Data process management involves collecting data, processing it, and delivering relevant insights and value to customers in real-time through a simple, secure, and sustainable process. It requires integrating knowledge, technology, and people to manage data quality, ensure a single source of truth, and drive business goals. An agile approach to data process management can create both short-term profitable actions and long-term value for organizations.

1. DATA PROCESS
MANAGEMENT
The ability to build data-driven
long-term relationships
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2. INTRODUCTION
@BNieme
• Founder Adversitement, O2MC I/O,
Digital Power
• 10 years in financial sector -
transparency
• Digitally active since 2000
• Privacy by Design Ambassador
• Board of Advisory TU/e M&I
215-06-15

3. 15-06-15 3
AGENDA
• Value
• Our Challenges
• Data Management
• Data Process
Management
• Customers & Data
• FAQ

4. Data will tell if your strategy is
right !
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5. BRAND
VALUE
• What would they miss if
your brand was not
around anymore?
• Why would they invest in
a relationship with you?
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“Consumers state that 70%
of the brands they buy
are fully exchangeable.”

6. Long-term strategic value
Improved reputation and customer
experience and agile competitive
advantage
Short-term operational value
New business opportunities, more
efficient marketing processes, smarter
decision making, time and cost reduction
and guaranteed data control
BUSINESS
VALUE
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7. VALUABLE
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8. WE NEED TO BUILD
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TRUST.

9. 15-06-15 9
CAN I
TRUST
Y O U ?
• Safety
• Transparency
• Honesty
• Convenience
• Relevance
• Compliance
• Respect

10. HELLO?
We want to have relevant experiences!
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11. ARE YOU
RELEVANT?
• Do you care
about me?
• Are you trying to
improve my life?
• Do I get a voice?
• Are you just in
time?
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12. BIG DATA,
BIG DEAL
• What’s
going on?
• What’s
the value?
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13. HYPER-CONNECTED ECONOMY
The internet of everything
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Omni Channel - customer

14. WE PRODUCE DATA
EVERY
SECOND
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15. 15-06-15 15
ON PURPOSE/
OFF PURPOSE?
WE HAD MULTIPLE WAKE-UP CALLS

16. BRIDGING
TODAY’S
CHALLENGES
TODAY’S
SOLUTIONS
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17. 15-06-15 17
ONLY 15%
of global companies
is able to exploit big
data in 2015.
Adapt new
technologies
to utilise:
Volume, Velocity,
Variety, Veracity

18. TODAY’S BIG DATA
CHALLENGES & COMPLEXITY
Business Applications
Inefficient siloed data for Marketing and Sales applications
.
Data Life Cycle Management
Inefficient and very costly data management process
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19. Q 1915-06-15
How is the data
process within your
company defined?
Who’s responsible?

20. DATA PROCESS
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BIG DATA
DATA
OPERATIONS
(processing)
RELEVANT
VALUE
REAL-TIME /// SIMPLE – SECURE - SUSTAINABLE
KNOWLEDGE + TECHNOLOGY + PEOPLE
All data
All sources
Data efficiency
Data quality
Data governance
One truth

21. 15-06-15 21

22. Q 2215-06-15
What data do you
collect?
Do you take your
customer journeys
into account?

23. A FOOL
WITH A
TOOL
2315-06-15

24. DATA PROCESS
MANAGEMENT
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1. Collect 2. Process 3. Deliver

25. 15-06-15 25
COLLECT

26. Q 2615-06-15
How do you
manage the data
processing?
Are your
customer data
available?

27. 15-06-15 27
PROCESS
• Knowledge
• Technology
• People

28. 15-06-15 28
SCALE YOUR
KNOW HOW!
Knowledge
• Domain knowledge
• Big data technology
• Regulations
• Customer Journeys

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ACCELERATE BY
AUTOMATION
Technology – standards and innovation
• Collection
• Tag management
• Storage/Data warehousing
• Analytics
• BI tools
• Visualisation

30. 15-06-15 30
YOUR
COMPETENCES
People – co-creation
• CDO, CMTO, CIO
• Data scientists
• Data engineers
• Analysts
• IT

31. 15-06-15 31
DATA DRIVEN
Company – Agile, Process, Innovation
ActionDecisionInsightDataKPIBusiness goal
Data Process ManagementManager Analyst Manager

32. Q 3215-06-15
What kind of
technology is
valuable for your
business?
Are they supported
by the right
knowledge?

33. WHAT
ABOUT
DATA
QUALITY
3315-06-15

34. DATA QUALITY
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• Poor data quality is a primary reason for 40% of all business
initiatives failing to achieve their targeted benefits.
• Data quality effects overall labour productivity by as much as
20%.
• As more business processes become automated, data quality
becomes the rate limiting factor for overall process quality.

35. Q 3515-06-15
How does data
quality affect
your decision
making?
How do you
control your
data quality?

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DATA
QUALITY
• Complete
• Accurate
• Accessible
• In time

37. 15-06-15 37
DATA
QUALITY
REQUIRES
• Knowhow to be
shared
• Best of breed
technology and
practices
• High expertise to
be standardised
• Prevention of new
compliance risks
• Innovations to be
top priority

38. DATA ETHICS
TIME TO TAKE A STAND
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39. Q 3915-06-15
What is your
(organisation’s)
standpoint on
data ethics?
How will data
ethics impact your
reputation and CX?

40. DATA,
DATA,
DATA…
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41. Q 4115-06-15
Why do you
collect data?
For what
activities is
this data
valuable?
What would be the
impact if your data
weren’t available
anymore?

42. EVERYBODY HAS THE RIGHT
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TO BE FORGOTTEN

43. Q 4315-06-15
Is your data
process fit to
facilitate this right
to your customers ?
Will it make a
difference if you
do?
Can you adapt to
new circumstances
and regulations?

44. “TRY NOT
TO BECOME
A MAN OF
SUCCESS
BUT A MAN
OF VALUE.”
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45. YOUR DILEMMA
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SHORT-TERM PROFITS
OR
LONG-TERM VALUE?

46. OUR SUGGESTION
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“AGILE DATA PROCESS MANAGEMENT WILL
LEAD TO LONG-TERM VALUE AND
SHORT-TERM PROFITABLE ACTIONS.”
BOB NIEME, ADVERSITEMENT

47. THNX FOR
YOUR
ATTENTION
15-06-15 47
Bob Nieme
Adversitement