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Mark Zozulia, Principal, Deloitte Consulting LLP presented the keynote address on "Operationalizing the Analytics Enterprise" on April 4, 2014 at the Kelley Forum on Business Analytics 2014.
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Mark ZozuliaDeloitte US Business Intelligence & Data Warehousing Practice Leader
Operationalizing the Analytics EnterpriseKelley Forum on Business Analytics
Agenda1. Trends – Data as the “end”2. Enablement – What is enterprise?3. Operational Insights – Keeping pace…4. Closing Remarks5. Q&A
Trends – Data as the “end”empowering the businessinsights as a service
1. Analytics Applied• Explosion in other countries• Global glue
2. CxO Viewpoints• Empowerment of the business with data • What the CIO needs to do to keep up
3. Vendor Perspectives• Pre-built analytic solutions / applications• Scalability, Enterprise-ready, Modernization
Deloitte Global Analytics Summit – Munich Germany
AnalyticsAware
2009-2013
AnalyticsApplied
2013-2016
InsightEconomy
2020+“Big Data”
“Internet of Things”
“Analytics Enterprise”
CloudComputing
Machine Learning / AI
DataScientists
Crowd-sourcing
Analytics asa Disruptor
2014-2018+
Analyticsas R&D silo
1995 - 2009
ActuarialModels
Smart phones
SocialMedia
Evolution of Analytics
Data as a means to an end Data is the end Data as a service
InternetOf
ThingsBig Data
Data Science / Machine Learning
ConvergingTrends:
Innovation: New Data New Processes New Insights
• Integrated ecosystem –customers, employees, shareholders, suppliers
• Zero Latency information flow
• Secure data exchange
Insight Economy
• Culture of data-driven decision making
• Integration of operational and behavioral data
• Machine-learning detection of patterns and trends
Road to the “Insights Economy”
“We are moving to a world where the machines we work with are
not just intelligent; they are brilliant. They are self-aware, they are
predictive, reactive and social. It's a world where information…
comes to us automatically when we need it without having to look
for it… allowing us to remotely and automatically monitor,
manage and upgrade industrial assets.”
Marco Annunziata, Chief Economist, General Electric
Internet of Things – “Industrial Internet”
Challenges of Big Data
Velocity
Volume
Variety
Value
+
+
=
Sources:1 http://www.theverge.com/2013/5/19/4345514/youtube-users-upload-100-hours-video-every-minute2 http://mashable.com/2012/06/22/data-created-every-minute/3 http://gartnerevent.com/SYMfactoids/
Velocity Frequency of data generation
100 hoursOf video uploaded to
YouTube every minute1
2,000,000 queries
On Google every minute2
47,000 App download per
minute at the Apple Store3
Volume The growth of world data
1 terabyte hold the equivalent of roughly 210 single sided DVDs
Variety Structured and unstructured data – types of Big Data
Web and social mediaData includes clickstream and interaction data from social media such as Facebook, Twitter, LinkedIn and blogs.
Machine to MachineData includes readings from sensors, meters, and other devices as part of the so-called “internet of things”.
Big transaction dataIncludes healthcare claims, telecommunications call data records (CDRs), and utility billing records that are increasingly available in semi-structured and unstructured formats.
BiometricData includes fingerprints, genetics, handwriting, retinal scans, and similar types of data.
Human-generatedData includes vast quantities of unstructured and semi-structured data such as call centre agents’ notes, voice recordings, email, paper documents, surveys, and electronic medical records.
The Big Data Value Equation
Velocity Volume Variety Value+ + =Veracity Viability+ +
Veracity Establishing trust in data
1 in 3business leaders don’t trust the information1
Uncertaintydue to inconsistency,
ambiguity, latency and approximation
Value Return on investment
CostsRisk of simply creating Big Costs without creating the value
InsightSophisticated queries, counter-intuitive insights and unique learning
Viability Relevance and feasibility
Hypothesisvalidation to determine if
the data will have a meaningful impact
Long-termrewards and better
outcomes from hidden relationships in data
“Does weather affect sales?”
Sources:1 http://businessoverbroadway.com/in-data-we-trust
Enablement –What is Enterprise?new use casesnew opportunities
Industry Analytics Use Cases
Heat Map: Warm Hot Boiling
Industry/Domain Customer Supply Chain Workforce Finance Risk
Consumer Business and Transportation
Energy and Resources
Financial Services
Life Sciences and Health Care
Manufacturing
Public Sector
Technology, Media and Telecommunications
Source: Deloitte analysis, 2013
CxO Viewpoints
1. Analytics has landed on the agenda for most CXOs—it’s no longer the sole domain of a few select teams buried deep in the business
2. Analytics-focused collaboration between CXO stakeholders is rising rapidly in importance
3. CEOs need to engage more and serve as the orchestrator
Creating the Analytics Enterprise
Value, not science experiments
Vision
Mission
Key Objectives
Companies achieving competitive advantage with information require new organizational, transformational, and technology approaches for enabling the analytics enterprise
• Operationalizing high value business use cases through data mining, discovery and visualization
• Defining new organization models that redefine traditional roles between IT and the business
• Integrating big data with traditional data in data warehouses• Optimizing core business intelligence and reporting environments• Architecting purpose-built, high-performance analytic technology
ecosystems
Analytic “factories” to keep pace with business
demandBuild capabilityInnovation (and cost
take-out) through architecture
Operational Insights– Keeping pace…what to do how to start
MENU
“I’m in the mood for fish tonight…”
Order
Listen to the customer first and the value sought
Business Opportunity
“We can substitute that. And may I recommend a wine?”
Server and Sommelier
Understand the issues in the context of a function and industry, we can begin to translate business needs into analytical requirements
Visioning
Plating and DeliverySprinkle with chives and garnish
Displaying the analysis in an intuitive and compelling way
Visualization and Delivery
Consumption and Reviews“Is your meal to your liking?”
Insights and FeedbackEnable informed decision-making and collect feedback for process improvement
Analytics as the “Insight Restaurant”
Top Questions
Enabler Awareness
Understanding the needed people, processes and
technology enablers
Analytics Momentum
Generating excitement, buzz and demand in the organization for analytic
solutions
Leading from the Front
Aligning the analytics organization behind corporate goals and
priorities
Capacity & Skills
How do we make sure we have the right set of skilled resources available to deliver on business demand?
Priority Insights
How do we make sure our “Phd” type resources are answering difficult questions, not building proof of concepts?
Data Platforms
How do we work with our IT partners to stand up a platform that enables quick access to high quality data on a global scale?
Efficient Delivery
How do we stand up an efficient delivery model aligned to critical business segments and also a center of excellence?
Where to Focus & What to Expect
Processes
How do we implement processes that promote collaboration across the business?
Getting Started – The Program Journey
“Agile Analytics”• Work through agile sprints to build dashboards and analytical models
• Align with IT delivery models
• Train end users and roll application out to the enterprise
“Prioritize and Analyze”• Establish a business driven analytical conformity layer
• “Harden” POCs with certified data
• Iteratively define requirements using real data and tools
“The Art of Possible”• Stakeholders determine use cases utilizing “sandboxes”
• Demonstrate POCs for analytic applications through roadshows
IdeaProof
of Concept
Requirements
Pre-Design
Design
Deploy
Next Generation Analytics Ecosystems
Closing remarksanalytics appliedanalytics enterprise
Key Takeaways
The Light at the End of the Tunnel
is a Train
New Data, New Processes, New
Insights
New Skills Required – Get or
Grow Them
Rethink Decision Making
GET STARTED
Questions?
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