In medicine - an MRI can quickly reveal a hidden ailment and actionable insight to get better. For IT and business leaders whose key concern with the mainframe is the platform costs and lean operations - the CA Mainframe Resource Intelligene reveals multiple sources of hidden mainframe costs and operational inefficiencies along with actionable recommendations. This is the only offering in the market that combines economic consulting services with proprietary utilities and automation technologies. View this SlideShare to understand the solution – how services, best practices and mainframe expertise of 40+ years from CA comes together to solve the CIO and CFO’s biggest challenge. Call your account director or mainframe specialist.: https://www.ca.com/us/contact/mainframe-economic-consultant.html

1. Mainframe
Resource
Intelligence
by CA Technologies

2. CIO desired outcomes:
Cost Imperative: Must Save Now to Invest in the Modernization Journey
2
What are the barriers to
building a modern software
factory including Mainframe to
build and deliver mission critical
services at the same speed as
my cloud services?
What is the state of my
systems and skills to provide
99.999 availability and
redundancy?
How can I build
Digital Trust to enable
us to be a Digital
Enterprise?
How secure is our data and
how compliant are we with
GDPR and other regulations?
What resources can I free up to
self-fund digital initiatives?
Economics

3. 3
Economics
PROCESS MRI
AGILITY/SPEED
TOOLCHAIN
ECONOMICS MRI
CAPACITY COST
SOFTWARE COSTS
LABOR COSTS
SYSTEMS MRI
SLA’S
SKILLS
AUTOMATION
Start with Mainframe Resource Intelligence (MRI) to
assess your current state in the modern software factory
Economics
SECURITY MRI
PRIVACY
ACCESS

4. 4
Apply Best Practices with Mainframe Resource Intelligence
Optimization to Modernization
AI DRIVEN SELF DRIVING DATACENTER
AGILE DEVOPS
TOOLCHAIN
ECONOMICS MRI
DATA & USER CENTRIC
SECURITY
OPTIMIZE PLATFORM
PROCESS MRI SECURITY MRISYSTEMS MRI
• Dynamically
manage capacity
• Leverage Specialty
Engine and Java
• Software
Standardization
• Modern UX and
Visual analytics
• Leverage
experts to train
AI/ML
algorithms
• Augment people
with machine
Intelligence
• Automatic
remediation to
create self driving
datacenter
• Adopt open modern
tools familiar to
next gen
developers
• Automate to shift
“ops” left to enable
continuous delivery
• Provide everything
as a service
• Discover and
protect sensitive
data
• Implement multi-
factor
authentication
• Reduce risk by
Trusted user
management

5. An Economic MRI is the first step
Seems Simple but it’s not..
5
How can you
simplify what
you have..
..and
continuously
Iterate and
Optimize to
reduce both
CAPEX and
OPEX?
FTE
CAPACITY
CURRENT DESIRED
SOFTWARE
TOOLS
ECONOMICS MRI

6. Mainframe Economics Challenge
Predicting Capacity
6
~ 35% of Mainframe Spend
Situation
• Capacity spikes
• Missed SLAs
• Over-provisioning
• Modest but periodic MLC price
increases add up $$$MMs
ECONOMICS MRI

7. Mainframe Economics Concern
Skills
~ 25% of spend
Situation
• Retiring specialists leading to skill gaps
• Tools under-utilization
• Higher probability of outage or degradation
• Inadvertent redundant purchases
• Lack of awareness of upgrades and
specialty engine exploitation
Source:https://diginomica.com/2017/07/20/mainframe-still-matters-skills-crisis-attached/
7
ECONOMICS MRI

8. Vendor 1
• Xxxxx
• Xxxxx
• xxxxx
Vendor 2
• Xxxxx
• Xxxxx
• xxxxx
Vendor 3
• Xxxxx
• Xxxxx
• xxxxx
Mainframe Economics Concern –
Tool Proliferation
8
~40% of Mainframe spend
Situation
• Redundant Capabilities
• Higher vendor management burden
• Higher maintenance cost
• Different skills to maintain for different tools
• Need to modernize – same toolset across
mainframe and rest of your datacenter
ECONOMICS MRI

9. 9
Solution? Here are the Best Practices to Optimize
the platform
o Optimize capacity
o Leverage Specialty
Engines and Java
o Pursue software
standardization
ECONOMICS MRI

10. Don’t panic
Let’s delight
your CFO
With an economics MRI
that exposes hidden
opportunities to save and
invest wisely

11. 3 Ways to Optimize and Reduce Costs
11
Deploy tools to the fullest
with feature & zIIP
exploitation, upgrade
analysis, best practices
and configuration
consultation
Perform capping analysis
and select the right
workload candidates for
tuning, shifting and load
balancing to save MLC
Discover redundant
capabilities and
systematically analyze
consolidation and
modernization to reduce
license and skills costs
Optimize Capacity
Leverage specialty
processors and Java
Standardize Software
ECONOMICS MRI

12. 12
A Economics MRI from CA
based on
Across 500+
Engagements
12
• 8-10% baseline savings against total MLC
• Up to $200K savings per LPAR
• 55% - 65% offload of workload to specialty processors
saves MLC
• 24% tool reduction due to removal of redundancy
• Same development tools for distributed and Mainframe
• Lower FTE costs due to common skills
Optimize Capacity
Standardize Software
Leverage Specialty Engines & Java
ECONOMICS MRI

13. Economics MRI Engagement Model
Services, Best Practices & Technology Combined for Predictable Delivery
13
Discovery and Data
Collection
Cost analytics using
proprietary utilities and data
automation
CA delivers findings Client decision
Portfolio data DNA
Scenarios of potential cost
savings
implement findings
SMF 70, 72 X-Ray Ease vs. impact analysis
Use of CA services &
onversion utilities
Product inventory
In-built health-checks and
metrics
Estimation of customer effort
Adopt new capabilities to
realize business case goals.
Business case objectives
ANALYZE ASSESS RECOMMEND FOLLOW
2 weeks! Fast recommendation powered by analytics and automation

14. Economics MRI Engagement Model
Automation and utilities minimizes your effort
14
• Tailor your own engagement: Pick one one, 2 or all three reviews
• Least disruption to your team – CA services professionals guide the way.
ANALYZE
CA tools with Customer provided data Customer Level of Effort
Optimize
capacity
“X-Ray” or Dynamic Capacity analyzer runs a
90-Day extract of SMF 70, 72
Low to moderate
Leverage
specialty
engines
Best practices and product health-checks with
metrics & usage data
Moderate
Standardize
software
DNA automated discovery of customer installed
portfolio
Low
APPROACH

15. Your peers
are doing this..

16. 16
Automated Capacity Mgmt.: Depicts all LPAR usage, but most expensive LPAR had the highest usage
Optimize Capacity

17. 17
Optimize Capacity: Identify peak usage
Automated Capacity Mgmt.: Easily view peak real-time rolling four-hour (R4HA), Caps and MLC

18. 18
Optimize Capacity – Pricing scenarios
Pricing Optimization View: Show scenarios of
Advanced Workload License Chart usage vs. Country Multiplex Pricing

19. Optimize Capacity
Recommendations include
 Peak usage vs. Peak cost LPARs
 Optimal Pricing model (e.g. CMP)
 Time shifting – moving batches to night
 White-space usage potential
 Risk scenarios
ECONOMICS MRI

20. CA’s Dynamic Capacity
Intelligence is a win –win for
us. It provides automated
and predictable capacity
management so we can
optimize system resources
to the most critical business
needs
CHALLENGE:
Needed to monitor thresholds that were relevant for pricing predictions in real-time.
Take timely and appropriate actions against unplanned peaks in usage and costs
to maximize ROI.
German Insurance Company
German insurance giant needed to reduce cost in their data center
20
10% software
cost reduction
Across
mainframe
operations
Reduced
manpower
involved in
capacity
management
Prioritized
MSU
capacity
based on
workload
priorities
across LPAR
The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous.
“

21. 21
Leverage specialty engines and Linux
 Assessment of products and
capabilities to leverage
specialty processors
 Cost avoidance or MIPs
savings estimations
 Product best practices
 Configuration
 Tuning
 Installation and upgrade
guidance

22. CHALLENGE:
Reduce Mainframe HW and SW licensing cost while maintaining “5 9’s of
availability. Key delivery applications run on CA’s highly resilient CA Datacom
database technologies.
DHL
Is a global logistics company specializing in packaging, courier and express
delivery with a network of operations spanning 220 countries and territories.
22
CA provides mobile-to-
mainframe visibility and
machine learning
intelligence for a better
customer experience
55% of
workloads
offloaded to
specialty
engines
Higher
throughput at
reduced
licensing fees
Lower TCO
The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous.
“

23. Standardize Software
23
COMPLEXITY OF STANDARDIZATION
VALUEPOTENTIAL
REPORTING: ANNUALIZED SAVINGS

24. CA’s approach is way
ahead of other
intelligence engines
which aren’t real time
CHALLENGE:
Multiple tools, multiple vendors in their mainframe environment built over years
resulted in redundant capabilities, costly shelf-ware costs as well as unnecessary
licenses & maintenance costs
Leading Insurance Company
An insurance giant serving 90% of the Fortune Global 500 needed to leverage
their valuable mainframe data and support a variety of new business initiatives
24
45% product
reduction
14% vendor
reduction
50% Software
License cost
savings
Conversion
duration:
4 months
from start to
production
The company in this case study has policies against publicly endorsing vendors and prefers to remain anonymous.
“

25.  Tell your CA Account Director
 Tell us about your concerns and overall
business challenge
CONTACT US!
 Provide a list of your vendors, tools, & current
capacity status
 Jointly determine the type of review for maximum
near term benefit
PARTNERING FOR SUCCESS
 Get your saving assessment from CA
 Determine next steps for implementation
 Feel confident that CA’s there for you
today and tomorrow
CELEBRATE