The document discusses a webinar series on data monetization, highlighting historical developments in data collection, management, and technological advancements such as blockchain and IoT. It emphasizes the importance of first mover advantage in digital business, the challenges of self-service BI, and the need for effective data presentation to facilitate decision making. The content outlines various strategies for wrapping data around products and discusses the evolving landscape of data monetization and management.

1. Data Monetization
Webinar Series / Expert Sessions
Henrik Gabs Liliendahl, Product
Data Lake
Dr. Rado Kotorov, Information
Builders

2. Data Revolutions and
Their Impact on Business2

3. 3
 The invention of writing allowed
for the collection and store of
DATA
 This lead to:
 Sales records
 Aggregate results
 Tax collection
 This lead to:
 Trade expansion
 Cities
 Large construction projects

4. 4
 Invention of double entry
accounting in the 15th century:
 The general leger creates
undisputable record of
business transactions, profit
and losses
 Agency trade emerges
 Then came the computer and
ERP Systems
 Then came Blockchain – the
universal ledger
Goal is to reduce transaction costs!

5. 5
 The sensor –causing the 4th
industrial revolution
 Every process and activity is
under microscopic scrutiny
 Extreme insight into processes,
events and condiotions
The rush is to embed as
many sensors in
everything and reap the
opportunities.

6. 6
 Physical Assets
Businesses
 Digital Businesses

7. 7
Scale
Scope
Effect on Competition
 First mover advantage matters
 First mover scales fast
 Digital businesses expand
scope fast
Penetrate adjacent markets
at super speed
Hypercometition is the new
norm.

8. 8
If you didn’t think that first
mover matters, here is how
Bezos titled his book
released in February 2018.

9. 9
Three flavors of data monetization
Wrapping data around
products
Advanced analytics and
decision making
Selling data
Third party data First party dataSecond party data

10. 10
Data management and data monetization
MDM
Supplier self-service Customer self-service
Self registrationSelf registration
Product data syndication Syndicated product information
Big reference data: Business directories, consumer/citizen information, location data
Business ecosystems
Social data:
profiles and
streams
Sensor data / IoT Data lakes

11. 11
Quest no 1: Enterprise wide data management
Location master data as an example Wrapping location data around products
and services
Including location data in advanced
analytics and decision making

12. 12
Quest no 2: Ecosystem wide data management
Example: Product data syndication
Trading products with
chaotic (often excel and
email based) data exchange
Trading products with shared data
wrapped around

13. 13
Result: Product data monetization
Wrapping data around products
We do not always
want to be told
what to buy.
We want to know
what we are
buying.

14. 14
Well known examples from best performers
Wrapping data around products and services
Two way
reviews
Data governance in
self-service

15. Poll Question
Webinar Series / Expert Sessions

16. The Vote Is Still Out on Self-Service BI
16
 Self-service failed to
deliver pervasive BI
 Less than 30%
penetration
 Operational people want
information but do not want
DIY analysis!!!

17. Analysis vs. Decision Making
17
 What and Why?
 Data and method
 Time consuming
 When and How?
 Clear choice options
 Quick decision

18. • Self-Service failed to deliver pervasive BI
• Less than 30% penetration
 Companies are significantly more aware of
the differences and benefits of Operational
BI for on the job decision making
FACT Change
Analysis is different from deciona making!

19. 19
Make a decision in less than 6 min Make a fact based decision instantly

20. Aesthetics of data presentation Storytelling and Infographics
FACT Change
 Transition from showing just data to stories
 Conclusions jump at you
 Design builds emotional connecton
 Dashboards are boring
 Too many; all look the same
 Conclusions do not jump at you

21. User habits are changing Voice for mobile BI
FACT Change

22. Multiple ledgers, i.e.
each company
keeping its own
ledger, increase
transactions and
verification costs
The number of peer-
to-peer digital
transactions are
growing reapidly
A universal unbreakable ledger
increase the speed of transacting
and lowers the cost
FACT Change

23. Architecture to Support Survival in the Digital World
23
The digital enterprise technology platform
includes five interrelated systems with BI
and information management being at its
core:
 Scaling your BI out requires a deep
technology that is highly customizable &
secure
 Scaling your BI across requires robust
information management stack

24. Data Monetization
Webinar Series / Expert Sessions
Henrik Gabs Liliendahl, Product
Data Lake
Dr. Rado Kotorov, Information
Builders