Sharing my presentation from the Predictive Analytics conference. Thanks to all the attendees for the great response! If you are looking to monetize your data, take a look and reach out if this is of interest. Would love to help you out!

1. Shikha Verma
Nature Lover, Data & Analytics Leader & Advisor
Data Monetization
&
Money Making Analytics

2. Let’s get to know all you data heros!
 Quick Intro, company, one place you’d rather be
 Do you monetize your data? Examples?

3. Who am I?
 Data Analytics Leader, Advisor, Speaker, Nature Lover
 Formerly, Sr. Director – Data Insight & Analytics,
Central Garden & Pet
 Pre-Formerly, Director – Information Management & BI,
Symantec Corporation
 Pre-Pre… Boy I’m old – Principal with Knightsbridge, PCS
 Let’s connect!
LinkedIn: http://www.linkedin.com/in/shikhaverma
Email: shikha.verma.now@gmail.com
Twitter: @_shikha_verma_

4. I’d rather be here! Ah… Machu Picchu!

5. Data Monetization
 Generating revenue from the data you are creating, collecting
and/or aggregating
 Potential – huge in most industries
 Watch-outs – privacy, security, data ownership
 Is it for you? – My Data Monetization article on LinkedIn
* Selling or trading
data externally
* Creating data
services and
products
Direct
Monetization * Improving
efficiency internally
* Reducing risk
* Optimizing
operations
Indirect
Monetization

6. What are Money-Making Analytics?
 Analytics that help you create new revenue streams, make more money off
existing revenue streams or save money
 Money-Making Analytics harness indirect monetization capabilities and lead to
direct monetization
 Read more – My Money-Making Analytics article series on UPSIDE.COM (TDWI)

7. Let’s think of that for a second, standing in the Salt Flats in Bolivia!

8. Example – High Tech
 Background: Acquisition inquisitive large tech company,
big and diverse product portfolio, different go to market
strategies, huge data and process disparity across the
acquired entities
 Challenge/Opportunity: Money being left on the table
with customers for License renewals
 Monetization Potential: Over $60M

9. Example – Consumer Retail
 Background: Acquisition oriented large consumer retail
products company, diverse product portfolio, data and
process disparity across the acquired entities, several
plants, distribution centers, locations across US
 Challenge/Opportunity: Inventory optimization
 Monetization Potential: Over $100M

10. Example – Financial Services
 Background: Fin Tech online startup in the consumer
finance management, lending and mortgage industry,
rapid silo’d growth, no integration across
businesses/products
 Challenge/Opportunity: Cross-sell and partner
enablement
 Monetization Potential: Over $50M

11. Hmm…
 How do we find such opportunities in our company?
 How do we decide whether direct or indirect is the way
to go?
 What kind of money-making analytics would make sense
to deploy?
 How do we find out the size of the prize?
 How to get alignment across the company on moving
forward with such initiatives?

12. What a kaleidoscope of questions, just like the Rainbow mountains in China!

13. Money-Making Analytics – How to
find that rainbow?
Analytics
Strategy
Technology
that fits
Action-
oriented
framework
Collaborative
enterprise

14. Analytics Strategy
 What: Analyze Market, Company Strategy, Business
value opportunities and current value leakages. Pick
the biggest enablers
 How: Top down and bottoms up
 Sample questions
 Examples:
 License Renewals
 Customer Shipments
Strategy
•Market Share
•Differentiation
•Company Strategy
Operations
•Handshakes
•Goals
•SWOT
Nuts and
Bolts
•Key Decisions
•Roadblocks
•Opportunities

15. Technology that fits
 What: Evaluate the Technology & Data landscape, Data
Quality and Culture. Pick technology that enables the
culture.
 How: Wide and deep, Internal and external data sources
 Sample approach
 Examples:
 Spreadsheets or not
 Data quality

16. Action Oriented Framework
 What: Create your analytics tools in a way that enable
taking data-driven action across the organization
 How: Institute tools and process where
action/decision/steps are needed in the organization
 Sample approach

17. Collaborative enterprise
 What: Setup framework that enables collaboration
across the organization.
 How: Institute a cadence across the organization,
enable collaborative action
 Sample structure
 Examples:
 Retail
 High Tech

18. Now you can wander off into the sunset in the African Savannah!

19. Audience Poll again
 Did this presentation spark any ideas?
 Any new Monetization opportunities that come to mind?
 Follow-up conversations

20. Thank you for your time!
Here you can actually go this weekend, Mt. Diablo!
LinkedIn: http://www.linkedin.com/in/shikhaverma
Email: shikha.verma.now@gmail.com
Twitter: @_shikha_verma_