September 15, 2016 Dresner Advisory Services, LLC 2016 Edition Small and Mid-Sized Enterprise Business Intelligence Market Study Wisdom of Crowds ® Series Licensed to TIBCO
September 15, 2016
Dresner Advisory Services, LLC
2016 Edition
Small and Mid-Sized Enterprise Business Intelligence Market Study
Wisdom of Crowds®
Series
Licensed to TIBCO
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
http://www.dresneradvisory.com Copyright 2016 Dresner Advisory Services, LLC
2
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 its content.
Reproduction and distribution of this publication in any form without prior written permission is forbidden.
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Business Intelligence: A Definition We define Business intelligence (BI) as “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 are on track to release 15 major reports, including our recent flagship BI
report—in its seventh year of publication!
In addition, 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.
For this, our fourth SME market study report, we created a focused, detailed report
examining business intelligence in small and mid-sized organizations. In particular, we
consider how their deployments and views differ from each other and from larger
organizations. Also included is an SME buyer’s guide for 24 BI software vendors.
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 ....................................................................................................... 7
A Consumer Guide ...................................................................................................... 7
A Supplier Tool ............................................................................................................ 7
External Awareness .................................................................................................. 7
Internal Planning ....................................................................................................... 7
About Howard Dresner and Dresner Advisory Services .................................................. 8
About Jim Ericson ........................................................................................................... 9
Survey Method and Data Collection .............................................................................. 10
Executive Summary ...................................................................................................... 12
Study Demographics ..................................................................................................... 13
Geography ................................................................................................................. 13
Functions ................................................................................................................... 14
Vertical Industries ...................................................................................................... 15
Analysis and Trends ...................................................................................................... 17
How SMEs Differ ........................................................................................................... 18
Technology Priorities Changing ................................................................................. 18
Departments/Functions Driving Business Intelligence ............................................... 20
Departmental Drivers .............................................................................................. 20
User Roles Targeted for Business Intelligence .......................................................... 22
Objectives for Business Intelligence .......................................................................... 24
Business Intelligence Objectives by Function ......................................................... 26
Penetration of Business Intelligence .......................................................................... 27
SME Success with Business Intelligence ................................................................... 30
SMEs and State of Data ............................................................................................ 32
SMEs and Action on Insight ....................................................................................... 34
Business Intelligence Market Models for SMEs ............................................................ 37
Customer Experience Model for SMEs ...................................................................... 37
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Vendor Credibility Model for SMEs ............................................................................ 39
SME Business Intelligence Buyers’ Guide .................................................................... 41
Cloud Platform Support – Vendors (B – I) .................................................................. 41
Cloud Platform Support – Vendors (K – M) ................................................................ 42
Cloud Platform Support – Vendors (O – Q) ............................................................... 43
Cloud Platform Support – Vendors (S – Y) ................................................................ 44
Mobile Platform Support Vendors (B – I) ................................................................... 45
Mobile Platform Support Vendors (K – O) .................................................................. 46
Mobile Platform Support Vendors (P – Y) .................................................................. 47
Traditional Platform Support Vendors (D – I) ............................................................. 48
Traditional Platform Support Vendors (L – O) ............................................................ 49
Traditional Platform Support Vendors (P – R) ............................................................ 50
Traditional Platform Support Vendors (S – Y) ............................................................ 51
Other Dresner Advisory Services Research Reports .................................................... 52
Appendix - The 2016 Wisdom of Crowds® Business Intelligence Market Survey
Instrument ..................................................................................................................... 53
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Benefits of the Study The DAS Small and Mid-Sized Enterprise Business Intelligence Market Study provides
a wealth of information and analysis—offering value to both consumers and producers
of business intelligence technology and services.
A Consumer Guide
As an objective source of industry research, consumers use the DAS Small and Mid-
Sized Enterprise Business Intelligence Market Study to understand how their peers use
and invest in business intelligence and related technologies.
Using our trademark 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
A Supplier Tool
Vendor Licensees can use the DAS Small and Mid-Sized Enterprise Business
Intelligence Market Study in several important ways, for example to:
External Awareness
- Build awareness for the business intelligence market and supplier brand, citing the
DAS Small and Mid-Sized Enterprise Business Intelligence Market Study trends and
vendor performance
- Create lead and demand generation for supplier offerings through association with
the DAS Small and Mid-Sized Enterprise Business Intelligence Market Study brand,
findings, webinars, etc.
Internal Planning
- Refine internal product plans and align with market priorities and realities as
identified in the DAS Small and Mid-Sized Enterprise 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 DAS Small and Mid-Sized Enterprise 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
- Enterprise Planning
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 Vice President and 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 For this SME study, we sampled data sets from the 2016 Wisdom of Crowds Business
Intelligence Market Survey. Dresner Advisory Services defines “small enterprise” as an
organization with between one and 100 employees, “mid-sized enterprise” as an
organization with between 101 and 1,000 employees, and “large enterprise” as an
organization with more than 1,000 employees. We constructed the study from a survey
instrument to collect data and used social media and crowdsourcing techniques to
recruit participants.
Figure 1 – SME study sample
31% 30%
39%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
Small (1 - 100) Mid (101 - 1000) Large (1001+)
SME Study Sample
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Executive
Summary
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Executive Summary
Small and mid-sized enterprises prioritize a wide span of BI technologies and
initiatives. Top priorities include "nuts and bolts" dashboards, data discovery, and
reporting. Compared to large peers, small organizations are more interested in
cloud, open source, social media analysis, and less so in data warehousing (p. 18).
Top SME technology priorities have remained consistent over time, but sentiment
has cooled somewhat (p. 19).
While operations and executive management are the largest drivers of BI at
organizations of any size, sales, and to a lesser effect marketing, take bigger roles at
SMEs (p. 20). SME BI driver momentum across all functions has cooled somewhat
over time (p. 21).
SMEs (with thinner management ranks), are most likely to target BI toward
executives and have higher interest in customer empowerment (p. 22- 23).
Small organizations are more likely to focus outwardly with BI initiative objectives
(revenues, competitive advantage); large organizations are geared more toward
operational efficiency (p. 24-26).
Current BI penetration is much higher and future plans are much more aggressive at
small compared to large organizations (p. 27-29).
Estimates of success with BI are highest at small organizations; expectations of BI
success for the most part decrease as organization size increases (p. 30).
Organizational estimates of trustworthy data and ability to take action based on data
decrease as organization size increases (p. 31-35)
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Study Demographics The respondents studied in this SME survey provide a cross-section of geographies,
functions, organization sizes, and vertical industries. We believe this is a representative
sample and more useful indicator of true market dynamics. We constructed cross-tab
analyses using these demographics to identify and illustrate important industry trends.
Geography
In our 2016 study, 56 percent of respondents are located in North America, which
includes the United States, Canada, and Puerto Rico (fig. 2). EMEA organizations
account for 29 percent of respondents. Asia Pacific (10 percent) and Latin America (4
percent) are the other regions represented.
Figure 2 – SME geographies represented
North America, 56.4%
Europe, Middle East and Africa, 29.1%
Asia Pacific, 10.4%
Latin America, 4.1%
SME Geographies Represented
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Functions
Information technology (29 percent) and executive management (28 percent) are the
functions most represented in the study. Ten percent of respondents represent the
business intelligence competency center (BICC), which in the SME market can include
dedicated BI resources as well as formal organizational departments (fig. 3). Finance
and marketing/sales are the next most represented.
Measuring attitudes and behaviors by function helps us develop analyses comparing
and contrasting the plans and priorities of the different departments within
organizations.
Figure 3 – SME functions represented
29% 28%
10% 8%
6% 4% 4%
3% 2%
6%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
SME Functions Represented
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Vertical Industries
Vertical industry distribution in our 2016 study is led by consulting followed by
technology and healthcare (fig. 4). Education, financial services, business services, and
manufacturing are the next most represented.
Figure 4 – SME vertical industries represented
14%
11%
10%
7% 7% 6% 6%
4%
3% 3% 3% 2% 2% 2% 1% 1% 1% 1% 1% 1%
11%
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
SME Vertical Industries Represented
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Analysis and
Trends
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Analysis and Trends This report describes the small and midsized enterprise market for business intelligence
by its own characteristics, drivers, trends, and also by how it compares to the large
enterprise market.
In 2016 we sampled SME experience with business intelligence including the uptake of
technologies, year over year and future plans. As in our larger Wisdom of Crowds study,
we collected and analyzed data for SMEs surrounding functions driving business
intelligence, goals/objectives for BI, targeted user roles, current penetration, and future
plans for business intelligence deployment and organizational success.
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How SMEs Differ
Technology Priorities Changing
Much like large organizations, small and mid-sized enterprises prioritize a wide span of
BI technologies and initiatives (fig. 5). Top priorities common to organizations of any
size include "nuts and bolts" dashboards, data discovery, and reporting. However, there
are significant distinctions between small and large organizations elsewhere. Large
organizations are much more likely to prioritize data warehousing, and they have
somewhat more extensive reporting requirements. Large organizations are more
interested in data mining, enterprise planning, governance, and big data, among other
areas. Small and mid-sized organizations are predictably much more interested in cloud
computing and, to a lesser extent, open source and social media analysis. Generally,
we find small organizations are early adopters where risk exposure and time/cost of
implementation are lower.
Figure 5 - Technology priorities by organization size
1
1.5
2
2.5
3
3.5
4
4.5Dashboards
ReportingAdvanced visualization
Data discovery
End-user "self service"
Data warehousing
Data storytelling
Integration with operational processes
Data mining, advanced algorithms,…
Mobile device support
Enterprise planning/budgeting
Embedded BI (contained within an…
Software-as-a-Service and cloud…
Collaborative support for group-based…End-user data preparation and blending
GovernanceSearch-based interface
In-memory analysis
Location intelligence/analytics
Ability to write to transactional…
Big Data (e.g., Hadoop)
Pre-packaged vertical/functional…
Streaming data analysis
Open source software
Social media analysis (Social BI)
Text analytics
Cognitive BI (e.g., Artificial Intelligence-…
Complex event processing (CEP)
Internet of Things (IoT)Edge computing
Technology Priorities by Organization Size
Small (1 - 100) Mid (101 - 1000) Large (1001+)
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SME technology priority rankings have remained mostly consistent across four years of
study with some cooling of interest over time (fig. 6). We believe this reflects good
market awareness and some maturing of planning in response to BI provider marketing
and industry trends. Areas of sustained high interest include mainstays such as
dashboards, reporting, and advanced visualization. Data discovery gained momentum
in 2016. Interest in mobile, software as a service, end-user data preparation and
search-based interface have all diminished somewhat, though all remain in the top one-
half of respondent priorities. Pre-packaged applications, which we would expect to
appeal to the SME audience, fell most sharply across four years of study.
Figure 6 – SME technology priorities 2013 to 2016
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
DashboardsReporting
End-user "self service"
Advanced visualization
Data Discovery
Data Warehousing
Integration with operational processes
Mobile device support
Data storytelling
Data mining, advanced algorithms,predictive
Embedded BI (contained within anapplication, portal, etc.)
Enterprise planning/budgeting
Software-as-a-Service and "Cloud"computing
End-user data preparation and blendingCollaborative support for group-based
analysisSearch-based interface
In-memory analysis
Governance
Location intelligence/analytics
Pre-packaged vertical/functionalanalytical applications
Ability to write to transactionalapplications
Big Data (e.g., Hadoop)
Text analytics
Social media analysis (Social BI)
Streaming data analysis
Open source software
Cognitive BI (e.g., Artificial Intelligence-based BI)
Complex event processing (CEP)
Internet of Things (IoT)
Edge computing
SME Technology Priorities 2013 to 2016
2013 2014 2015 2016
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Departments/Functions Driving Business Intelligence
Our 2016 survey looks at the functions that drive business intelligence initiatives within
the organization. We asked respondents to specify whether a given function drives
business intelligence “always,” “often,” “sometimes,” “rarely,” or “never.” We used this to
create a weighted average on a one-to-five scale.
Departmental Drivers
While operations and executive management are the largest drivers of BI at
organizations of any size, sales, and to a lesser effect marketing, take bigger roles at
SMEs (fig. 7). Finance is a stronger driver in mid-sized and larger organizations and,
predictably, IT influence as a central BI authority grows with organization headcount.
BICC, supply chain, and human resource influence are stronger in large organizations,
which are more likely to support these roles.
Figure 7 – Functions driving business intelligence by organization size
1
1.5
2
2.5
3
3.5
4
4.5
Functions Driving Business Intelligence by Organization Size
Small (1 - 100) Mid (101 - 1000) Large (1001+)
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Like BI technology priorities, SME drivers of business intelligence have mostly held rank
across four years of study, albeit with some cooling of interest (fig. 8). The obvious
exception to this trend is in operations, which gained influence and jumped three or four
places to become the top SME departmental driver in 2016. We expect the growth in
operational influence could be a nod to efficiency and establishment of leading
institutional BI best practices in SMEs. That said, SMEs still maintain a broad range of
drivers across roles and departments.
Figure 8 - SME drivers of BI 2013 to 2016
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
SME Drivers of BI 2013 to 2016
2013 2014 2015 2016
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User Roles Targeted for Business Intelligence
Our survey asked which functions/roles are targeted with business intelligence
solutions. Respondents were able to designate these roles as either “primary,”
“secondary,” or “not applicable.” Among all organizations sampled, the majority
prioritized (in order) executives, middle managers, line managers, individuals,
customers, and suppliers.
Small and mid-sized enterprises, which by definition have smaller middle management
ranks than larger peers, are most likely to target executives over other roles (fig. 9).
SMEs are also less likely to target individual contributors but are most likely (almost 30
percent) to target customers with business intelligence. Suppliers remain the least
interested BI target, with less than 5 percent interest among organizations of any size
large or small.
Figure 9 - Primary targeted users for business intelligence by organization size
0%
10%
20%
30%
40%
50%
60%
70%
Executives Middlemanagers
Line managers Individualcontributors &professionals
Customers Suppliers
Primary Targeted Users for Business Intelligence by Organization Size
Small (1 - 100) Mid (101 - 1000) Large (1001+)
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Across four years of study, BI targeting at SMEs has incrementally cooled, perhaps in
light of maturing practices that delivered existing constituencies of users (fig. 10).
Interest in BI targeting of customers nonetheless ticked up slightly in 2016 while
executive, manager, and individual targeting was lower year over year. (Fig. 10
combines small and mid-sized organizations, which have some differences in
sentiment.)
Figure 10 - SME targets for BI 2013 to 2016
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Executives MiddleManagers
Line Managers IndividualContributors &Professionals
Customers Suppliers
SME Targets for BI 2013 - 2016
2013 2014 2015 2016
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Objectives for Business Intelligence
BI objectives are somewhat consistent across organizations of different sizes with
subtle differences (fig. 11). In a general sense, small organizations are a bit more likely
to focus outwardly (revenues, competitive advantage) and are more focused on
customers than larger peers. Among all organizations of any size, “better decision
making” is the most-cited objective and a goal that gains momentum with organization
size. Likewise, operational efficiency is a goal associated with scale and complexity of
business processes and thus is more likely to appeal to large organizations.
Figure 11 - Business intelligence objectives by organization size
1
1.5
2
2.5
3
3.5
4
4.5
5
Better decision-making
Improvedoperationalefficiency
Growth inrevenues
Increasedcompetitiveadvantage
Enhancedcustomer service
Business Intelligence Objectives by Organization Size
Small (1 - 100) Mid (101 - 1000) Large (1001+)
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Across four years of data, SME sentiment toward all BI objectives has cooled slightly,
though prioritized rankings have held fast (fig. 12). "Better decision making" is
consistently the top choice (though less pronounced at SMEs than large enterprises as
noted in fig. 11, p. 24). No priority falls below a mean value of 3.5, indicating "very high"
importance.
Figure 12 – SME BI objectives 2014 to 2016
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
4.50
5.00
Better decisionmaking
Improvedoperationalefficiency
Growth in revenues Increasedcompetitiveadvantage
Enhanced customerservice
SME BI Objectives 2013 - 2016
2013 2014 2015 2016
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Business Intelligence Objectives by Function
Across SMEs (and our entire sample), "better decision making" is the perennial top BI
objective of organizations, which tells us that specific functions take an opportunistic
approach as market conditions change. In compartmentalized roles, it's predictable to
find marketing and sales concerned with growth and revenues while finance focuses on
efficiencies (fig. 13). BICC likewise takes above-mean interest in competitive advantage
as well as enhanced customer service.
Figure 13 – BI objectives by function: SMEs Only
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: SMEs Only
Executive Management Marketing and Sales
Information Technology (IT) Finance
Business Intelligence Competency Center Mean
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Penetration of Business Intelligence
As is historically the case, SMEs in 2016 report much higher levels of business
intelligence penetration than larger organizations, a finding that can be accounted for in
part by simple headcount (fig. 14). Not to underestimate this SME BI pervasiveness,
small enterprises (1-100 employees) are almost three times as likely as large
organizations to report the highest (81 percent or more) BI penetration and significantly
less likely to report the lowest levels of penetration. Mid-sized organizations (100-1,000
employees) also report their BI penetration is greater than large peers but by a much
smaller margin.
Figure 14 – Business intelligence penetration today by organization size
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Under 10% 11 - 20% 21 - 40% 41 - 60% 61 - 80% 81% or more
Business Intelligence Penetration Today by Organization Size
Small (1 - 100) Mid (101 - 1000) Large (1001+)
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In addition to high existing BI penetration, small organizations are much more
aggressive in their plans to reach higher levels of BI penetration in 12, 24, and 36-
month time frames (fig. 15). This finding, in part, reflects the agility of small
organizations to adopt at lower cost and accept risk more easily than larger peers. To a
lesser degree, the sentiment to increase high-level penetration extends to mid-sized
peers. Large organizations are more likely to pursue future deployments focused on low
and mid-level enterprise BI strategies that "lift all boats."
Figure 15 – Planned business intelligence penetration through 2019 by organization size
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
In 12months
In 24months
In 36months
In 12months
In 24months
In 36months
In 12months
In 24months
In 36months
Small (1 - 100) Mid (101 - 1000) Large (1001+)
Planned Business Intelligence Penetration through 2019 by Organization Size
Under 10% 11 - 20% 21 - 40% 41 - 60% 61 - 80% 81% or more
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Across three years of data, SMEs have reported growing levels of BI penetration (fig.
16). As percentages for low-level penetration (<10 percent, 11-20 percent, 21-40
percent) have decreased and mid-level (41-60 percent) has flattened, the highest levels
of penetration (up to 81 percent or greater) increased in mean value over time. We
believe this trend helps affirm and validate our case that BI adoption is stronger at
SMEs than at larger organizations.
Figure 16 - SME BI penetration 2014 to 2016
0%
5%
10%
15%
20%
25%
30%
35%
Under 10% 11 - 20% 21 - 40% 41 - 60% 61 - 80% 81% or more
SME BI Penetration 2014 - 2016
2014
2015
2016
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SME Success with Business Intelligence
The likelihood of reporting "complete success" with business intelligence programs and
initiatives is, by far, most pronounced in small (1-100 employees) organizations (fig. 17).
Estimations of "complete success" thereafter decrease as organization size (along with
cost and complexity) increases. Mid-sized (100-1,000 employees) and larger
organizations are incrementally more likely to "agree somewhat" that their BI work has
been successful. Fewer than 10 percent of all organizations "disagree somewhat" that
BI has been successful, and only a handful (3 percent or less) "disagree" summarily.
Figure 17 - Success with business intelligence by organization size
0
0.1
0.2
0.3
0.4
0.5
0.6
Completely agree Agree somewhat Disagree somewhat Disagree
Success with Business Intelligence by Organization Size
Small (1 - 100) Mid (101 - 1000) Large (1001+)
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Over time, SME estimates of BI success have wavered somewhat. The 2013 high-water
mark for "complete success" dwindled in 2015 before rebounding slightly in our 2016
survey (fig. 18). Correspondingly, the number that "somewhat agree" that their BI work
has been successful increased over time to offset this decline. That said, sentiment
regarding these two top levels of achievement have remained between 40 percent and
48 percent in the four years of our survey. We find it a positive that lower estimates
("somewhat disagree," "disagree") are low and have remained steady over time,
perhaps confined to a few insistent holdouts/doubters and perhaps a few hapless
organizations.
Figure 18 - SME and BI success 2013 to 2016
0%
10%
20%
30%
40%
50%
60%
Completely agree Agree somewhat Disagree somewhat Disagree
SME and BI Success 2013 - 2016
2013
2014
2015
2016
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SMEs and State of Data
An organization's opinion of its state of data governance and consistency decreases as
the size of the organization increases (fig. 18). Well more than one-third of closer-knit,
small (1-100 employees) enterprises have the highest view of their governance being at
the level of “data as truth.” More than 40 percent of small and mid-sized organizations
claim "a common view of enterprise data," somewhat ahead of large organizations.
Large organizations are more likely than SMEs to report department-level or multiple
inconsistent data sources.
Figure 19 – Business intelligence and the state of data by organization size
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Small (1 - 100) Mid (101 - 1000) Large (1001+)
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 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 and distrusted
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SME estimations of their "state of data" has dwindled slightly across three years of
study (fig 20). Compared to the linear success at small versus mid-size and larger
organizations (fig. 19), within the SME realm (of both small and mid-sized organizations)
sentiment is less consistent. While "data as truth" held steady in 2015 and 2016, the
common but "parochial" sentiment fell as less coordinated, and "conflicting functional
views" gained a bit. Overall, these sentiments are nonetheless more positive than found
in large (>1,000 employees) organizations.
Figure 20 - SME state of data 2014 to 2016
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Data as "truth" - A common view of enterprisedata 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 departmentallevel. Conflicting, functional views of data
causes confusion and disagreement
We have multiple, inconsistent data sourceswith conflicting semantics and data.
Information is generally unreliable anddistrusted
SME State of Data 2014 - 2016
2014
2015
2016
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SMEs and Action on Insight
Action on Insight is Dresner Advisory’s high-level self-assessment of BI best (and worst)
practices. As we would expect (based on other findings), small (1-100 employees)
organizations to report the most instances of "closed-loop processes” (fig. 21). We also
note that mid-sized organizations report fewer closed-loop processes than either small
or large organizations. Mid-sized organizations report more instances of “ad hoc
informal action” than either small or large organizations. A notable 15 percent of large
organizations (twice as many as small) report uncoordinated/parochial Action on Insight,
undoubtedly attributable to the greater complexities of scale.
Figure 21 – Business intelligence and action on insight by organization size
0% 10% 20% 30% 40% 50% 60% 70%
Insights are rarely leveraged
Uncoordinated/ parochial action (sometimes at theexpense of others)
Ad hoc (informal) action on insights across functions
"Closed loop" - Information is shared, teams work toprocess and act in a timely fashion. No formal
boundaries
Business Intelligence and Action on Insight by Organization Size
Large (1001+) Mid (101 - 1000) Small (1 - 100)
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SMEs’ ability to take Action on Insight improved between 2015 and 2016 (fig. 22). The
top two capabilities ("closed-loop processes," "ad hoc/informal action") both improved
while the remaining lesser capabilities declined. In 2016, fewer than 10 percent of
respondents report "uncoordinated/parochial" action and less than 5 percent say
insights are "rarely leveraged." (For reasons that are not immediately explicable,
negative attitudes toward Action on Insight ebbed noticeably in 2015.)
Figure 22 - SME action on insight 2014 to 2016
0% 10% 20% 30% 40% 50% 60% 70%
Closed loop” processes ensure timely, concerted action
Ad hoc (informal) action on insights acrossfunctions
Uncoordinated/ parochial action (sometimes atthe expense of others)
Insights are rarely leveraged
SME Action on Insight 2014 - 2016
2014
2015
2016
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SME Vendor
Rankings
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Business Intelligence Market Models for SMEs
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. These ratings reflect the opinions of SME organizations, in contrast to
a broader community reflected in our “flagship” 2016 Wisdom of Crowds Business
Intelligence Market Study Report.
Customer Experience Model for SMEs
The customer experience model considers the real-world experience of customers
working with BI products on a daily basis (fig. 23). For the x axis, we included all vendor
touch points—including the sales and acquisition process, technical support, and
consulting services—into a single “sales and service” dimension. On the y axis, we
plotted customer sentiment surrounding product, derived from 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 23 – Vendor rankings based on Customer Experience Model for SMEs
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Vendor Credibility Model for SMEs
The vendor credibility model considers how customers “feel” about their vendor (fig. 24).
The x axis plots perceived value for the price paid. The y axis combines 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 24 - Vendor rankings based on Vendor Credibility Model for SMEs
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SME Business Intelligence Buyers’ Guide
In this section we present a Business Intelligence Buyers’ Guide organized by key
platforms: Traditional, Cloud, and Mobile. For each vendor, we share data collected for
26 different areas of current capability.
An “X” indicates a feature that was available in a vendor’s product during Q1 2016.
Cloud Platform Support – Vendors (B – I)
Feature Birst Dimensional
Insight GoodData IBM Infor Information
Builders
Ability to write to transactional applications X X X X X X
Ad-hoc query X X X X X X
Advanced visualization X X X X X X
Big data support X X X X X
Cognitive computing X
Collaborative support X X X X X
Complex Event Processing (CEP) X X
Custom CSS X X X
Data storytelling X X X
Data integration / data quality tools / ETL X X X X
Data mining and advanced algorithms X X X X X
Data visualization X X X X X X
Embedded BI X X X X X X
End-user "self-service" X X X X X X
End-user data "blending" or "mashups" X X X X X X
In-memory support X X X X X X
Interactive analysis X X X X X X
Location intelligence/analytics X X X X X
Personalized dashboards X X X X X X
Pre-packaged vertical/functional analytical applications X X X X X X
Production reporting X X X X X X
Search-based interface X X X X
Social media analysis (Social BI) X X X X
Streaming data analysis
Text analytics X X X
User/content governance X X X X X
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Cloud Platform Support – Vendors (K – M)
Feature Klipfolio Logi
Analytics Looker Microsoft MicroStr
ategy
Ability to write to transactional applications X X
Ad-hoc query X X X X X
Advanced visualization X X X X X
Big data support X X X X
Cognitive computing X
Collaborative support X X X X
Complex Event Processing (CEP) X X X X
Custom CSS X X X X
Data storytelling X X
Data integration / data quality tools / ETL X X
Data mining and advanced algorithms X X
Data visualization X X X X
Embedded BI X X X X X
End-user "self-service" X X X X X
End-user data "blending" or "mashups" X X X X X
In-memory support X X X X X
Interactive analysis X X X X
Location intelligence/analytics X X X X
Personalized dashboards X X X X X
Pre-packaged vertical/functional analytical applications X X X X
Production reporting X X X X
Search-based interface X X X
Social media analysis (Social BI) X X X X
Streaming data analysis X X X
Text analytics X X X
User/content governance X X X X X
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Cloud Platform Support – Vendors (O – Q)
Feature OpenText Oracle Pentaho Pyramid Analytics Qlik
Ability to write to transactional applications X X X
Ad-hoc query X X X X X
Advanced visualization X X X X X
Big data support X X X X X
Cognitive computing X
Collaborative support X X X X
Complex Event Processing (CEP) X X
Custom CSS X X
Data storytelling X X X X
Data integration / data quality tools / ETL X X X X X
Data mining and advanced algorithms X X X X
Data visualization X X X X X
Embedded BI X X X X X
End-user "self-service" X X X X X
End-user data "blending" or "mashups" X X X X
In-memory support X X X X
Interactive analysis X X X X X
Location intelligence/analytics X X X X
Personalized dashboards X X X X X
Pre-packaged vertical/functional analytical applications X
Production reporting X X X X
Search-based interface X X
Social media analysis (Social BI) X X X X
Streaming data analysis X X X
Text analytics X X X X
User/content governance X X X
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Cloud Platform Support – Vendors (S – Y)
Feature SAP Sisense Tableau TIBCO Yellowfin
Ability to write to transactional applications X
Ad-hoc query X X X X X
Advanced visualization X X X X X
Big data support X X X X X
Cognitive computing
Collaborative support X X X X X
Complex Event Processing (CEP) X
Custom CSS X X X
Data storytelling X X X X
Data integration / data quality tools / ETL X X X X
Data mining and advanced algorithms X X X
Data visualization X X X X X
Embedded BI X X X X X
End-user "self-service" X X X X X
End-user data "blending" or "mashups" X X X X X
In-memory support X X X X X
Interactive analysis X X X X X
Location intelligence/analytics X X X X
Personalized dashboards X X X X X
Pre-packaged vertical/functional analytical applications X X X
Production reporting X X X X X
Search-based interface X X X X
Social media analysis (Social BI) X X X
Streaming data analysis
Text analytics X
User/content governance X X X X
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Mobile Platform Support Vendors (B – I)
Feature Birst Dimensional
Insight Dundas IBM Infor Information
Builders
Ability to write to transactional applications X X X X
Ad-hoc query X X X X X X
Advanced visualization X X X X X
Big data support X X X X
Cognitive computing X
Collaborative support X X X
Complex Event Processing (CEP) X
Custom CSS X X
Data storytelling X X X
Data integration / data quality tools / ETL X
Data mining and advanced algorithms X X X X X
Data visualization X X X X X X
Embedded BI X X X X X
End-user "self-service" X X X X X X
End-user data "blending" or "mashups" X X
In-memory support X X X X X X
Interactive analysis X X X X X X
Location intelligence/analytics X X X X X
Personalized dashboards X X X X X X
Pre-packaged vertical/functional analytical applications X X X X X
Production reporting X X X X X
Search-based interface X X X X X
Social media analysis (Social BI) X X X
Streaming data analysis
Text analytics X
User/content governance X X X X X
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Mobile Platform Support Vendors (K – O)
Feature Klipfolio Logi
Analytics Looker MicroStrategy OpenText Oracle
Ability to write to transactional applications X X X X
Ad-hoc query X X X X X
Advanced visualization X X X X X
Big data support X X X X X
Cognitive computing X
Collaborative support X X X X X
Complex Event Processing (CEP) X X X X
Custom CSS X X X X
Data storytelling X X X X
Data integration / data quality tools / ETL X X X
Data mining and advanced algorithms X X X X
Data visualization X X X X X X
Embedded BI X X X X X
End-user "self-service" X X X X X X
End-user data "blending" or "mashups" X X X X X X
In-memory support X X X X X X
Interactive analysis X X X X X
Location intelligence/analytics X X X X X
Personalized dashboards X X X X X X
Pre-packaged vertical/functional analytical applications X X X X
Production reporting X X X X X
Search-based interface X X X
Social media analysis (Social BI) X X X X X
Streaming data analysis X X X
Text analytics X X X X
User/content governance X X X X X
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Mobile Platform Support Vendors (P – Y)
Feature Pentaho Pyramid Analytics Qlik SAP Sisense Tableau Yellowfin
Ability to write to transactional applications X X
Ad-hoc query X X X X X X
Advanced visualization X X X X X X X
Big data support X X X X X X X
Cognitive computing
Collaborative support X X X X X X
Complex Event Processing (CEP) X X X
Custom CSS X X X X
Data storytelling X X X X X
Data integration / data quality tools / ETL X X X X
Data mining and advanced algorithms X X X X X
Data visualization X X X X X X X
Embedded BI X X X X X X
End-user "self-service" X X X X X X X
End user data "blending" or "mashups" X X X X X X
In-memory support X X X X X X
Interactive analysis X X X X X X X
Location intelligence/analytics X X X X X
Personalized dashboards X X X X X X X
Pre-packaged vertical/functional analytical applications X X X X
Production reporting X X X X X X
Search-based interface X X X X X
Social media analysis (Social BI) X X X X X X
Streaming data analysis X X X
Text analytics X X X
User/content governance X X X X X X X
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Traditional Platform Support Vendors (D – I)
Feature Dimensional
Insight Dundas IBM Infor Information
Builders
Ability to write to transactional applications X X X X
Ad-hoc query X X X X X
Advanced visualization X X X X X
Big data support X X X X
Cognitive computing X
Collaborative support X X X X X
Complex Event Processing (CEP) X X
Custom CSS X X X X
Data storytelling X X X
Data integration / data quality tools / ETL X X X X
Data mining and advanced algorithms X X X X
Data visualization X X X X X
Embedded BI X X X X X
End-user "self-service" X X X X X
End-user data "blending" or "mashups" X X X X X
In-memory support X X X X X
Interactive analysis X X X X X
Location intelligence/analytics X X X X X
Personalized dashboards X X X X X
Pre-packaged vertical/functional analytical applications X X X X
Production reporting X X X X X
Search-based interface X X X X
Social media analysis (Social BI) X X X
Streaming data analysis
Text analytics X X
User/content governance X X X X
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Traditional Platform Support Vendors (L – O)
Feature Logi
Analytics Looker Microsoft MicroStrategy OpenText Oracle
Ability to write to transactional applications X X X X
Ad-hoc query X X X X X X
Advanced visualization X X X X X X
Big data support X X X X X X
Cognitive computing X X
Collaborative support X X X X X
Complex Event Processing (CEP) X X X X X X
Custom CSS X X X X X X
Data storytelling X X X X X
Data integration / data quality tools / ETL X X X X
Data mining and advanced algorithms X X X X
Data visualization X X X X X
Embedded BI X X X X X X
End-user "self-service" X X X X X X
End-user data "blending" or "mashups" X X X X X X
In-memory support X X X X X X
Interactive analysis X X X X X X
Location intelligence/analytics X X X X X X
Personalized dashboards X X X X X X
Pre-packaged vertical/functional analytical applications X X X X X
Production reporting X X X X X X
Search-based interface X X X X
Social media analysis (Social BI) X X X X X X
Streaming data analysis X X X X X
Text analytics X X X X X
User/content governance X X X X X X
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Traditional Platform Support Vendors (P – R)
Feature Pentaho Pyramid Analytics Qlik RapidMiner
Ability to write to transactional applications X X
Ad-hoc query X X X X
Advanced visualization X X X X
Big data support X X X X
Cognitive computing X
Collaborative support X X X
Complex Event Processing (CEP) X
Custom CSS X X X
Data storytelling X X
Data integration / data quality tools / ETL X X X X
Data mining and advanced algorithms X X X X
Data visualization X X X X
Embedded BI X X X X
End-user "self-service" X X X X
End-user data "blending" or "mashups" X X X X
In-memory support X X X X
Interactive analysis X X X
Location intelligence/analytics X X X
Personalized dashboards X X X X
Pre-packaged vertical/functional analytical applications X
Production reporting X X X X
Search-based interface X
Social media analysis (Social BI) X X X X
Streaming data analysis X X
Text analytics X X X
User/content governance X X X X
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Traditional Platform Support Vendors (S – Y)
Feature SAP Sisense Tableau TIBCO Yellowfin
Ability to write to transactional applications X X X
Ad-hoc query X X X X X
Advanced visualization X X X X X
Big data support X X X X X
Cognitive computing
Collaborative support X X X X X
Complex Event Processing (CEP) X X X
Custom CSS X X X X
Data storytelling X X X X
Data integration / data quality tools / ETL X X X X
Data mining and advanced algorithms X X X
Data visualization X X X X X
Embedded BI X X X X X
End-user "self-service" X X X X X
End-user data "blending" or "mashups" X X X X X
In-memory support X X X X X
Interactive analysis X X X X X
Location intelligence/analytics X X X X
Personalized dashboards X X X X X
Pre-packaged vertical/functional analytical applications X X X
Production reporting X X X X X
Search-based interface X X X X
Social media analysis (Social BI) X X X
Streaming data analysis X X
Text analytics X X
User/content governance X X X X X
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Other Dresner Advisory Services Research Reports
- “Flagship” Wisdom of Crowds Business Intelligence Market Study
- 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
- “Flagship” Wisdom of Crowds Enterprise Planning market Study
- Internet of Things and Business Intelligence
- Location Intelligence
- Mobile Computing and Business Intelligence
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53
Appendix - The 2016 Wisdom of Crowds® Business Intelligence Market
Survey Instrument
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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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 ( ) ( ) ( ) ( ) ( )
Research and ( ) ( ) ( ) ( ) ( )
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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
operational
( ) ( ) ( ) ( ) ( )
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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
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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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 ( ) ( ) ( ) ( ) ( )
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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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 ( ) ( ) ( ) ( ) ( )
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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Search-based
interface
( ) ( ) ( ) ( ) ( )
Social media
analysis (Social BI)
( ) ( ) ( ) ( ) ( )
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
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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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
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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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 ( ) ( ) ( ) ( ) ( ) ( )
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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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 ( ) ( ) ( ) ( ) ( ) ( )
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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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
( ) ( ) ( ) ( ) ( ) ( )
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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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
2016 Small and Mid-Sized Enterprise Business Intelligence Market Study
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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
____________________________________________