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Data Analytics, Algorithms & Machine Learning
ONLINE SURVEY
2
Table of ContentsIntroduction & Methodology 3
Key Findings
Current Status with Regard to Leveraging Data Analytics 9
Satisfaction with Specific Data Analytics Functions 10
Leveraging Predictive Analytics 11
Potential for Machine Learning to Enhance Data Analytics 12
Automation in Predictive Analytics & Competitive Advantage 13
Leveraging Automated Predictive Analytics 14
Leveraging Automated Machine Learning 15
Deterrents to Leveraging Machine Learning in Production 16
Companies Associated with Machine Learning Solutions 17
Resources for Implementing Machine Learning in Production 18
Respondent Profile
Primary Industry 5
Number of Employees 6
Current Job Function 7
About Informa Engage
3
Introduction & Methodology
OVERVIEW
Methodology, data collection and analysis by Informa Engage, on behalf of Dell.
Data collected March 8, through March 26, 2018.
Methodology conforms to accepted marketing research methods, practices and procedures.
PRIMARY OBJECTIVES
Investigate various issues around the current and future use of use of analytics, predictive analytics and machine learning, including:
Satisfaction with data analytics activities
Key benefits and deterrents associated with the use of machine learning
Companies associated with machine learning
METHODOLOGY
On March 8, 2018, IT Pro Today emailed invitations to participate in an online survey to a net 118,083 subscribers.
By March 26, 2018, Informa Engage had received 315 completed surveys, for an overall response rate of 0.3%.
RESPONSIVE MOTIVATION
To encourage prompt response and increase the response rate overall, a live link to the survey was included in the email invitation to route respondents directly to the online survey.
The invitations and survey were branded with the IT Pro Today name and logo, in an effort to capitalize on user affinity for this valued brand.
Each respondent was afforded the opportunity to enter a drawing for one of four $100 Amazon gift cards.
Follow-up emails were sent to non-respondents.
4
Respondent Profile
5
Primary Industry
Question: Which of the following best reflects your organization's primary industry?
Base: All respondents (n=315).4%
1%
1%
1%
1%
1%
1%
1%
1%
2%
2%
2%
2%
3%
3%
3%
6%
6%
6%
7%
8%
12%
12%
13%
Other
Restaurant & Hospitality
Real Estate, Rental and Leasing
Food/Beverage
Energy/Power
Data Center Services
Construction
Aviation
Agriculture
Wholesaler/Distributor
Transportation
Retail Trade
Engineering
Telecommunications
Non-Profit
Media & Entertainment
Healthcare/Pharmaceutical
Finance/Banking/Investment
Consulting/Professional Services
Government
Manufacturing
Information Technology
Education
IT Services
A variety of industry types are represented in the sample, most commonly IT Services, Education and Information Technology.
6
Number of Employees
Question: How many people are employed by your organization (at all locations)?
Base: All respondents (n=315).
17%
31%
8%
18%
7%9%
11%
Fewer than 100 100 - 249 250 - 499 500 - 999 1,000 - 4,999 5,000 - 9,999 10,000 or more
Organizations of all sizes are represented in the sample: 17% from small organizations (<100 employees); 57% from mid-sized (100-999
employees); and 27% from enterprise (1,000+ employees).
7
Current Job Function
Question: Which one of the following best reflects your current job function?
Base: All respondents (n=315).
11%
4%
8%
9%
9%
10%
16%
17%
Other IT Function
Database Administration
Engineering
DevOps/Development/Applications
Consultant/Systems Integrator
CIO/CTO
IT Architect
Networking/Messaging/Systems
The majority of respondents hold IT job functions (84%), most commonly Networking/Messaging/Systems and IT Architects.
IT Job Function (NET 84%)
<1%
<1%
1%
2%
2%
5%
6%
Purchasing/Procurement
CFO/COO
Marketing
Sales
Operations
Other Business/Corporate Function
CEO/President/Owner
Business Job Function (NET 16%)
8
Key Findings
9
Current Status with Regard to Leveraging Data Analytics
10%
12%
11%
13%
26%
26%
28%
33%
11%
12%
15%
11%
19%
18%
16%
18%
35%
33%
31%
26%
Employing algorithms
Automated action triggered by algorithms
Predictive analytics
Big data/analytics
Using extensively Using in some areas Testing Considering Not using
Question: What is your organization's current status with regard to the following?
Base: All respondents (n=315).
Respondent organizations are most likely to be using big data/analytics (46%), followed by predictive analytics (39%), employing algorithms
(36%) and automated action triggered by algorithms (38%). An additional 28%-30% of respondents report their organizations are either testing
or considering each activity.
10
Satisfaction with Specific Data Analytics Functions
13%
13%
15%
17%
27%
30%
33%
37%
55%
51%
46%
39%
4%
7%
4%
7%
Big data/analytics
Employing algorithms
Predictive analytics
Automated action triggered by algorithms
Extremely satisfied Very Satisfied Moderately satisfied Not very satisfied Not at all satisfied
Question: How satisfied are you with your organization’s use of…?
Bases vary: Respondents currently using respective function; Big data analytics (n=135); Predictive analytics (n=117); Employing algorithms (n=104); Automated action triggered by algorithms (n=111).
Respondents expressed the highest satisfaction with the most advanced functionality: automated action triggered by algorithms (54% are
“extremely” or “very satisfied”), followed by predictive analytics (48%). Interestingly, big data/analytics is associated with relatively lower levels
of satisfaction, which may be driven in part by a lack of clarity around how to most effectively utilize that data.
11
Leveraging Predictive Analytics
Question: How is your organization leveraging predictive analytics?
Base: Respondents currently using predictive analytics; multiple answers permitted (n=117).
Those respondents whose organizations are currently using predictive analytics are most likely to leverage it for risk assessment (56%) and/or
cyber security (48%), followed by fraud prevention (39%) and/or supply and demand planning (34%).
5%
16%
24%
26%
34%
39%
48%
56%
Other
Facial recognition
Manufacturing optimization
Predictive buying behavior
Supply and demand planning
Fraud prevention
Cyber security
Risk assessment
Other responses:
All flavors of servers Support
Applying it mainly to our customer's datasets
Corrections communication
Developing a custom solution
Problem Detection and suggesting solution option
Process improvement
12
Potential for Machine Learning to Enhance Data Analytics
Question: Could your company improve its data analytics program with machine learning?
Base: Respondents currently using data analytics (n=252).
A majority of those respondents currently leveraging data analytics (55%) believe those programs would benefit from machine learning.
An additional third think machine learning could possibly enhance their use of data analytics.
22%
33%
37%
6%
2%
Definitely Probably Possibly Probably not No
13
Automation in Predictive Analytics & Competitive Advantage
Question: Do you think automation in predictive analytics will be a key differentiator for companies to stay competitive in the future?
Base: Respondents currently using data analytics (n=252).
A clear majority of those respondents currently leveraging data analytics (68%) believe automation in predictive analytics will be a key
differentiator for companies in terms of staying competitive in the future.
32%
36%
28%
4%1%
Definitely Probably Possibly Probably not No
14
Leveraging Automated Predictive Analytics
Question: How is your organization leveraging predictive analytics?
Base: Respondents currently using some form of data analytics; multiple answers permitted (n=247).
The majority of those respondents whose companies are currently using some form of data analytics (76%) are also leveraging automated
predictive analytics. The most common application is detection of security breaches/threats (41%), followed by customer service (35%)
and/or sales/revenue forecasting (35%).
24%
6%
35%
35%
41%
N/A; We are not currently leveragingautomated predictive analytics.
Other
Sales/revenue forecasting
Customer service
Security breaches/threats
Other responses:
Applying it mainly to our customer's datasets
Azure & windows
Being provided to partners
Claims analysis
Customer experience for network testing
Ordering levels of titles
Product Health Monitoring
Workforce planning
15
Leveraging Machine Learning
Question: Is your organization currently leveraging machine learning in production?
Base: Respondents currently using some form of data analytics (n=247).
Only 18% of those using some form of data analytics are currently leveraging machine learning. Another 55% are either considering
implementing, or researching machine learning.
Question: What are the primary benefits of leveraging machine learning in production?
Base: Respondents currently leveraging machine learning; multiple answers permitted (n=45).
Primary Benefits of Machine LearningMachine Learning Utilization
18%
23%
32%28%
Yes No, but we areconsidering doingso within the next
18 months.
No, but weare currently
researching it.
No, and we haveno immediateplans to do so. 2%
56%
63%
67%
72%
Other
Revenue increase
Change the way our customersengage with the business
Innovate faster and findnew market opportunities
Automate repetitive processes and tasksthat currently require human involvement
16
Deterrents to Leveraging Machine Learning in Production
Question: What are the deterrents to leveraging machine learning in production?
Base: Respondents not currently leveraging machine learning; multiple answers permitted (n=197).
Those top two deterrents to leveraging machine learning in production are lack of skills, talent and understanding (47%) and lack of budget
for implementation (44%).
16%
5%
22%
26%
27%
44%
47%
N/A; There are no deterrents at my organization.
Previous investments have failed
Still think technology is unproven
Lack of executive buy-in
Complications around policies, regulations, and rights
Lack of budget for implementation
Lack of skills, talent and understanding
17
Companies Associated with Machine Learning Solutions
Question: Which companies do you most associate with machine learning solutions?
Base: Respondents currently using data analytics (n=252).
Respondents are most likely to associate Google and IBM with machine learning solutions, followed by Dell EMC and Salesforce.
65%60%
23%19%
10% 11% 10%
Google IBM Dell EMC Salesforce NVIDIA Other None of theabove
Other responses:
Amazon (4 mentions)
AMD
And few others
Deep Instinct
Fixture testing
Fortinet
HP
Intel
LogRythm
Microsoft (8 mentions)
Oracle
Palo Alto
Samsung
Still not selected
18
Resources for Implementing Machine Learning in Production
Question: What resources do you, or will you use to implement machine learning in production?
Base: Respondents using or considering machine learning; multiple answers permitted (n=235).
Respondents using or considering machine learning are most likely to rely on internal staff for implementation. Approximately half rely on
software vendors with consulting services, and 40% rely on software providers.
3%
27%
40%
48%
61%
Don't know
Dedicated AI consulting firm(s)
Software providers
Software vendors with consulting services
Internal staff
19
About InformaEngage
20
Informa Engage is the marketing services powerhouse behind Informa’s trusted brands. We provide B2B
marketers with unrivaled specialist audiences, deep knowledge of vertical markets, sophisticated data and
content marketing expertise. Through our deep understanding of our customer’s behaviors and changing
needs, Informa Engage connects marketers to customers as they move from discovering a problem to
identifying features and functionality of a solution to selecting a provider and making a purchase.
Connect at informaengage.com
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21
Meet Our Research Team
Kristin Letourneau, PhD
Research Director
kristin.letourneau@informa.com
(913) 967-1892
Scott Grau, MS
Senior Research Manager
scott.grau@informa.com
(952) 851-4650
Jennifer Sigwart, MBA
Data Analyst
jennifer.sigwart@informa.com
(410) 935-5023
Elinor Delagrange, MBA
Senior Research Manager
elinor.delagrange@informa.com
(770) 693-2064
22
Thank you!Kristin Letourneau, PhD Director, Market Research
Informa EngageOverland Park, KS, USA(913) 967-1892
kristin.letourneau@informa.com engage.informa.com
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