Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ? Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics

1. Agile Data Strategy and
Lean Execution
Mario Faria
mario.faria@cdo-inc.com
@mariofaria
http://www.cdo-inc.com/
Aug 22nd 2014

2. Agile data strategy and lean execution
August 22, 2014
Moderator: Mario Faria
Chief Data Officer, CDO Inc.
mario.faria@cdo-inc.com
Antanina Kapchonava
Project Director, Data Driven Business
antanina@datadrivenbiz.com

3. Participants
Vik Manchanda
Chief Infor mation Officer
Mario Faria
Chief Data Officer
Mike Jennings
Senior Director
Enterprise Data Architecture

4. mario.faria@cdo-­‐‑inc.com
@mariofaria
h0p://www.cdo-­‐‑inc.com
• One of the first Chief Data Officers in the world
leading teams focused in Analytics, Data
Monetization, Data Quality, Data Governance,
Operations and Business Architecture
• Currently he is the head of CDO, Inc., advising
companies on how to cross the “data & analytics
chasm”
• Worked as a CDO for ServiceSource and Boa
Vista (Equifax)
• Worked for IBM, Accenture and Microsoft,
leading projects related to BI, DW, CRM, Supply
Chain, Web Development and Management
Consulting
• His motto is : "If you do not treat people,
technology and data as economic assets, they will
become liabilities“
Mario Faria
Chief Da ta Officer

5. Mario Faria
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6. Mario Faria
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7. Mario Faria
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8. Mario Faria
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How to transform data
assets into competitive
insights, that will drive
business decisions and
actions, using people,
processes and
technologies ?

9. Mario Faria
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On data and analytics
• Many problems with streamlining a data strategy
• Major concerns with data management
• How you can overcome the issues
• What we have learned from the data journey

10. The Manifesto for Agile Software Development
Mario Faria
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• Individuals and interactions over
processes and tools
• Working software over
comprehensive documentation
• Customer collaboration over
contract negotiation
• Responding to change over
following a plan

11. Mario Faria
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Source : Leading Strategic Initiatives (www.leadingstrategicinitiatives.com)

12. Data, Information, Analytics, Business
Intelligence and Performance Management
Mario Faria
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13. Mario Faria
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The Data Value Chain

14. Mario Faria
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15. Mario Faria
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The Deming Model :
Production Viewed as a System

16. Mario Faria
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Toyota Production System

17. Implementing
Data Management
Best Practices based on
the Lean Principles
that came from the
Toyota Manufacturing
Process

18. The Chief Data / Analytics / Digital Officer roles
Mario Faria
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Chief Data Officer
(focused on data
management)
Chief Analytics Officer
(focused on decision
Chief Digital Officer
(focused on digital
transformation)
management
initiatives)
The ultimate leader who
creates and executes digital,
data and analytics strategies
to drive business value Copyright: Mario Faria 2014

19. How
did
some
organiza/ons
change
to
a
data
driven
culture
?

20. Mario Faria
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Executive Support

21. How
AIG
and
Walgreens
implemented
some
of
these
changes

22. Michael Jennings : Bio

23. Enterprise Data Strategy Brief
22 August 2014
Mike Jennings
©2014 Walgreen Co. All rights reserved. Confidential and proprietary information. All rights reserved.

24. Walgreens Company Overview

25. Data Opportunities
Challenges to Fully Leveraging Data

26. Defining Enterprise Data Strategy

27. Why do we need this strategy?
Enterprise Data Strategy will help:

28. Data Strategy Depends on
Enterprise Data Management

29. Data Strategy Depends on
Data Governance & Stewardship

30. Data Strategy Depends on
Master Data & Reference Data

31. Data Strategy Depends on
Data Quality

32. Data Strategy Depends on
Enterprise Data Models & Data Integration

33. Data Strategy Depends on
Leveraging Industry & National Standards

34. SAVE THE DATE!
CDO EXECUTIVE FORUM 2014
NOVEMBER 12, 2014 - NEW YORK, NEW YORKER HOTEL
CUTTING-EDGE RECOMMENDATIONS ON HOW TO:
• Mobilize your C-suite and prepare your organization for a new data-driven culture
• Translate your enterprise data assets into intelligence by reconsidering your approach to
information management processes
• Reach the consensus between the IT and business units to attain organizational efficiency
and eliminate the dangers of siloed data
• Get a granular view of your data: use analytics to separate clutter from meaningful
information and boost your company’s profitability
• Deliver highly actionable data through enhanced data management and analytics
initiatives
Find out more at:
http://www.datadrivenbiz.com/cdoforum/index.php
Call 201-204-1674 or email antanina@datadrivenbiz.com
Register today with discount code WEBINAR0819 and save additional $100

35. Vik Manchanda
Chief Information Officer
RUTGERS UNIVERSITY, NJ
B.A. – Computer Science
COLUMBIA UNIVERSITY, NY
CTA Diploma
UCLA, CA
Executive IT & Business Integration
Coaching
AIG Life and A&H Houston, 2012 – Present
Senior Vice President, Chief Information Officer
AIG Advisor Group Houston, 2009 – 2010
Sr. Consultant
ACE Group, LTD. Houston, 2008 – 2009
Executive Vice President, Chief Architect & Data Officer
AIG Global Services New York, 2005 – 2008
Vice President, Chief Strategy & Administration Officer
AAIG Retirement Services Los Angeles, 2001 – 2005
Vice President, Senior Information Officer
AIG Domestic Brokerage Group New York & INDIA, 1996 – 2001
Assistant Vice President, Information Services Group
Bear Stearns, Inc.; New York, 1989 – 1996
Lehman Brothers; Citi Group;
Suburban Propane; AT&T
Affiliations:
• SIPA
• TiE
• No Kid Goes Hungry
• American Cancer Society

36. • Get Facts @ the right
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time and the right place."
• Use Facts everytime
making crucial business
decisions."
• Preserve Facts."
Winning with Data!

37. Big Data Practice
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Our approach reverse that
ratio offering maximum
business value in Revenue
generation, Operational
efficiency and Compliance
Business
Intelligence
Data Mining
OAP
Benchmarking BPR
Data
Warehousing
Analytics
Reporting
Traditionally 75% of
effort spent in data
aggregation and
transformation yields
25% in benefits
Big
Data

38. Three Good Winning Examples:
ü At AIG, we use data gathered from physical exam and blood results and pass
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them through a model jointly created along with John Hopkins University to
predict mortality rates and based upon that we underwrite insured, resulting in
significant reduction in claims & increase in net profits.
ü At Ace, we created a model to apply to the insured to predict their risk level
and accordingly either underwrote them with appropriate rate class or denied
coverage. Same model was used to detect fraudulent claims.
ü At AIG, we are using a combination of mobile and data strategy to converge
distribution channels such that each agent is able to offer multiple lines of
businesses to the customers, as opposed to traditionally just creating leads for
the other lines of business. Further we are creating incentives for cross-selling
and upselling that are visibly working.

39. Incent The Right Behavior
• Link Compensation to Targets"
• Create Commission
39
Transparency"
• Allow Margin Control at Point
of Sale"
• Stricter Compliance and
Governance"
• Yield Higher Revenues"
"

40. Debate

41. Participants
Vik Manchanda
Chief Infor mation Officer
Mario Faria
Chief Data Officer
Mike Jennings
Senior Director
Enterprise Data Architecture

42. Q&A

43. Participants
Vik Manchanda
Chief Infor mation Officer
Mario Faria
Chief Data Officer
Mike Jennings
Senior Director
Enterprise Data Architecture

44. Conclusions

46. Agile Data Strategy and
Lean Execution
Mario Faria
mario.faria@cdo-inc.com
@mariofaria
http://www.cdo-inc.com/