Creating and managing a data office is not an easy task. The reasons for so many problems in streamlining a data strategy come from lack of data ownership, lack of a data roadmap and the data processes not clearly defined. Using the Lean Principles that come from the Toyota Production System is one method that has been proved to be quite successful. This session delivered for the Data Quality Pro Summit explores how it can be done.

1. Using Lean Principles to Manage
the Data Value Chain
Mario Faria
Twitter: @mariofaria
Head and Chief Data Officer
CDO, Inc.
http://www.cdo-inc.com/
Track: Data Quality, Data Governance
Industry:

2. Mario Faria
2
About Mario Faria
• Mario was one of the first Chief Data Officers in the world
• Acting as a CDO for the last 5 years in North America, South America,
Europe and Asia
• Passion : Bring order to the chaos
• Leader of teams working in Analytics, Data Monetization, Data Quality,
Data Governance, Operations and Business Architecture
• Motto: “If you do not treat people, technology and data as economic
assets, they will become liabilities”
Mario Faria
Twitter: @mariofaria
Head and Chief Data Officer
CDO, Inc.
http://www.cdo-inc.com/

3. Managing your most
important asset to
drive business
performance

4. In
May
1915,
The
Boston
Red
Sox
Babe
Ruth
pitching
debut
and
his
first
home
run,
but
…

5. The
Rex
Sox
lost
to
the
NY
Yanks

6. Your
data
strategy
is
a
journey

9. Mario Faria
9
The 3 Architectures a Company needs
to succeed
Business
Architecture
Technology
Architecture
Data
Architecture

10. Mario Faria
10
Data & Analytics Responsibilities
• Data Strategy
• Data Governance
• Data Quality
• Data Analytics
• Data Insights
• Data Architecture
• Data Acquisitions
• Data Operations
• Data Policies
• Data Security
• Data Protection

11. A
data
&
analyGcs
team
is
responsible
for
transforming
data
assets
into
compeGGve
insights,
that
will
drive
business
decisions
and
acGons,
using
people,
processes
and
technologies

12. Data
teams
build
the
bridge
between
business
and
IT

13. Mario Faria
13

14. Mario Faria
14

15. Mario Faria
15
A data product allows an objective to
be achieved using data & analytics

16. Mario Faria
16
More and more, leaders are being hired to
think strategically about all the steps, from
getting raw data and making it useful to the
business users

17. Mario Faria
17
Chief
Data
Officer
(focused
on
data
management)
Chief
Digital
Officer
(focused
on
digital
transforma8on)
Chief
Analy8cs
Officer
(focused
on
decision
management
ini8a8ves)
The
ul8mate
leader
who
creates
and
executes
digital,
data
and
analy8cs
strategies
to
drive
business
value
Copyright:
Mario
Faria
2014
The
Chief
Data
/
AnalyGcs
/
Digital
Officer
roles

18. Mario Faria
18
A few lessons I have learned to
become a data and analytics expert
• Many problems with streamlining a data strategy
• Major concerns with data management
• How you can overcome the issues
• What I have learned from several data journeys

19. The
Data Life
Cycle

20. Mario Faria
20
The Data Value Chain

21. Mario Faria
21
A few problems in most organizations
• Data is fragmented and scattered
• Silos of information hanging around
• Like the truth, data has many versions
• The Data Lifecycle is a complex process
• Data projects being managed by IT
• A formal process to data management is
a requirement in order to do Analytics

22. Mario Faria
22
Data is an abstract concept

23. Using Supply Chain
Concepts and
Techniques to
manage your
data assets

24. Mario Faria
24
Data & Analytics as a Production System

25. Mario Faria
25
The Deming Model :
Production Viewed as a System

26. Mario Faria
26
What is Data Quality ?
• Quality is a customer perception
• A few dimensions: freshness, coverage,
completeness, accuracy
• It is a never ending job

27. Mario Faria
27
A Few Quality Programs
TDQM
TIQM

28. Mario Faria
28
Source: Dan Myers, The Value of Using the Dimensions of Data
Quality, Information Management

29. Implementing
Lean Best Practices
that came from the
Toyota Manufacturing
Process

30. Mario Faria
30
Toyota Production System

31. Mario Faria
31
Lean Goals
• Improve quality
• Eliminate waste
• Reduce lead time
• Reduce total costs
It is about how behaviors, processes and
actions can be changed for improving the
overall system

32. Mario Faria
32

33. Mario Faria
33

34. Mario Faria
34
The 8-Basics of Kaizen
Based Lean Manufacturing,
by Bill Gaw
http://bbasicsllc.com/

35. Mario Faria
35
• Specify the value desired by the customer
• Map the data value stream
• Reengineer your data processes to eliminate waste
• Introduce “pull”
• Strive for continuous improvement
Source : Meghann Wooster, Beyond Fire Drills: Applying Lean Principles to Information
Governance, http://www.cmswire.com/cms/information-management/beyond-fire-drills-applying-
lean-principles-to-information-governance-023705.php
Applying Lean Principles to Information
Governance

36. Mario Faria
36
• Data & Analysis are becoming products
• Quality is key to success
• Data explosion in volume, variety and
velocity
• The number and value of external data
sets are rising fast
• Focus your team efforts is crucial
• Leverage technology to implement a
distributed data value chain initiative
Why Building a Distributed Data Value
Chain is Critical

37. Mario Faria
37

38. Mario Faria
38
The Predictive Analytics
Factory Concept

39. Mario Faria
39
Data Value Chain Monitoring
Centers

40. Right
People
Right
Data
Right
Technology

41. Without
proper
Data
Quality
principles,
it
is
impossible
to
achieve
the
goals
of
increasing
revenue,
reducing
costs
or
gaining
operaGonal
efficiency
in
the
business
areas

42. Mario Faria
42
Problems with Data Quality
• Business people don’t understand it and don’t have time
or patience
• IT people still have a technology mindset
• Data & Analytics people make it more complex than it is

43. Mario Faria
43
Quality is about customer
perception

44. Mario Faria
44
What you can do : Establish a
customer oriented mentality within
your team

45. How
did
some
organizaGons
change
to
a
data
driven
culture
?

46. Make Everyone in
the organization
feel responsible for
Data Quality

47. How prepared is your
business to have
a lean data quality
program in place ?

48. Time
People
Technology

49. Some bonus tips
and
recommendations

50. Mario Faria
50
Start where it hurts the
most

51. Mario Faria
51
Learn from mistakes

52. Mario Faria
52
Be flexible and adapt to
changes fast

53. Mario Faria
53
Source : Leading Strategic Initiatives (www.leadingstrategicinitiatives.com)

54. Conclusions

55. Mario Faria
55
Data, Information, Analytics, Business
Intelligence and Performance Management

56. “The Data Asset: How Smart Companies
Govern Their Data For Business Success” - by
Tony Fisher

57. Mario Faria
57
• A good CDO can implement a data organization
with success
• A great CDO has the ability to turn raw data into
new revenue streams for the business
• Components such as technology and
methodologies are important, but they are just
enablers
• The CDO focus is delivering enterprise value to the
business (not writing code or SQL scripts)
From good to great CDO

58. Mario Faria
58
How leaders can benefit from using Lean for
Data Quality programs
• Increase of productivity
• Increase throughput
• Improve of quality
• Reduce of cycle times
• Less fire-fighting
• Smooth operation
• Reduce costs

59. Mario Faria
59
Golden Rules to Success in Data Quality
• Find out the Why
• Strategic vision and a plan in place
• Strong Data Quality leader
• Secure investments and budget
• Always deliver results

60. Mario Faria
60
Future of Data Quality

61. Mario Faria
61
When was the last time ?

62. Mario Faria
62
“Continuous improvement is not about the things you
do well — that’s work. Continuous improvement is
about removing the things that get in the way of your
work. The headaches, the things that slow you down,
that’s what continuous improvement is all about.”
Bruce Hamilton , lean thought leader

63. Mario Faria
http://www.cdo-inc.com
www.slideshare.com/fariamario
Twitter : @mariofaria
mario.faria@cdo-inc.com
+1 (425) 628-3517