This document discusses strategies for effective data monetization. It outlines challenges in data monetization like the increasing volume of data and the need for AI. It presents a data monetization maturity model and describes the top 5 best practices for successful data monetization as: getting the foundation right by infusing AI/data science; focusing on people like data engineers and scientists; constructing a robust business model; and ensuring trust and ethics. The document recommends using case generation and prioritization and provides industry examples. It promotes IBM Cloud Private for Data as an integrated analytics platform to overcome challenges and realize the benefits of data monetization.

1. Karan Sachdeva
IBM Asia Pacific
karan@sg.ibm.com
M- +65 9028 3694
Effective Data Monetisation Strategies

2. 2
1. Unlimited and Complex
2. Blending and sharing
3. Valuable when Real time
Data has been called “the new oil”
However, I believe that data is more than the
new oil. Data is-
Data Monetization = Economic Value:
Reducing Cost,
Increasing Revenue and
Managing Risks

3. Data Monetization Maturity Model
AI and Data Science is basis of data monetization
Operational BI and Data
Warehousing
Self-Service
Analytics
New Business
Models
TRANSFORMATION
Value
MODERNIZATIONCOST REDUCTION INSIGHT-DRIVEN
Most
are here
83% of
organizations
view AI as a
strategic
opportunity
3Descriptive Analytics Predictive Analytics Prescriptive Analytics

4. 4
Data Monetization Challenges are compounded by the ever increasing
volume of data and the need for AI
of data is either inaccessible,
untrusted or unanalyzed80%
of data scientists’ time is
productively utilized – rest is spent
finding, cleaning, organizing data20%
only
of organizations are able
to get value from their data15%
only
AI
Create a trusted analytics
foundation
COLLECT
Make data simple & accessible
ORGANIZE
ANALYZE
AUTOMATE
Scale insights on demand
TRUST
Achieve trust & transparency
Apply ML everywhere
of enterprises do not yet
understand the data required
for AI algorithms
81%
IBM Cloud / © 2018 IBM Corporation

5. Top 5 Best Practices to do successful Data Monetization
2. Getting the foundation right- Infuse AI and Data Science
3. People: Data Engineers, Data Scientists, CDO and LOB Executives
4. Robust Business Model Construct- How will you charge back?
5. Trust and Ethics- Glorify in constraints of regulatory pressures and data
protection/privacy.
1. Use Case Generation and Prioritization:
Identifying your customers needs and aspirations
Five Key Recommendations to Innovate with Machine Learning and Big Data

6. 1. Use Case Generation and Prioritization
Financial
Services
Insurance
• Credit Scoring
• Fraud /Risk Analytics
• Compliance- GDPR,
PDPA etc
• Customer Segmentation
• Customer Acquisition
• Predictive credit card
churn analytics
• Customer Insights
• Network Optimization
• Data Partnerships
• Localization
• Predictive maintenance
• Loyalty programs
• Upsell/Cross sell
• Agile Supply Chain
• Next Best Offer/Action
• Connected Store
• Operational Data Store
• IoT – Stores
• Connected: Car, Plane,
Equipment
• Agile Supply Chain
• Predictive Maintenance
• IoT Data enabled
“Smart Services”
Manufacturing
Industrial
Automotive
• Border Control
• Public Safety /
Intelligence
• 360 Tax payer
• Tax Optimization
• Cyber Threat
• Citizen Self Service
• Social Services Fraud
Telco
Media
Utilities
Retail
Ecommerce
Government
Public Sector
Data Virtualization
360 view of all
your data
Enterprise Data Catalog
Shop for Data
Data Science Engine
Collaborative
Data Science

7. 2. Integrated Modern Analytics Platform
IBM Cloud Private for Data (Multi-Cloud)
Business
Users & Analysts
Data
Engineers
App
Developers
Data
Scientists
Data
Stewards
Custom
Extensions
Enterprise Cloud
Microservices
Containerized
Workloads
Multi-Cloud
Provisioning
Data & AI Microservices
Analyze Data Trust AI Infuse AIOrganize DataCollect Data
7

8. 8
3. Get the people equation right
Increases workforce productivity across the analytics lifecycle – governed seamlessly
Architects data pipelines and
ensures operability
Gets deep into the data to draw
insights for the business
Works with data to apply insights
to business strategy
Plugs into analysis and code to
build apps
DEPLOY COLLECT Data Engineer
Data Scientist
Business Analyst
App Developer
Governs data and ensures
regulatory compliance
Data Steward
CXO
Sys
Admin
Access
data
Transform:
cleanse
Create
and build
model
Evaluate
Deliver and
deploy model
Communicate
results
Understand
problem and
domain
Explore
and
understand
data
Transform:
shape
ANALYZE ORGANIZE

9. 5 X
R O I
4. Business Model- How will you charge back?
1. Start with
estimating ROI for
business.
2. Charge as-a-service
to business units.
3. Sometimes it could
be too strategic to
put dollar value.
4. External
monetization charge
as per insights
created

10. 10
Manage fluid data with built-in
protection and compliance
(e.g., GDPR)
Profile, cleanse, integrate
and catalog all types of data
AI-based Metadata
Management and Data Lineage
Persona-based experiences
with built-in industry models
Govern data lakes and data
warehousing offloading
5. Trust & Ethics
Create a trusted, business-ready analytics foundation
Containerized Integrated End to End Analytics Platform
Seamless hybrid and
- multi-cloud support
Ethical
and
Trusted
Data
IBM Cloud
Private for Data
Policy and business driven
visibility, discovery and reporting

11. Under the Hood of Data Monetization Architecture-
IBM Cloud Private for Data
2
3
IBM Cloud Private
4 5
6
1. Leverages Open Ecosystem
included but not limited to
Tensorflow, Spark, Hadoop,
kubernetes etc).
2. Role based Enterprise
Collaborative AI Ready data
platform
3. Connect to all data sources
seamlessly with Data
Virtualization
4. Use Intelligent machine
learning based Governance
Catalog
5. Manage and deploy Data
Science and ML models
6. Run in any public cloud or
private cloud

12. Benefits of choosing IBM Cloud Private for Data based
architecture
1) Deploys an information architecture for AI
2) Modernizes your data estate for a multi-cloud world
3) Makes your data ready for AI
4) Infuses AI everywhere, with confidence
5) Puts open source to work
12

13. Enabling Data Monetization for leading businesses
13IBM Cloud / © 2018 IBM Corporation
Transforming banking with HPaaS
- Hybrid Platform as a Service
Australia
High performance Computing with
IBM Cloud for VMWare
Australia
Australian Federal Government signs
a $1B agreement for Cloud & AI
Australia
Award-winning visual effect company
choses IBM Cloud (Bare Metal)
India
A big data platform to be more res-
ponsive and lay the foundation for IoT
Indonesia
Industry-first intelligent chatbot
build on Watson.
Singapore
Reinventing the shopping
experience with AI
Korea
Empowering employees with
expert knowledge with Watson
Australia
Changing their business model
with IBM Cloud Private.
Vietnam
India
Improved decision-making
with self-service analytics
Creating a digital enterprise by
leveraging Cloud & Analytics
India
First of a kind “Data Science Sandbox as
a Service” platform, built on IBM Cloud
Private for Data
Singapore

14. IBM industry leadership
The Forrester Wave
Predictive Analytics & Machine Learning
The Forrester Wave
Machine Learning Data Catalogs
The Forrester Wave
Conversational Computing Platforms
IBM
IBM
14
IBM #1 in AI
Market Share
Industry Design
Awards
Reddot
Design Awards
IBMIBM

15. Engage experts to monetize your data and get results in less then 4
weeks
IBM’s Data Science Elite team IBM Cloud Private Experiences
What do we offer?
ü Free 14 days Sandbox for IBM Cloud Private for Data.
ü Experience a 20 minute guided journey to build AI-
powered applications
ü Get hands-on with 14 days of free, hosted access and
schedule 30 mins expert consultations
ibm.biz/experienceICP4D
Ibm.com/analytics/expert-advice
Join us at APAC AI Council
An exclusive community of like minded business and technology leaders to be the first to learn about a new ideas in AI, ML
and data science space
https://goo.gl/forms/Z4funOJnWf6OFKHz2
What do we offer?
ü Free onsite engagement
ü Identify use case(s) & Minimal Viable Products via
discovery & design workshops
ü Collaboratively build & evaluate data science and
machine learning models
ü Mentor & enable client teams hands-on
www.ibm.com/analytics/
globalelite/ibm-analytics-data-science-elite-team

16. Join IBM at Gartner Symposium/ITxpo from Nov 13th-16th in Goa,
India
Learn more- https://ibm.biz/GartnerSym_web

17. 20
17