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Building Big Data Analytics Center Of Excellence
1. Building Big Data Analytics
Center of Excellence
Dr. Mohan K. Bavirisetty
Chief Innovation Officer
Modern Renaissance Corp.
@innovarch #bdadv
2. <Enticement> Announcement
All attendees get some of the collateral
referenced here
All those who participated in discussions get
additional collateral - e.g. eBooks
Best Prize goes to the one who posed most
original and intriguing question.
3. Roadmap
In God we trust. All others must bring data. - W.E. Deming
● What is Big Data?
● Business Value of Analytics
● What is different about Big Data Analytics?
● Big Picture on Big Data Analytics
● Mission Statement
● COE Value Proposition
● COE Focus Areas
● 5 Keys to Success
● Engage in building a Smarter Planet
● Questions & Discussions
4. What Is Big Data?
Big data is high-volume, high-velocity and high-
variety information assets that demand cost-
effective, innovative forms of information
processing for enhanced insight and decision
making. Source: Gartner Group.
Image credit: Greenbookblog.org
5. What Is Big Data?
Big data is high-volume, high-velocity and high-
variety information assets that demand cost-
effective, innovative forms of information
processing for enhanced insight and decision
making.
6. Success from Ground up - A Case Study
involving customer service
Problem Statement: Tracking customer complaints is
taking too long and expensive
Challenge Response: Employ Analytics to provide
actionable intelligence
Results:
Source: Simplify360 Analytics
7. What’s so different about Big Data Analytics?
Source: Analytics in Big Data Environment. by Dr. Lisa Sokol and Robert Ames IBM RedGuide for Business Leaders
11. Gearing up for growth
In the new economy … all Enterprises have to do three things to remain
competitive: improve, innovate and expand. – Peter F. Drucker
12. What is a Center of Excellence?
“A formally appointed and documented body of knowledge and experience on a
particular subject area with the goals of providing expertise, managing
governance practices, and supporting projects associated with the subject area.”
Source: Forrester Research, Inc.
Image credit: School of Athens, by Raphael
14. Why is An Analytics COE Essential?
1. Maximizes the quality, efficiency and application of analytics across all lines of
business, resulting in greater confidence and consistency in decision-making
2. Leads to a higher success rate for business analytics deployments, delivering
more value at less cost and in less time
3. Drives end user adoption, leading to a smoother path to improved outcomes
4. Provides a formal organizational structure, enabling your organization to strike the
right balance between agility and sound management in deploying analytics
technologies
5. Reduces the gap between Business and IT, improving time-to-market and
responsiveness to change
16. COE Focus Areas
● Business Strategy Alignment
● Best Practices & Standards
● Advise & Consult
● Community Services
● Communication and Evangelism
● Enterprise Technical Architecture
● Support
● Education
● IT Governance Alignment
● Data Governance Alignment
17. 5 Keys to Success of Analytics Program
● Strategy
● Value
● People
● Process
● Technology
Boyer, et. Al. (2012) 5 Keys to Business Analytics Program Success
18. Strategy
● Establish the vision to use Analytics for better
business outcomes and beyond
● Connect the COE Mission to the priorities of your
business
● Find Analytics Champions inside the company to
sponsor COE
● Build a roadmap identifying information sweet
spots that reflect priorities and key objectives of
business
● Build a COE steering committee involving key
stakeholders from IT, Finance and Business
19. Value
● Identify a core team to continually measure and
report on the value of Analytics projects
● Create a business case for each Analytics project
and demonstrate increase in business
effectiveness iteratively
● Capture benchmarks that can demonstrate value
● Maintain a Business Value Portfolio
● Communicate the success across the
organization
“By using Business Analytics to understand sales patterns, match buying to sales,
increase sell-through and cut returns, we gain a dramatic return of investment”
- Nihad Atyaman, Elie Tahari
20. People
● Assess Current Analytics Culture and Maturity
● Encourage executive involvement
● Map your stakeholders to COE steering
committee
● Create virtual teams and corresponding role
maps
● Fund training and certification programs
● Cultivate a Data and Decision Sciences practice
● Encourage people to develop cutting-edge skills
21. Process
● Develop and customize an Agile BI process and
Analytics-Oriented BI Architecture
● Adopt it to Big Data - include both real-time and
batch data
● Emphasize on Data quality
● Establish Data Governance program - use it drive
best practices
● Have enablement and adoption programs
● Review and Revise processes and programs
regularly
“Evidence-based decision-making (aka Big Data) is not just the latest fad, it's
the future of how we are going to guide and grow business.” - Kristen
Hammond, CTO, Narrative Sciences
22. Process - Analytics Oriented BI Architecture
Source: Information Management Jan/Feb 2011
23. Technology
● Assess your stakeholder needs
● Engage the star-players both on IT and Business
to help in Technology selection
● Engage the vendors to build POCs for your
business case
● Ensure Technologies are compliant with
standards
● Avoid vendor lock-in
● Architect your solutions to promote self-service
● Build for change - growth and user adoption
25. References
Bavirisetty (2008) Open COE Method. Building Centers of Excellence for
Competitive Advantage.
Bavirisetty (2010) 8 Disciplines of Enterprise Modernization.
Boyer, et. Al. (2012) 5 Keys to Business Analytics Program Success
Drucker(1986) Discipline of Innovation, Harvard Business Review
Hammond(2013) The Value of Big Data isn’t the Data. Harvard Business Review blog
IBM(2013) Unlock Big Value in Big Data with Analytics IBM Redbooks publication
MIT & SAS (2013) From Value to Vision:Reimagining the Possible with Data Analytics
INTEL (2013) What is Big Data and Why Should You Care?
InterSystems(2011) Big Data Case Studies and Key Considerations
Porter (1998) Competitive Advantage: Creating and Sustaining Superior Performance
Talend(2013) Demystifying Big Data Complexity
26. about.me
Dr. Bavirisetty is the CIO at Modern Renaissance, a Thought
Leadership company that helps businesses, organizations and
individuals to realize unprecedented levels of innovation
through strategic design thinking, innovation platforms and
disruptive technologies. Before he founded Modern
Renaissance, he worked with IBM, Pegasystems, Sybase and
with a number of clients helping them modernize their
enterprises as well as build smarter systems, platforms and
solutions.
Dr. Mohan K. Bavirisetty
mohan@emodern.biz
about.me/innovate4good
@innovarch
Research Assistant:
Rachel Fleming rachel@emodern.biz
