5

5

Better decision making Improved operationalefficiency

Growth in revenues Increased competitiveadvantage

Enhanced customerservice

Success with Business Intelligence by BI Objectives

Successful Somewhat successful Somewhat unsuccessful

Unsuccessful Mean

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Success with Business Intelligence by Targeted Users

Executives top the target priorities at organizations that are successful, somewhat

successful, and somewhat unsuccessful at business intelligence (fig. 69). In contrast,

the least successful organizations deemphasize all target groups but do not place

disproportionate emphasis on executive audiences. Unsuccessful organizations place

much less emphasis on customers and disproportionately high emphasis on individual

contributors. Unsuccessful organizations may thus be more ad hoc in nature and

uncoordinated structurally.

Figure 69 - Success with business intelligence by targeted users

0%

10%

20%

30%

40%

50%

60%

70%

80%

Successful Somewhat successful Somewhatunsuccessful

Unsuccessful

Success With Business Intelligence by Targeted Users

Executives Middle managers

Line managers Individual contributors & professionals

Customers Suppliers

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Success with Business Intelligence and Technology Priorities

Organizations that are successful with business intelligence broadly pay much more

attention to BI-related technology priorities than all other groups (fig. 70). Unsuccessful

organizations place much less emphasis on dashboards than more successful

businesses and have the highest interest in (albeit lower priority) prepackaged

vertical/functional analytical applications. In general, beyond reporting and dashboards,

less successful BI organizations appear hesitant toward BI technologies and priorities.

Figure 70 - Technologies and initiatives strategic to business intelligence by BI success

2

2.5

3

3.5

4

4.5Reporting

DashboardsEnd-user "self-service"

Advanced visualization

Data discovery

Data warehousing

Data mining, advanced algorithms,…

Integration with operational processes

Data storytelling

Enterprise planning/budgeting

Mobile device support

Embedded BI (contained within an…

Governance

Collaborative support for group-based…End-user data preparation and blending

Search-based interfaceSoftware-as-a-service and cloud…

In-memory analysis

Ability to write to transactional…

Location intelligence/analytics

Big Data (e.g., Hadoop)

Pre-packaged vertical/functional…

Text analytics

Streaming data analysis

Open source software

Social media analysis (SocialBI)

Cognitive BI (e.g., Artificial…

Complex event processing (CEP)

Internet of things (IoT)Edge computing

Technologies and Initiatives Strategic to Business Intelligence by BI Success

Successful Somewhat successful Somewhat unsuccessful Unsuccessful

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Success with Business Intelligence and Number of BI Tools

Historically, we have found that organizations that are successful with business

intelligence generally have fewer tools in use based on strategic intent and engaged

leadership. Awareness of the number of tools in use also increases with the degree of

BI success (fig. 71). It can be argued, however, that BI tools can proliferate or be

restrained independent of BI success.

Figure 71 – Numbers of business intelligence tools in use by BI success

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Successful Somewhat successful Somewhat unsuccessful Unsuccessful

Number of Business Intelligence Tools in Use by BI Success

One Two Three to six Seven or more Don't know

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Success with Business Intelligence and the State of Data

Success with business intelligence relates powerfully and directly to an organization’s

state of data (fig. 72). Organizations that view data as “truth” or with a common view of

enterprise data are 80 percent likely to be successful, compared to 39 percent for

somewhat unsuccessful and just 15 percent of unsuccessful organizations (none of

which report complete success).

Figure 72 – Business intelligence and the state of data by BI success

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Successful Somewhatsuccessful

Somewhatunsuccessful

Unsuccessful

Business Intelligence and the State of Data by BI Success

Data as "truth" - A common viewof enterprise data is available withcommon application of data,filters, rules, and semantics

A common view of enterprise datais available. However, parochialviews and semantics are used tosupport specific positions

Consistent data is available at adepartmental level. Conflicting,functional views of data causesconfusion and disagreement

We have multiple, inconsistentdata sources with conflictingsemantics and data. Information isgenerally unreliable anddistrusted

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Success with Business Intelligence and Action on Insight

Success with business intelligence correlates perhaps even more strongly with an

organization’s ability to take action on insights (fig. 73). At the high end of performance,

organizations with closed-loop processes are completely successful 47 percent of the

time and at least somewhat successful 93 percent of the time. Organizations with ad

hoc or informal action on insights are well less than half as likely to report complete

success. Organizations with the two lowest levels of coordination are much more likely

to fail than to succeed. No unsuccessful organizations in our 2016 sample say they are

able to leverage closed-loop processes.

Figure 73 – Business intelligence and action on insight by BI success

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Successful Somewhatsuccessful

Somewhatunsuccessful

Unsuccessful

Business Intelligence and Action on Insight by BI Success

"Closed loop" - Information isshared, teams work to processand act in a timely fashion. Noformal boundaries

Ad hoc (informal) action oninsights across functions

Uncoordinated/ parochial action(sometimes at the expense ofothers)

Insights are rarely leveraged

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Success with Business Intelligence and Penetration of Users

Organizations that are more successful with business intelligence have higher number

of users as a percentage of the workforce (fig. 74). Fifty-eight percent of organizations

with at least 21-40 percent BI penetration say they are successful. As BI success

decreases, so does penetration: among unsuccessful organizations, less than 20

percent have the same (21-40 percent) level of BI penetration. Seventy percent of

unsuccessful organizations have less than 10 percent BI penetration.

Figure 74 - Penetration of business intelligence solutions today by BI success

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Successful Somewhatsuccessful

Somewhatunsuccessful

Unsuccessful

Penetration of Business Intelligence Solutions Today by BI Success

81% or more

61 - 80%

41 - 60%

21 - 40%

11 - 20%

Under 10%

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Industry and

Vendor

Analysis

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Industry and Vendor Analysis In this section we review business intelligence vendor and market performance, using

our trademark 33-criteria evaluation model.

Scoring Criteria

The criteria for the various industry and vendor rankings are grouped into seven

categories including sales/acquisition experience, value for price paid, quality and

usefulness of product, quality of technical support, quality and value of consulting,

integrity, and whether the vendor is recommended.

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Industry Performance

Sales/Acquisition Experience

Across the last two years of our study, industry professionalism and product knowledge

have retained the highest and most consistent scores in our evaluation (fig. 75). During

the same period, scores for responsiveness, flexibility/accommodation, business

practices and follow-up after the sale have improved. From an industry perspective, it

suggests that sales groups have stepped up efforts to respond to customers and

support them beyond the close of the sale.

Figure 75 - Industry performance—sales/acquisition experience: 2011 to 2016

3.3

3.4

3.5

3.6

3.7

3.8

3.9

4

4.1

4.2

4.3

4.4

2011 2012 2013 2014 2015 2016

Industry Performance–Sales and Acquisition Experience: 2011 to 2016

Professionalism

Product knowledge

Understanding our business/needs

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and conditions

Follow up after the sale

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Value

End users generally believe they are getting high and improving value from industry

vendors over time (fig. 76). An ongoing rating higher than 4.0 extends a high and mildly

positive trend line. Though gradients are in a narrow range, the 2016 score of 4.11

nonetheless represents an all-time high for industry value performance. With the

exception of 2012, perceived value for price paid has remained above "very good."

Figure 76 - Industry performance—value: 2011 to 2015

3.8

3.85

3.9

3.95

4

4.05

4.1

4.15

2011 2012 2013 2014 2015 2016

Industry Performance–Value: 2011 to 2016

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Quality and Usefulness of Product

Industry product quality and usefulness has improved over time across almost all

dimensions (fig. 77). The most notable improvements are in areas reflecting ease of

use: ease of upgrade, ease of installation, and ease of administration. These

improvements correspond directly to areas where we have seen the industry invest to

improve customer and end-user autonomy through simplification. Most other

parameters, including the top priority of robustness, also held gains or improved.

Figure 77 - Industry performance—quality and usefulness of products: 2011 to 2016

3.3

3.4

3.5

3.6

3.7

3.8

3.9

4

4.1

4.2

Robustness/sophisticationof technology

Completeness offunctionality

Reliability of technology

Scalability

Integration of componentswithin product

Integration with third-party technologies

Overall usability

Ease of installation

Ease of administration

Customization andextensibility

Ease of upgrade/migrationto new versions

Online training, forumsand documentation

Industry Performance–Quality and Usefulness of Products: 2011 to 2016

2011 2012 2013 2014 2015 2016

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Technical Support

In 2016, the vendor industry performed well among user respondents in the area of

technical support (fig. 78). Product knowledge and responsiveness reached all-time

high levels. Time to resolve problems rebounded strongly from a 2015 decline to near

an all-time high. (We consider product knowledge, responsiveness, and time to resolve

problems as cornerstones of immediacy in support of urgent customer needs).

Continuity of personnel, often a challenge for vendors to sustain, held solid. In all, charts

76-78 are encouraging signs of vendor success that bode well for the industry's future.

Figure 78 - Industry performance—technical support: 2011 to 2016

3.5

3.6

3.7

3.8

3.9

4

4.1

4.2

4.3

2011 2012 2013 2014 2015 2016

Industry Performance–Technical Support: 2011 to 2016

Professionalism Product knowledge Responsiveness

Continuity of personnel Time to resolve problems

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Consulting

BI vendor consulting was also generally positive in 2016 (fig. 79). The only attribute that

suffered a decline was experience, which (like continuity of personnel), is a traditional

sore spot in user engagements. Project expansion and broad general demand often

become a cost of success that leads to employee poaching and/or hiring fewer

experienced or domain-familiar consulting personnel. Apart from this weakness, other

parameters, noticeably value, held steady or improved.

Figure 79 - Industry performance—BI vendor consulting: 2011 to 2016

3.6

3.7

3.8

3.9

4

4.1

4.2

4.3

2011 2012 2013 2014 2015 2016

Industry Performance–BI Vendor Consulting: 2011 to 2016

Professionalism Product knowledge Experience Continuity Value

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Integrity

Vendor integrity—measured as honesty and truthfulness in all dealings—has remained

mostly flat over the last three years with some slight positive trending (fig. 80). With

mean scores well above 4.0, indicating "very good" to "excellent," this parameter of

industry performance is secure as a core strength within the industry.

Figure 80 - Industry performance—integrity: 2012 to 2016

4.00

4.05

4.10

4.15

4.20

4.25

4.30

4.35

4.40

2012 2013 2014 2015 2016

Industry Performance–Integrity: 2012 to 2016

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Recommended

Industry performance in the area of customers willing to recommend rose slightly year

over year, though the six-year trend line is down, thanks to a very strong 2011

performance (fig. 81). As the scores for recommend have rebounded for three straight

years, they are also the highest mean scores of any in our survey, well above "very

likely" and approaching near certainty.

Figure 81 - Industry performance—recommended: 2011 to 2016

4

4.1

4.2

4.3

4.4

4.5

4.6

4.7

4.8

4.9

5

2011 2012 2013 2014 2015 2016

Industry Performance–Recommended: 2011 to 2016

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Performance Improvements

Another view of more recent year-over-year vendor performance shows a significant

improvement in 2016 (fig. 82). Compared to 2016, perceived overall industry

improvement jumped 6 percentage points from 39 percent to 45 percent. This suggests

that vendors are paying greater attention to their full range of services and products

(perhaps in conjunction with a better business climate and BI and information

management success rates overall). In either or both cases, customers are upgrading

their vendors' performance alongside their own abilities to manage data and leverage it.

Figure 82 - Overall industry performance improvement 2014 to 2016

39% 39% 45%

56% 57% 50%

4% 5% 5%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2014 2015 2016

Overall Industry Performance Improvement: 2014 to 2016

Improved Stayed the same Declined

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Vendor

Ratings

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Vendor Ratings In this section we offer ratings of business intelligence software vendors. We rated

vendors using 33 different criteria, on a five-point scale for each. Criteria covered sales

/acquisition experience (8 criteria), value for price paid (1), quality and usefulness of

product (12), quality of technical support (5), quality and value of consulting services (5),

whether the vendor is recommended (1), and integrity (1).

As we explore vendor performance in more detail, it is important to understand the scale

we used in scoring the industry and vendors:

5.0 = Excellent

4.0 = Very good

3.0 = Adequate

2.0 = Poor

1.0 = Very poor

For 2016 we dispensed with market segmentation and now rely upon our Customer

Experience and Vendor Credibility models, introduced last year, as a means of

presenting relative vendor ratings. As a result, we no longer include a peer average for

individual vendor rating charts. Instead, this has been replaced (where possible) with a

year-over-year comparison for each vendor.

Based on our scoring methodology, all vendors performed at a level that is considered

more than “adequate” for all criteria categories.

Please note that “average score” is the mathematical mean of all items included in

vendor ratings. Each column in the chart represents a scale consisting of varying

numbers of items (for example, "sales" is a scale consisting of eight items, while "value

for price paid” is one item). As such, each column is weighted differently (based upon

the number of items represented and the number of respondents rating those items) in

calculating the overall average rating. The average score cannot be calculated by

simply averaging across the subscale scores.

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Business Intelligence Market Models

Starting in 2015, we developed two new models for examining and understanding the

business intelligence market. Using quadrants, we plotted aggregated user sentiment

into x and y axes.

Customer Experience Model

The customer experience model considers the real-world experience of customers

working with BI products on a daily basis (fig. 110). For the x axis, we combined all

vendor touch points–including the sales and acquisition process (8 measures), technical

support (5 measures), and consulting services (5 measures)–into a single “sales and

service” dimension. On the y axis, we plotted customer sentiment surrounding product,

derived from the 12 product and technology measures used to rank vendors. On the

resulting four quadrants we plotted vendors based on these measures.

The upper-right quadrant contains the highest-scoring vendors and is named “overall

experience leaders.” Technology leaders (upper-left quadrant) identifies vendors with

strong product offerings but relatively lower services scores. Contenders (lower-left

quadrant) would benefit from varying degrees of improvement to product, services, or

both.

User sentiment surrounding outliers (outside of the four quadrants) suggests that

significant improvements are required to product and services.

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Figure 83 - Customer experience model

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Vendor Credibility Model

The vendor credibility model considers how customers “feel” about their vendor (fig.

111). The x axis plots perceived value for the price paid. The y axis combines the

integrity and recommend measures, creating a “confidence” dimension. The resulting

four quadrants position vendors based on these dimensions.

The upper-right quadrant contains the highest-scoring vendors and is named “credibility

leaders.” Trust leaders (upper-left quadrant) identifies vendors with solid perceived

confidence but relatively lower value scores. Contenders (lower-left quadrant) would

benefit by working to improve customer value, confidence, or both.

User sentiment surrounding outliers (outside of the four quadrants) suggests that

significant improvements are required to improve perceived value and confidence.

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Figure 84 - Vendor credibility model

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Detailed Vendor Ratings In this section, we offer detailed vendor scores. Using our 33-criteria evaluation model

(table 1), we compare each vendor’s performance to their previous year’s performance

and to the average for all vendors (all records in the study population).

The detailed criteria are below. We added “clock” position information to assist in

locating specific scores.

Table 1 - Detailed vendor rating criteria

- Sales/acquisition experience

(12 - 2 o’clock) o Professionalism o Product knowledge o Understanding our

business/needs o Responsiveness o Flexibility/accommodation o Business practices o Contractual terms and

conditions o Follow-up after the sale

- Value for price (3 o’clock)

- Quality and usefulness of product

(3 - 7 o’clock) o Robustness/sophistication of

technology o Completeness of functionality o Reliability of technology o Scalability o Integration of components

within product o Integration with third-party

technologies o Overall usability o Ease of installation o Ease of administration

- Quality and usefulness of product (continued)

o Customization and extensibility

o Ease of upgrade/migration to new versions

o Online forums and documentation

- - Quality of technical support

(8 - 9 o’clock) o Professionalism o Product knowledge o Responsiveness o Continuity of personnel o Time to resolve problems

- Quality and value of consulting

services (9 - 10 o’clock)

o Professionalism o Product knowledge o Experience o Continuity o Value

- Integrity (11 o’clock)

- Whether vendor is

recommended (12 o’clock)

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Birst Detailed Score

Figure 85 -Birst detailed score

With scores generally above the overall sample, Birst is an overall leader for both

Customer Experience and Vendor Credibility models. For 2016, it saw improvements in

sales responsiveness, product robustness/sophistication of technology, reliability of

technology, Integration with third-party technologies, ease of administration,

customization and extensibility, technical support professionalism, consulting

professionalism, and product knowledge.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Birst

Birst 2015 Birst 2016 Overall Sample

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Dell Detailed Score

Figure 86 - Dell detailed score

For the first year of coverage in our report, Dell is ranked as an overall leader in both

the Customer Experience and Vendor Credibility models. It scored substantially above

the overall sample for all measures and is best in class for technical support product

knowledge, consulting product knowledge, and has a perfect recommend score.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0Sales: professionalism

Product knowledgeUnderstanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of components…

Integration with third-party…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of upgrade/migration…

Online training, forums and…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Dell

Dell 2016 Overall Sample

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Dimensional Insight Detailed Score

Figure 87 – Dimensional Insight detailed score

With scores well above the entire sample, Dimensional Insight is a consistent overall

leader in both the Customer Experience and Vendor Credibility models. It is best in

class for sales product knowledge, understanding customer business/needs,

flexibility/accommodation, business practices, contractual terms and conditions, follow-

up after the sale, consulting product knowledge, and experience. It also saw

improvements in overall value, product robustness/sophistication of technology,

completeness of functionality, reliability of technology, integration with third-party

technologies, overall usability, ease of upgrade/migration to new versions, online

training, forums and documentation, consulting value, and recommend scores.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0Sales: professionalism

Product knowledgeUnderstanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Dimensional Insight

Dimensional Insight 2015 Dimensional Insight 2016 Overall Sample

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Domo Detailed Score

Figure 88 - Domo detailed score

For the first year of coverage in our report, Domo is ranked as a Technology Leader in

the Customer Experience Model and a Trust Leader in the Vendor Credibility Model. It

scored above the overall sample for most sales and product measures and was

generally in line with the sample for all others.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0Sales: professionalism

Product knowledgeUnderstanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of components…

Integration with third-party…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of upgrade/migration…

Online training, forums and…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Domo

Domo 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

111

Dundas Detailed Score

Figure 89 - Dundas detailed score

For 2016 Dundas is an overall leader in the Customer Experience Model and a Trust

Leader in the Vendor Credibility Model. It scores are generally above the overall sample

with improvements in 2016 for follow-up after the sale, product Integration with third-

party technologies, technical support responsiveness, continuity of personnel, time to

resolve problems, consulting professionalism, continuity, and value.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Dundas

Dundas 2015 Dundas 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

112

GoodData Detailed Score

Figure 90 - GoodData detailed score

For the first year of coverage in our report, GoodData is ranked as an overall leader in

both the Customer Experience and Vendor Credibility models. It scored above the

overall sample for virtually all measures and has a perfect recommend score.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0Sales: professionalism

Product knowledgeUnderstanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of components…

Integration with third-party…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of upgrade/migration…

Online training, forums and…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

GoodData

Gooddata 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

113

IBM Detailed Score

Figure 91 - IBM detailed score

Although below the overall sample, for 2016, IBM saw key improvements across most

measurement categories including sales, value, product, and consulting.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0Sales: professionalism

Product knowledgeUnderstanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

IBM

IBM 2015 IBM 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

114

Infor Detailed Score

Figure 92 - Infor detailed score

Although Infor’s performance declined year-over-year, it saw improvements in product

ease of installation, ease of upgrade/migration to new versions, online training, and

forums and documentation.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Infor

Infor 2015 Infor 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

115

Information Builders Detailed Score

Figure 93 - Information Builders detailed score

With scores consistently above the entire sample, Information Builders is an overall

leader in both the Customer Experience and Vendor Credibility models. It saw key

improvements in sales responsiveness and follow-up after the sale, consulting

professionalism, experience, continuity, and value. It has a perfect recommend score.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0Sales: professionalism

Product knowledgeUnderstanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Information Builders

Information Builders 2015 Information Builders 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

116

Jedox Detailed Score

Figure 94 - Jedox detailed score

For the first year of coverage in our report, Jedox is ranked as an overall leader in both

the Customer Experience and Vendor Credibility models. It scored above the overall

sample for virtually all measures and was best in class for value and overall product

usability. It has a perfect recommend score.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0Sales: professionalism

Product knowledgeUnderstanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of components…

Integration with third-party…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of upgrade/migration…

Online training, forums and…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Jedox

Jedox 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

117

Klipfolio Detailed Score

Figure 95 - Klipfolio detailed score

With scores consistently above the overall sample, Klipfolio is an overall leader in both

the Customer Experience and Vendor Credibility models. Its score increased year-over-

year with key improvements for most sales, value, product, technical support, and

recommend measures.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Klipfolio

Klipfolio 2015 Klipfolio 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

118

Logi Analytics Detailed Score

Figure 96. Logi Analytics detailed score

With scores generally in line with or slightly above the overall sample, Logi Analytics is a

Technology Leader in the Customer Experience Model and a Trust Leader in the

Vendor Credibility Model. For 2016, it saw an improvement in its overall score with

improvements across most measures for sales, value, product, technical support,

consulting, and integrity.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Logi Analytics

Logi Analytics 2015 Logi Analytics 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

119

Looker Detailed Score

Figure 97 - Looker detailed score

For the first year of coverage in our report, Looker is ranked as an overall leader in both

the Customer Experience and Vendor Credibility models. It scored significantly above

the overall sample for all measures and was best in class for sales professionalism,

responsiveness, product ease of installation, ease of administration, ease of

upgrade/migration to new versions, online training, forums and documentation, technical

support professionalism, responsiveness, continuity of personnel, time to resolve

problems, consulting continuity, value, and overall integrity.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of components…

Integration with third-party…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of upgrade/migration…

Online training, forums and…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Looker

Looker 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

120

Microsoft Detailed Score

Figure 98 - Microsoft detailed score

With scores generally below the overall sample, Microsoft is a Trust Leader in the

Vendor Credibility Model. It saw key improvements for 2016 in its overall score and

most categories of measurement including sales, product, technical support, consulting,

overall integrity, and recommend.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Microsoft

Microsoft 2015 Microsoft 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

121

MicroStrategy Detailed Score

Figure 99 - MicroStrategy detailed score

Although its scores declined compared to 2015, MicroStrategy saw improvements in

key areas of sales flexibility/accommodation, product robustness/sophistication of

technology, completeness of functionality, integration of components within product,

integration with third-party technologies, and consulting product knowledge.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

MicroStrategy

MicroStrategy 2015 MicroStrategy 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

122

OpenText Detailed Score

Figure 100 - OpenText detailed score

OpenText is Trust Leader in the Vendor Credibility Model. For 2016 it had key

improvements for sales contractual terms and conditions, product scalability, integration

of components within product, integration with third-party technologies, overall usability,

ease of installation, ease of administration, customization and extensibility, and

consulting value.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

OpenText

OpenText 2015 OpenText 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

123

Oracle Detailed Score

Figure 101 - Oracle detailed score

Oracle’s scores are generally below the overall sample and are lower compared to

2015. It saw some improvement in sales responsiveness, product completeness of

functionality, integration with third-party technologies, overall usability, ease of

installation, customization and extensibility, technical support time to resolve problems,

consulting value, and recommend.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Oracle

Oracle 2015 Oracle 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

124

Pentaho Detailed Score

Figure 102 - Pentaho (Hitachi) detailed score

Pentaho is a Trust Leader in the Vendor Credibility Model. Generally in line with the

overall sample, it saw improvements for 2016 in sales understanding of business/needs,

flexibility/accommodation, product integration of components within product, integration

with third-party technologies, ease of installation, ease of administration, customization

and extensibility, ease of upgrade/migration to new versions, online training, forums and

documentation, technical support product knowledge, and responsiveness.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Pentaho (Hitachi)

Pentaho 2015 Pentaho 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

125

Pyramid Analytics Detailed Score

Figure 103 - Pyramid Analytics detailed score

With scores well above the overall sample, Pyramid Analytics is an overall leader in

both Customer Experience and Vendor Credibility models. For 2016, it saw key

improvements compared to 2015 in virtually every category of measurement including

sales, value, product, technical support, consulting and integrity. It has a perfect

recommend score.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Pyramid Analytics

Pyramid Analytics 2015 Pyramid Analytics 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

126

Qlik Detailed Score

Figure 104 - Qlik detailed score

Qlik is a Technology Leader in the Customer Experience Model and a Trust Leader in

the Vendor Credibility Model. Generally in line with the overall sample, it saw

improvements for 2016 across most sales measures, and product integration of

components within product, integration with third-party technologies, customization and

extensibility, ease of upgrade/migration to new versions, technical support

responsiveness, consulting professionalism, product knowledge, value, and overall

integrity.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Qlik

Qlik 2015 Qlik 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

127

RapidMiner Detailed Score

Figure 105 - RapidMiner detailed score

RapidMiner is a Technology Leader in the Customer Experience Model and an overall

leader in the Vendor Credibility Model. Although its scores fell versus 2015, it saw key

improvements in overall value, product robustness/sophistication of technology,

reliability, ease of installation, ease of administration and ease of upgrade/migration to

new versions.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

RapidMiner

RapidMiner 2015 RapidMiner 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

128

Salesforce Detailed Score

Figure 106 - Salesforce detailed score

For the first year of coverage in our report, Salesforce is ranked as a Technology

Leader in the Customer Experience model with scores above or in line with the overall

sample.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of components…

Integration with third-party…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of upgrade/migration…

Online training, forums and…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Salesforce

Salesforce 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

129

SAP Detailed Score

Figure 107 - SAP detailed score

Although below the overall sample, SAP saw ongoing and significant improvements in

all categories of measurement including sales, value, product, technical support,

consulting, integrity, and recommend.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

SAP

SAP 2015 SAP 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

130

SAS Detailed Score

Figure 108 - SAS detailed score

Although generally below the overall sample for most scores, SAS saw improvements

across a number of sales, product, technical support, and integrity measures.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

SAS

SAS 2015 SAS 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

131

Sisense Detailed Score

Figure 109 - Sisense detailed score

With scores generally above the overall sample, Sisense is an overall leader for both

Customer Experience and Vendor Credibility models. Its overall score rose for 2016,

with key improvements across virtually all categories of measurement including sales,

value, product, and integrity. It has a perfect recommend score.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Sisense

Sisense 2015 Sisense 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

132

Tableau Software Detailed Score

Figure 110 – Tableau Software detailed score

With scores generally above the overall sample, Tableau Software is a Technology

Leader in the Customer Experience Model and a Trust Leader in the Vendor Credibility

Model. For 2016, it saw improvements in product completeness, scalability, technical

support product knowledge, and continuity of personnel, consulting product knowledge,

experience, and continuity.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Tableau Software

Tableau 2015 Tableau 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

http://www.dresneradvisory.com Copyright 2016 – Dresner Advisory Services, LLC

133

TIBCO Software Detailed Score

Figure 111 – TIBCO Software detailed score

With scores consistently above the overall sample, TIBCO Software is an overall leader

in both Customer Experience and Vendor Credibility models. Its overall score increased

year-over-year with key improvements across most categories of measurement

including sales, value, product, integrity and recommend. It is best in class for product

robustness/sophistication of technology, scalability, integration with third-party

technologies, customization, and extensibility. It has a perfect recommend score.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

TIBCO Software

TIBCO 2015 TIBCO 2016 Overall Sample

2016 Wisdom of Crowds® Business Intelligence Market Study

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134

Yellowfin Detailed Score

Figure 112 - Yellowfin detailed score

For 2016 Yellowfin is a Technology Leader in the Customer Experience Model and an

overall leader in the Vendor Credibility Model. Although its scores declined over 2015, it

saw improvements in product ease of administration, customization and extensibility

and online training, forums and documentation.

0.00.51.01.52.02.53.03.54.04.55.0

Sales: professionalismProduct knowledge

Understanding our…

Responsiveness

Flexibility/accommodation

Business practices

Contractual terms and…

Follow up after the sale

Value

Product: robustness/…

Completeness of…

Reliability of technology

Scalability

Integration of…

Integration with third-…Overall usability

Ease of installationEase of administrationCustomization and…

Ease of…

Online training, forums…

Support: professionalism

Product knowledge

Responsiveness

Continuity of personnel

Time to resolve problems

Consult: professionalism

Product knowledge

Experience

Continuity

Value

IntegrityRecommend

Yellowfin

Yellowfin 2015 Yellowfin 2016 Overall Sample

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Other Dresner Advisory Services Research Reports

- Advanced and Predictive Analytics

- Big Data Analytics

- Business Intelligence Competency Center

- Cloud Computing and Business Intelligence

- Collective InsightsTM

- Embedded Business Intelligence

- End User Data Preparation

- Enterprise Planning

- Internet of Things and Business Intelligence

- Location Intelligence

- Mobile Computing and Business Intelligence

- Small and Mid-sized Enterprise Business Intelligence

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Dresner Advisory Services - 2016 Wisdom of Crowds Survey

Please enter your contact information below

First Name*: _________________________________________________

Last Name*: _________________________________________________

Title: _________________________________________________

Company Name*: _________________________________________________

Street Address: _________________________________________________

City: _________________________________________________

State: _________________________________________________

Zip: _________________________________________________

Country: _________________________________________________

Email Address*: _________________________________________________

Phone Number: _________________________________________________

URL: _________________________________________________

May we contact you to discuss your responses and for additional information?

( ) Yes

( ) No

What major geography do you reside in?*

( ) North America

( ) Europe, Middle East and Africa

( ) Latin America

( ) Asia Pacific

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Please identify your primary industry*

( ) Advertising

( ) Aerospace

( ) Agriculture

( ) Apparel & accessories

( ) Automotive

( ) Aviation

( ) Biotechnology

( ) Broadcasting

( ) Business services

( ) Chemical

( ) Construction

( ) Consulting

( ) Consumer products

( ) Defense

( ) Distribution & logistics

( ) Education (Higher Ed)

( ) Education (K-12)

( ) Energy

( ) Entertainment and leisure

( ) Executive search

( ) Federal government

( ) Financial services

( ) Food, beverage and tobacco

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( ) Healthcare

( ) Hospitality

( ) Insurance

( ) Legal

( ) Manufacturing

( ) Mining

( ) Motion picture and video

( ) Not for profit

( ) Pharmaceuticals

( ) Publishing

( ) Real estate

( ) Retail & wholesale

( ) Sports

( ) State and local government

( ) Technology

( ) Telecommunications

( ) Transportation

( ) Utilities

( ) Other - Write In: _________________________________________________

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How many employees does your company employ worldwide?

( ) 1 - 100

( ) 101 - 1,000

( ) 1,001 - 2,000

( ) 2,001 - 5,000

( ) 5,001 - 10,000

( ) More than 10,000

What function do you report into?*

( ) Business Intelligence Competency Center

( ) Executive management

( ) Faculty (Education)

( ) Finance

( ) Human resources

( ) Information Technology (IT)

( ) Manufacturing

( ) Marketing

( ) Medical staff (Healthcare)

( ) Operations

( ) Research and development (R&D)

( ) Sales

( ) Strategic planning function

( ) Supply chain

( ) Other - Write In: _________________________________________________

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Does your organization have a Chief Data Officer or Chief Analytics Officer in place?

For

less

than

1

year

1 -3

years

3 - 5

years

More

than

5

years

Not

applicable

Chief

Data

Officer

( ) ( ) ( ) ( ) ( )

Chief

Analytics

Officer

( ) ( ) ( ) ( ) ( )

8) Where do these roles report into?

Chief

Data

Officer

Chief

Analytics

Officer

CEO ( ) ( )

CFO ( ) ( )

CMO ( ) ( )

CIO ( ) ( )

Not

Applicable

( ) ( )

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Core Business Intelligence

Please respond to the following statement: "My organization considers our Business

Intelligence initiatives a success.

( ) Completely agree

( ) Agree somewhat

( ) Disagree somewhat

( ) Disagree

Why has your organization been successful or unsuccessful?

____________________________________________

____________________________________________

____________________________________________

____________________________________________

Which function drives your Business Intelligence initiatives?

Always Often Sometimes Rarely Never

Operations ( ) ( ) ( ) ( ) ( )

Faculty

(education)

( ) ( ) ( ) ( ) ( )

Business

Intelligence

Competency

Center

( ) ( ) ( ) ( ) ( )

Sales ( ) ( ) ( ) ( ) ( )

Finance ( ) ( ) ( ) ( ) ( )

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Research and

development

(R&D)

( ) ( ) ( ) ( ) ( )

Information

Technology

(IT)

( ) ( ) ( ) ( ) ( )

Clinical

(Healthcare)

( ) ( ) ( ) ( ) ( )

Human

resources

( ) ( ) ( ) ( ) ( )

Supply chain ( ) ( ) ( ) ( ) ( )

Executive

management

( ) ( ) ( ) ( ) ( )

Marketing ( ) ( ) ( ) ( ) ( )

Manufacturing ( ) ( ) ( ) ( ) ( )

Strategic

planning

function

( ) ( ) ( ) ( ) ( )

What does your organization expect to achieve with Business Intelligence?

Critical

Very

important Important

Somewhat

important Unimportant

Better

decision-

making

( ) ( ) ( ) ( ) ( )

Growth in

revenues

( ) ( ) ( ) ( ) ( )

Improved ( ) ( ) ( ) ( ) ( )

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operational

efficiency

Enhanced

customer

service

( ) ( ) ( ) ( ) ( )

Increased

competitive

advantage

( ) ( ) ( ) ( ) ( )

Who are the targeted consumers of Business Intelligence within your organization?

Primary Secondary

Not

targeted

Executives ( ) ( ) ( )

Middle

managers

( ) ( ) ( )

Line

managers

( ) ( ) ( )

Individual

contributors

&

professionals

( ) ( ) ( )

Customers ( ) ( ) ( )

Suppliers ( ) ( ) ( )

What percentage of all employees have access to Business Intelligence solutions?

Under

10%

11 -

20%

21 -

40%

41 -

60%

61 -

80%

81%

or

more

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Today ( ) ( ) ( ) ( ) ( ) ( )

In 12

months

( ) ( ) ( ) ( ) ( ) ( )

In 24

months

( ) ( ) ( ) ( ) ( ) ( )

In 36

months

( ) ( ) ( ) ( ) ( ) ( )

Please choose one of the following to describe the state of data governance in your

organization.

( ) Data as "truth" - A common view of enterprise data is available with common

application of data, filters, rules, and semantics.

( ) A common view of enterprise data is available. However, parochial views and

semantics are used to support specific positions

( ) Consistent data is available at a departmental level. Conflicting, functional views of

data causes confusion and disagreement

( ) We have multiple, inconsistent data sources with conflicting semantics and data.

Information is generally unreliable and distrusted

How do people in your organization take advantage of insights learned from Business

Intelligence solutions?

( ) “Closed loop” - Information is shared, teams work to process and act in a timely

fashion. No formal boundaries

( ) Ad hoc (informal) action on insights across functions

( ) Uncoordinated/ parochial action (sometimes at the expense of others)

( ) Insights are rarely leveraged

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Please indicate the importance of the following technologies to your Business

Intelligence strategy and plans.

Critical

Very

important Important

Somewhat

important

Not

important

Ability to write to

transactional

applications

( ) ( ) ( ) ( ) ( )

Advanced

visualization

( ) ( ) ( ) ( ) ( )

Big Data (e.g.,

Hadoop)

( ) ( ) ( ) ( ) ( )

Cognitive BI (e.g.,

Artificial

Intelligence-based

BI)

( ) ( ) ( ) ( ) ( )

Collaborative

support for group-

based analysis

( ) ( ) ( ) ( ) ( )

Complex event

processing (CEP)

( ) ( ) ( ) ( ) ( )

Dashboards ( ) ( ) ( ) ( ) ( )

Data discovery ( ) ( ) ( ) ( ) ( )

Data mining,

advanced

algorithms,

predictive

( ) ( ) ( ) ( ) ( )

Data story telling ( ) ( ) ( ) ( ) ( )

Data warehousing ( ) ( ) ( ) ( ) ( )

Edge computing ( ) ( ) ( ) ( ) ( )

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Embedded BI

(contained within an

application, portal,

etc.)

( ) ( ) ( ) ( ) ( )

End user "self

service"

( ) ( ) ( ) ( ) ( )

End user data

preparation and

blending

( ) ( ) ( ) ( ) ( )

Enterprise

planning/budgeting

( ) ( ) ( ) ( ) ( )

Governance ( ) ( ) ( ) ( ) ( )

In-memory analysis ( ) ( ) ( ) ( ) ( )

Integration with

operational

processes

( ) ( ) ( ) ( ) ( )

Internet of things

(IoT)

( ) ( ) ( ) ( ) ( )

Location

intelligence/analytics

( ) ( ) ( ) ( ) ( )

Mobile device

support

( ) ( ) ( ) ( ) ( )

Open source

software

( ) ( ) ( ) ( ) ( )

Pre-packaged

vertical/functional

analytical

applications

( ) ( ) ( ) ( ) ( )

Reporting ( ) ( ) ( ) ( ) ( )

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Search-based

interface

( ) ( ) ( ) ( ) ( )

Social media

analysis (SocialBI)

( ) ( ) ( ) ( ) ( )

Software-as-a-

service and cloud

computing

( ) ( ) ( ) ( ) ( )

Streaming data

analysis

( ) ( ) ( ) ( ) ( )

Text analytics ( ) ( ) ( ) ( ) ( )

How many Business Intelligence products are currently being used in your organization

today?

( ) Don't know

( ) 1

( ) 2

( ) 3

( ) 4

( ) 5

( ) 6

( ) 7

( ) 8

( ) 9

( ) 10 or more

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Business Intelligence Vendor Ratings

Please select one vendor to rate

( ) 1010 Data

( ) Actuate (OpenText)

( ) Adaptive Insights

( ) Advizor Solutions

( ) Alpine Data Labs

( ) Alteryx

( ) Altosoft

( ) Arcplan (Longview)

( ) Bime (Zendesk)

( ) Birst

( ) Bitam

( ) Board

( ) ClearStory

( ) Cubeware

( ) Datameer

( ) Datawatch (inc. Panopticon)

( ) Decisyon

( ) Dell Statistica

( ) Dimensional Insight

( ) Domo

( ) Dundas

( ) Entrinsik

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( ) Exago

( ) Good Data

( ) IBM/Cognos/SPSS

( ) iDashboards

( ) Inetsoft

( ) Infor/Lawson

( ) Information Builders (IBI)

( ) IntuitiveBI

( ) Izenda

( ) Jedox

( ) Jinfonet/JReport

( ) Klipfolio

( ) Knime

( ) Lavastorm

( ) LogiAnalytics

( ) Looker

( ) Microsoft

( ) MicroStrategy

( ) Neudesic

( ) NeutrinoBI

( ) Oracle

( ) Panorama

( ) Pentaho

( ) Phocas

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( ) Platfora

( ) Predixion

( ) Prognoz

( ) Pyramid Analytics

( ) Qlik

( ) RapidMiner

( ) Roambi (MeLLmo)

( ) Salesforce.com

( ) Salient

( ) SAP/Business Objects

( ) SAS Institute

( ) SiSense

( ) Tableau

( ) Targit

( ) TIBCO (Spotfire, Jaspersoft)

( ) Thoughtspot

( ) Yellowfin

( ) Other - Write In: _________________________________________________

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Please specify the product name and version for the selected vendor

How long has this product been in use?

( ) Less than 1 year

( ) 1 - 2 years

( ) 3 - 5 years

( ) 6 - 10 years

( ) More than 10 years

How many users currently use this product?

( ) 1-10

( ) 11-50

( ) 51-100

( ) 101-200

( ) 201-500

( ) More than 500

How would you characterize the sales/acquisition experience with this vendor?

Excellent

Very

good Adequate Poor

Very

poor

Don't

know

Professionalism ( ) ( ) ( ) ( ) ( ) ( )

Product knowledge ( ) ( ) ( ) ( ) ( ) ( )

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Understanding our

business/needs

( ) ( ) ( ) ( ) ( ) ( )

Responsiveness ( ) ( ) ( ) ( ) ( ) ( )

Flexibility/accommodation ( ) ( ) ( ) ( ) ( ) ( )

Business practices ( ) ( ) ( ) ( ) ( ) ( )

Contractual terms and

conditions

( ) ( ) ( ) ( ) ( ) ( )

Follow up after the sale ( ) ( ) ( ) ( ) ( ) ( )

How would you characterize the value for the price paid?

( ) Great value (Well exceeded expectations)

( ) Good value (Somewhat exceeded expectations)

( ) Average value (Met expectations)

( ) Poor value (Fell short of expectations)

( ) Very poor value (Fell far short of expectations)

How would you characterize the quality and usefulness of the product?

Excellent

Very

good Adequate Poor

Very

poor

Don't

know

Robustness/sophistication

of technology

( ) ( ) ( ) ( ) ( ) ( )

Completeness of

functionality

( ) ( ) ( ) ( ) ( ) ( )

Reliability of technology ( ) ( ) ( ) ( ) ( ) ( )

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Scalability ( ) ( ) ( ) ( ) ( ) ( )

Integration of

components within

product

( ) ( ) ( ) ( ) ( ) ( )

Integration with 3rd party

technologies

( ) ( ) ( ) ( ) ( ) ( )

Overall Usability ( ) ( ) ( ) ( ) ( ) ( )

Ease of installation ( ) ( ) ( ) ( ) ( ) ( )

Ease of administration ( ) ( ) ( ) ( ) ( ) ( )

Customization and

Extensibility

( ) ( ) ( ) ( ) ( ) ( )

Ease of

upgrade/migration to new

versions

( ) ( ) ( ) ( ) ( ) ( )

Online training, forums

and documentation

( ) ( ) ( ) ( ) ( ) ( )

How would you characterize the vendor's technical support?

Excellent

Very

good Adequate Poor

Very

poor

Don't

know

Professionalism ( ) ( ) ( ) ( ) ( ) ( )

Product

knowledge

( ) ( ) ( ) ( ) ( ) ( )

Responsiveness ( ) ( ) ( ) ( ) ( ) ( )

Continuity of

personnel

( ) ( ) ( ) ( ) ( ) ( )

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Time to resolve

problems

( ) ( ) ( ) ( ) ( ) ( )

How would you characterize the vendor's consulting services?

Excellent

Very

good Adequate Poor

Very

poor

Don't

know

Professionalism ( ) ( ) ( ) ( ) ( ) ( )

Product

knowledge

( ) ( ) ( ) ( ) ( ) ( )

Responsiveness ( ) ( ) ( ) ( ) ( ) ( )

Continuity of

personnel

( ) ( ) ( ) ( ) ( ) ( )

Time to resolve

problems

( ) ( ) ( ) ( ) ( ) ( )

How would you rate the "integrity" (i.e., truthfulness, honesty) of this BI vendor?

( ) Excellent

( ) Very good

( ) Adequate

( ) Poor

( ) Very poor

( ) Don't know

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Did this vendor's overall performance improve, remains the same or decline from last

year?

( ) Improved

( ) Stayed the same

( ) Declined

Would you recommend this vendor/product?

( ) I would recommend this vendor/product

( ) I would NOT recommend this vendor/product

Please enter any additional comments regarding this vendor and/or its products

____________________________________________


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