Analytics: The Next Killer App for Optimizing IT? #GartnerIOM

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Analytics: The Next Killer App for
Optimizing IT?
David Wagner, Director Market Development
david.wagner@teamquest.com

• Déjà vu all over again…
• Analytics and today’s optimization challenges
• What REALLY matters
• Desired state and results
• Methodology and ideation examples
– Business and service aligned
– Automated and predictive IT analytics
• Recommendations
Presentation Agenda

• Long-wave cycles, repeating… endlessly?
– Mainframes to minicomputers to PCs
– Server commoditization
– Virtualization and abstraction technologies (Cloud, SDDC, etc.)
• Killer apps drove mega-adoption rates
– PCs are great, then came Excel
– Client-server and commodity servers, but… “Can you say www?”
– Virtualization (again)… ah yes, consolidation
• Every time around…
– Rapid adoption = Optimization challenges
Play it again, Sam…

Cloud, Virtualization, SDDC ->
Changing Demands on IT
SDDC
• Asset Management
• Smart Devices
• Virtualized Storage
• Virtualized Servers
• Virtualized NW
• VDI
• Etc.
Customer
• Call Center Operations
• POS Optimization
• Demand Response
• Campaign Management
• Credit & Collections
• Billing
• Etc.BusinessServices/Applications

• Inclusion of legacy or non-virtualized
hardware resources
• Interoperability of multiple vendors’
converged infrastructure systems
• Management remains a mystery
– Lack of good enough data
– Lack of global optimization strategies
Optimization Challenges

• SDDC management will place a premium on new
management models
– Real-time data collections
– Embedded analytics
– Ability to span multiple data source domains intelligently
• New analytic goals — efficiency, cost, root cause analysis
• Goals include workload-centric optimization, global cost and
energy efficiency, global availability — challenges for
traditional management vendors
• Source: Forrester Research, September 2013
Management Is WAY More
Than Monitoring

• Lack of understanding of relationship of
dynamic technology to services
– Over- and under-provisioning—high costs
– Service risks
– Market risks
• Too many disparate tools and processes
– Expensive and siloed
– Error prone impacting service delivery
• Vendor dependence and “lock in”
– High costs
– Reduced agility
Negative Consequences
of the Current State

• “Imagine how you could combine IT and non-IT metrics to
discover new insights”
– Jonah Kowal, “Leverage Analytics beyond IT Metrics…” June 9, 2014
• “Pervasive, advanced analytics are a competitive issue”
– Milind Govekar, “10 Critical Trends and Technologies…” June 9, 2014
• “Non Linear can alter the nature of keeping the lights on”
– Deb Curtis, Ronnie Colville, “Keynote”, June 9, 2014
• It’s always been this way
Gartner IOM 2014 - Context

• Sports history and tradition
– Player statistics: 100+ years of “we’ve always done it this way”
– Better individual statistics  Higher salaries
– Poorer teams couldn’t buy “best” resources  Always lose
• Going rogue: team and idea
– Oakland A’s (small market, small $$ team)
– Measure/Analyze what REALLY matters, invest accordingly
– Result: 2002 and 2003 success with 3rd lowest player salaries (out of 30!)
• Results:
– Ever more teams adopting approach
– Other sports (football, hockey, etc.)
• Documented:
– A book: “The Art of Winning an Unfair Game,” Michael Lewis, 2003
– A movie: “Moneyball,” starring Brad Pitt, 2011
Learning from Elsewhere

• Traditional metrics and analysis versus “sabermetrics”
– More runs vs. More game-winning runs
– Least errors vs. Least game-losing errors
– More hits vs. Run-scoring hits
– “Measure and analyze what matters!”
• Democratization of information
– More access by everyone to all information
– Victory comes to those who look at EVERYTHING (first)!
• Ruthless drive for efficiency
– Investment size no guarantee, MUST also be more efficient!
– If you don’t, your competition will; you will spend more AND lose!
Moneyball Overarching Themes
Source: Wikipedia “Moneyball” Book Summary

• Traditional metrics and analysis versus “sabermetrics”
– Resource utilization vs. Work efficiency and cost
– Availability vs. Work accomplished
– Technology metrics vs. Application, service and workloads (latency,
throughput)
– “Measure and analyze what matters!”
• Democratization of information
– Software Defined Data Centers: big data, cloud, virtualization,
dynamism, etc.
– Spanning ALL silos: technology, business, financial, etc.
– If you don’t do it, you’ll be “done” by others who do!
Parallels:
Moneyball Themes for IT?

• Merge business and IT processes and tools — Alignment
– IT technology data -> Business analytics
– Business data -> IT analytics
– Use analytics
– Use automation
– Adopt ever-increasing proactivity
• Continuous optimization =
Alignment
+ Analytics
+ Automation
+ Proactivity
Moneyballing IT!

1. Existing tools don’t accept it
– ETL into acceptable format(s) is a lot of work, cost—forever
– Manual efforts cannot scale
– Don’t adapt to dynamic, “virtual everything” realities
2. IT has no expertise in business data
– It isn’t easily presented or understood
– We’ve never had the time to deal with it
3. What can we really DO with it?
– Where do we start?
– What is the value?
Why Doesn’t
IT Analyze Business Data?

• Continuously financially-optimized IT environment
– Always know where and when performance problems will affect the
bottom line
– Identify cost and performance inefficiencies in support of business
processes and eliminate them
• Continuously optimized customer experience
– Understand when, where and why customer experiences fail
– Resolve, predict and prevent customer dissatisfaction issues
Desired State:
Continuous Optimization

“What is the health of
the infrastructure?”
“How efficiently are
we using the
infrastructure?
What does it cost?”
“How many of those
do we have? Need?
When?”
“Changes compared to
the last reporting
period?”
“What’s the capacity
forecast? What
should/will it cost?”
“What were the
exceptions? Do we
Care?”
“What’s the risk
assessment?”
Desired State:
Answer the Questions!

• Significantly reduce initial CapEx, and ongoing OpEx
– Make, and keep making, more money!
• Optimize resources for systems of customer
engagement
• Deploy and refresh new applications faster
– E.g. Retailers need to capture their share of mobile commerce as it
grows from $6B to $31B (2016)
• Respond faster to business spikes
• Prevent business-impacting outages and slowdowns
Result:
Continuous IT Optimization

Underlying IT
Infrastructure
Outage
Management
Customer
Operations
Distribution
Automation
Asset
Management
18
Methodology:
Aligned Business and IT Analytics
Services
Applications
Server/OS
Big Data Collection
Business Intelligence
Aligned Business and IT Intelligence
Enterprise IT
Optimization
• Correlate business
& IT performance
• Insight into how
business process
changes impact IT
• Understand and
optimize IT costs by
business
unit/process and
technology
• Insight into business
performance across
technology stack
Network
Storage

• Federates existing data into purpose-designed
optimization process
– Technology data (e.g. server, network, storage, etc.)
– Service data (catalog, metrics, tickets, etc.)
– Financial data
– Business data (business analytics, KPIs, plans, TXNs, etc.)
• Automates analytics across all data sources
– Flexible and adaptive to dynamic SDDC environments
– Raw (commodity) data -> actionable information for IT
– Proactive to Predictive to Prescriptive
• Single-pane-of-glass IT optimization
Federated IT Analytics

Bank
Data Center Views

21
Status Report

Data Center Views

Power Consumption

Service Views

SLA Breaches
- Note there are two separate
data sources combined in this
report:
• Data from response time monitors
• Data from Service Desk

Services at Risk
Automatic Root Cause Analysis

• Uses modern, appropriate metrics
– Utilization simply doesn’t cut it anymore
– Use ‘sabermetrics’ for IT!
• Democratizes ALL your information
– Leverage both federation and centralization
– Fully-aligned business, service and IT performance
• Ruthlessly (and continuously) drives for efficiency
– Performance/throughput (business)
– Capacity
– Cost
28
An Optimized IT…

• Inventory IT processes and ALL your tools
– Data collection?
– Data storage?
– Capacity analysis/reporting?
• Inventory your business KPIs, factor your BI analytic
initiatives
• Identify low-hanging fruit
– By service?
– By BU?
– By platform?
– By technology/silo?
• Start bringing it together – your competition is!
29
Summary and Recommended Steps

“I know the
performance and costs
of my infrastructure!”
“I know how
efficient my IT
environment is and
can be and what it
will cost”
“I know what we
have, what we need,
and when we need
it!”
“I know what has
changed and why from
the last period!”
“I have a Capacity and
Financial Plan!”
“I understand the
exceptions and their
importance!”
“I know what my
risks to performance
are and will be!”
TeamQuest
Insight Automated, Optimization Achieved

Thank you!
David Wagner
Director Market Development
david.wagner@teamquest.com

Analytics: The Next Killer App for Optimizing IT? #GartnerIOM

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