How Digital Business is Shaping the Next Wave of Automation

IT & DATA MANAGEMENT RESEARCH,
INDUSTRY ANALYSIS & CONSULTING
Dan Twing
President and COO
EMA
How Digital Business is Shaping
the Next Wave of Automation
Tim Eusterman
Senior Director Solutions Marketing
BMC

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Today’s Presenters
Slide 3 © 2017 Enterprise Management Associates, Inc.
Dan Twing, President and COO, EMA
Dan is responsible for developing and executing strategic market research,
delivering value to IT organizations through consulting engagements, and
directing product developments and marketing efforts. Dan joined EMA in 2005
and has over 25 years of experience in information systems, software
development, and technology outsourcing. Dan focuses on all aspects of
intelligent and automated management of IT.
Tim Eusterman, Senior Director Solutions Marketing, BMC
Tim’s career spans over 25 years of B2B high tech marketing in the supply
chain and enterprise mobile computing industries. In his current position, he
leads the development and execution of the market strategy, BU and product
positioning, demand and content marketing, and sales enablement for the
Digital Business Automation business unit and Control-M product line.

Logistics for Today’s Webinar
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Dan Twing
President and COO
EMA
How Digital Business is Shaping
the Next Wave of Automation

Expectations of IT have never been higher
© 2017 Enterprise Management Associates, Inc.
Consumerization of IT
High Speed Innovation
Continuous Delivery
Anywhere Any/Time Access
IoT/ Everything Connected
Big Data/Predictive Analytics

IT Needs To Be Nimble and Flexible
Workload Mobility
Elastic Infrastructure
DevOps
Big Data
Shadow IT

To Survive Businesses Must Go Digital & IT Must
Transform To Deliver On Digital Transformation
Digital
Transformation
An initiative designed to
optimize business or
organizational effectiveness
via digital and IT services.

To Survive Businesses Must Go Digital & IT Must
Transform To Deliver On Digital Transformation
IT
Transformation
optimize IT performance for
business or organizational
needs and outcomes
Digital
Transformation
optimize business or
organizational effectiveness
via digital and IT services.

IT Transformation & Digital Transformation Interconnected
22%
23%
19%
24%
12%
27%
24%
14%
23%
12%
0% 5% 10% 15% 20% 25% 30%
IT is driving it all
We are primarily driven from within IT, but business stakeholders are actively
involved
We are even partners in our digital/IT transformation efforts, 50/50
Significantly-our business (organization) is more than 50% partner in our
transformaiton efforts
Critically, we are primarily driven by stakeholders outside of IT
IT Transformation Digital Transformation
To what degree are your digital or IT transformation initiatives driven by
stakeholders outside of IT?

Digital Transformation Requires…
Predictive Analytics
&
Visualization
IT Automation
Integrated Tools
Do The Old Things Better

Digital Transformation Requires…
Embrace Speed
Find A Way To Say Yes
Predictive Analytics
&
Visualization
IT Automation Bring A Digital Vision
Integrated Tools
Do The Old Things Better Bring A New Mindset

Digital
Business
Automation
Diverse
Infrastructure
Accelerated Applications
Disparate
Data
THREE CHALLENGES OF DIGITAL BUSINESS AUTOMATION

Most Organizations Are Using A Mix Of Environments
Which of the following is your company using to deliver a production
application?
Sample Size = 164, Valid Cases = 164
Slide 15
30%
38%
21%
62%
54%
49%
39%
41%
41%
50%
50%
62%
0% 10% 20% 30% 40% 50% 60% 70%
Platform as a Service (PaaS)
Infrastructure as a Service (IaaS)
Outsourcer
Company-owned data center
Software as a Service (SaaS)
Private Cloud
2017 2015

Workflows are fairly evenly placed across environments
Where are job workflows hosted?
Sample Size = 228, Valid Cases = 228, Total Mentions = 335
101
67 77 67
23
82
55
79
66
29
87
58
73
53
30
96
61
91
79
19
77
68
68
52
42
0
50
100
150
200
250
300
350
400
450
500
Production Staging Dev/Test Disaster Recovery None
Mainframe Distributed Physical Distributed Virtual Private Cloud Public Cloud

IT Directors are most often deciding where workloads are
placed
Who decides where a specific job workflow must be hosted (physical, virtual,
private cloud, or public cloud)?
43%
27%
9%
7%
6%
6%
1%
0% 10% 20% 30% 40% 50%
IT Director
CIO
VP of Infrastructure
Business owner
Infrastructure administrator
Workload designer
Workload Operator
Column %
Sample Size = 228

Performance and Security concerns rank highest in
determining where workloads are placed
How does your organization determine whether a new workload needs to be
placed in a physical, virtual, private cloud or public cloud environment?
64%
60%
50%
45%
31%
0% 10% 20% 30% 40% 50% 60% 70%
Performance
Security
Cost
Technical ability to deploy workload
Licensing
% Valid Cases (Mentions / Valid Cases)

Users Want Anywhere / Any Device Access
Multi-device adoption by enterprise workers
Laptop or Desktop PC Only
11%
Movile Device Only
2%
Smartphone & PC
49%
Tablet & PC
3%
Smartphone, Tablet & PC
35%
Slide 19

BYOD Adds To Diversity
© 2017 Enterprise Management Associates, Inc.Slide 20
8%
9%
4%
43%
42%
71%
49%
49%
25%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Smartphone
Tablet
PC
Purchased by user Supplied by employer Partly financed by employer
Who is purchasing enterprise devices?

DIVERSE INFRASTRUCTURE: CUSTOMER SUCCESS
Impact of Control-M:
Delivers ‘ZERO DAY’ global malware
threat detection and remediation
 Over 1.7 trillion data records ingested per day
 Process 1% signal out of 99% noise from millions
of data end points
 Provides real-time geo spatial mapping of global
malware threats to visualize, analyze, prioritize
propagation trends for Zero Day remediation
 Least cost model 100% delivered on AWS
“In the modern enterprise, cloud infrastructure has
allowed us to scale elastically and manage compute
costs by workload hour. Control-M is enabling
Malwarebytes to manage cloud infrastructure, Hadoop
applications, ETL jobs, and dashboard refreshes in a
way that takes advantage of the cloud billing model.”
Darren Chinen, Sr. Director,
Data Science and Engineering, Malwarebytes

Big Data on the rise
The number of organizations doing Big Data and the number of Big
Data projects within each organization are increasing.
Slide 23
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
Big Data Projects Stage
By Year
Investigating Serious Planning In Operation
2012 2013 2014 2016
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
1 2 3 4 5+ 1 2 3 4 5+ 1 2 3 4 5+
Number of Big Data Projects
By Year
2013 2014 2016

Originally Planned Information Architecture
System
System
System System
System
System ODS DWH
Cube
DM
DM
AnalyticalTransactional

A Realistic View

61%
53%
41%
4%
0% 10% 20% 30% 40% 50% 60% 70%
Increases resource requirements
Increases complexity
Increases difficulty of SLA management
None of the above
What has been the impact of Big Data projects on WLA?
Big Data increases resource requirements and complexity
Makes SLA management more difficult

Hybrid Data Ecosystem

Maturing Big Data Implementations are adding to Data Diversity
Workloads
• Nearly 70% of respondents are adopting strategies to implement
complex workloads.
• Over 40% of big data projects are implementing complex workloads
such as advanced analytics and data science.
• The top rated complex workload for big data initiatives is graph
analysis for behavioral and relationship analysis.

Workloads
• Nearly 70% of respondents are adopting strategies to implement
complex workloads.
• Over 40% of big data projects are implementing complex workloads
such as advanced analytics and data science.
• The top rated complex workload for big data initiatives is graph
analysis for behavioral and relationship analysis.
Response
• What Does Real-time Mean? 35%-Immediately 60% by end of
business day.
• 3 of 4 big data projects have an intra-day processing latency
requirement.
• Top business driver is faster response time for operational and
analytical workloads.
• Top real-time processing strategy driver is integrating machine –
generated data into optimization models.

Data Load
• Large big data environments (>10 PB) are expected to grow in 2017.
• Smaller big data environments (<250 TB) are declining.
• Better is Bigger – Robust scored organizations are 6x more likely to
have big data environment sizes over 250TB (69.2%) than those in
the Struggling and Ineffective categories (11.7%).

Structure
• 6 of 10 big data projects use multi-structured data like JSON, XML,
and API provided datasets.
• 17% increase in use of event data from 2014 to 2016.
• A top 3 challenge is accessing internal and external multi-structured
data sets.
Data Load

Structure
• 6 of 10 big data projects use multi-structured data like JSON, XML,
and API provided datasets.
• 17% increase in use of event data from 2014 to 2016.
• A top 3 challenge is accessing internal and external multi-structured
data sets.
Data Load
Economics
• Most common financial driver - reduce operational labor expenses for
data management configuration and operations.
• 10% decline in concern for capital expenditures for data management
hardware from 2014 to 2016.
• Struggling and Ineffective organizations are more concerned with labor
costs.

WLA tools have become better at integrating big data, analytics and BI
tools since 2013
50%
47%
46%
44%
55%
49%
45%
64%
0% 10% 20% 30% 40% 50% 60%
Central dashboard showing data quantities and flows across the
process
Adapters and connectors for more business applications
Ability to ingest meta data
Deeper integration with Big Data, analytics and BI tools
2016 2013
What additional Big Data-related WLA capabilities would be beneficial?

Job Scheduling continues to be one of the top three Big Data challenges
What are the Big Data-related challenges you face?
53%
53%
40%
36%
0% 10% 20% 30% 40% 50% 60%
Managing large data lakes
Integration with Big Data tools
Integration with other automation tools (e.g. job scheduling)
Insufficient compute power

DISPARATE DATA: CUSTOMER SUCCESS
35
Navistar’s OnCommand™ service
reduces vehicle downtime by 40%
 Reduced unplanned repairs by up to 30%
 Actionable IOT data sets delivered 5x faster
 20M+ data records/day collected and transformed
from more than 250,000 trucks
 20% improved time savings for Hadoop engineers
“We’ve just begun to tap the power of
Control-M to help us use big data to enhance
remote diagnostics, improve vehicle quality,
and protect critical resources from unauthorized
access, among other initiatives.”

IT Runs a Myriad of Applications for Many Environments
Which of the following types of applications is your company currently delivering
as a production service?
63%
51%
50%
48%
45%
39%
32%
24%
20%
17%
0% 10% 20% 30% 40% 50% 60% 70%
Custom
Commerical, packaged enterprise applications (such as ERP/CRM products)
Employee-facing web applications
Customer-facing web applications
Packaged applications with custom modifications
Web-based applications optimized for mobile
Mainframe as a "back end" system of record for "front end" systems of engagement
Stand alone mainframe applications
Native mobile
Mobile applications interacting with a mainframe
Sample Size = 201
Slide 37

Accelerated Applications – Frequency is increasing at an increasing rate.
4%
1%
3%
32%
18%
15%
19%
5%
2%
1% 1%
16%
17%
24%
18%
12%
10%
0%
5%
10%
15%
20%
25%
30%
35%
Don’t know 75%+ 50%- 75% 25% - 50% 10% - 25% <10% Same <10% 10% - 25% 25% - 50% 50%- 75% 75%+
INCREASEDDECREASED
2015 2017
How does your organization's frequency of code delivery today compare to that of 12 months ago?
Sample Size = 164

Accelerated Applications – Frequency is increasing at an increasing rate.
4%
1%
3%
32%
18%
15%
19%
5%
2%
1% 1%
16%
17%
24%
18%
12%
10%
0%
5%
10%
15%
20%
25%
30%
35%
Don’t know 75%+ 50%- 75% 25% - 50% 10% - 25% <10% Same <10% 10% - 25% 25% - 50% 50%- 75% 75%+
INCREASEDDECREASED
2015 2017
2015 – 59% Going faster than 1 year ago.
2017 – 81% Going faster than 1 year ago.
How does your organization's frequency of code delivery today compare to that of 12 months ago?
Sample Size = 164

More Frequent Code Deployment Adds To Complexity
As a rule, how frequently does your organization deploy new code to production?
Sample Size = 365
Slide 40
4%
11%
16%
15%
23%
16%
15%
6%
4%
10%
13%
24%
19%
23%
0%
5%
10%
15%
20%
25%
30%
< Monthly Monthly Multiple/month Weekly Multiple/week Daily Multiple/day
2015 2017

More Frequent Code Deployment Adds To Complexity
As a rule, how frequently does your organization deploy new code to production?
Sample Size = 365
Slide 41
4%
11%
16%
15%
23%
16%
15%
6%
4%
10%
13%
24%
19%
23%
0%
5%
10%
15%
20%
25%
30%
< Monthly Monthly Multiple/month Weekly Multiple/week Daily Multiple/day
2015 2017
2015 31%
2017 42%
Daily or Multiple Times Per Day

Faster Rate of Change Can Bring More Breakage Along With Better
Application Performance and Quality
How has this increase impacted production environments?
Slide 42
37%
33%
31%
30%
23%
23%
22%
18%
18%
17%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Application performance and/or availability have improved
Development is drawn into production troubleshooting more often
Operations is spending more time on production troubleshooting
Positive impact on quality of applications going into production
Minimal production impact
Executive complaints have increased
We are experiencing a higher number of performance and/or availability
problems
Service levels have degraded as rates of change increased
Customer complaints have increased
Project wait times have increased
Positive Outcomes Negative Outcomes

ACCELERATED APPLICATIONS: CUSTOMER SUCCESS
GLOBAL TOP-15 RETAILER
• 3 hours to 3 seconds - time to make job
changes and deploy from Jenkins
• 140 to 450 - stores able to do holiday
digital order fulfillment
• 42% increase - digital sales during holiday
period from prior year
“It used to take me hours to change a job’s
name or in/out conditions. But in JSON we can
do a ‘replace all’, apply it to all the jobs and it’s
now a simple change down to a few seconds.”
Self Service
Jobs-as-Code
“With this API, not having to know anything
about Control-M and never having to go into
the Control-M tool, I can deploy my job from
Jenkins to Control-M in seconds.”
Problem: Faulty automation leads to
rework in release-to-deploy phase
Resolution: Incorporate Control-M
into existing CI / CD pipeline
DevOps Developer
DevOps Developer

How Digital Business is Shaping the Next Wave of Automation

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