wisdom of crowds® bi market study - licensed to tibco - copyright 2016 dresner advisory services...
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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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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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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%
20%
30%
40%
50%
60%
70%
80%
90%
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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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%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
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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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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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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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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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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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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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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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%
20%
30%
40%
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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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
0%
10%
20%
30%
40%
50%
60%
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100%
In 1
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on
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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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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%
20%
30%
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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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%
20%
30%
40%
50%
60%
70%
80%
90%
100%
In 1
2 m
on
ths
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on
ths
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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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%
10%
20%
30%
40%
50%
60%
70%
80%
90%
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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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%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
In 1
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on
ths
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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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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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
0%
10%
20%
30%
40%
50%
60%
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80%
90%
100%
In 1
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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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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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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%
2%
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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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
Edu
cati
on
(H
igh
er E
d)
Fin
anci
al s
ervi
ces
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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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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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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%
10%
15%
20%
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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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%
10%
15%
20%
25%
30%
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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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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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
____________________________________________