This workshop was conducted at AdTech Bangalore where the speaker walked through how data can be made actionable for business.

1. How to make data actionable for business?
Workshop Sponsored by
Speaker: Ravi Padaki

2. How to make data actionable for business?
Torture the numbers until they confess!

3. Agenda
• Who is this for?
• What is this about and not about?
• Planning for Data
• Actionable Data for Business Framework
• Hands-on examples
• Key Takeaways

4. What do I mean by Data?
Data {noun}: reporting and analytical products, services
or solutions

5. Who is this for?
Creators of Data Consumers of Data
products/services products/services
Data {noun}: reporting and analytical products, services or solutions

6. What you will get out of this?
Creators Consumers
• Skilled in providing • Skilled in articulating
better insights needs for analytics
• Skilled in designing • Skilled in sponsoring
data that is contextual analytical capabilities
to the user in your organization

7. What is this about?
Structure to develop Structure to consume
• Data Strategy data
• Alignment • For faster decision
• Differentiation making
• ROI
• Data Planning
• Data Design

8. What is this not about?
• Data Mining and Warehousing Technology
• Evaluation of Statistical and analytical models
• Exploratory data analysis

9. When do you start planning for data?
Proactive
Start early!
Reactive
Product Product
Launch Support
Strategy Roadmap

10. Why is this topic important?
Analytics
Research
People
What
Storage &
Compute percentage of
revenue is
driven from
data and
analytics?
Value for Business?

11. The Data Pyramid
Analytics
(Intelligence)
Value
Reporting
(Information)
Raw Data

12. General Observations
• Give me all the
Raw Data
metrics you have
(because I don’t know
what I am looking Reports
for!)
Analytics
• So much data and yet
no insights!
• Great Insight, so
what?

13. Path to Data Driven Business Decisions
DECISION DECISION
How quickly can you collapse the path to decision?

15. The Actionable Data for Business Framework
Business Goal
Decisions
Task 1 Data Set 1
Task 2 Data Set 2
Task 3 Data Set 3
Task 4 Data Set 4
What if we ask the Question:
What data do you need…?
… to complete your business task?
… to achieve your business goal?

16. Map Data to Business Decisions
What data do you
need…? Data
… to complete your
Business
business task? Task
… to achieve your
Business
business goal? Goal

17. Example – Imagine you’re a BMW car dealer
Increase sales
Decisions
Manage Pricing Data Set 1
Target buyer Data Set 2
Analyze demand by
inventory Data Set 3
Manage inventory Data Set 4

18. Example – Imagine you’re a BMW car dealer
Increase sales
Analyze
Manage
Manage pricing Target buyer demand by
Inventory
inventory
How are my Who has been What have
How much is
current offers buying from me customers been
remaining/sold?
doing? so far? buying?
How much How is BMW Which series is
How much do I
discounts will faring in my poised to sell
need?
spur sales? demog? fast?
Who are my
most valued
personas?

19. Creators of Data
Increase sales
Decisions
•Design data for quick
Manage Pricing Data Set 1
insights
Target buyer Data Set 2 •Provide right data to the
right user at the right time
Analyze demand by
inventory Data Set 3 •Study gaps in analytical
capabilities to deliver
superior insights
Manage inventory Data Set 4

20. Consumers of Data
Increase sales
Decisions
Manage Pricing Data Set 1 • Get to decisions faster
• Articulate questions to
Target buyer Data Set 2 empower decision making
• Sponsor/champion for
Analyze demand by
inventory Data Set 3 closing gaps in analytical
capabilities
Manage inventory Data Set 4

21. Business Goals – Tasks
Goal 1 Goal 2 Goal 3
Task 1 Task 3 Task 5
Task 2 Task 4 Task 6

22. Business Goals can have Overlapping Tasks
Goal 1 Goal 2 Goal 3
Task 1 Task 1 Task 2
Task 2 Task 3 Task 4

23. Benefits of this framework
• Data is Meaningful and Actionable
• Data is Relevant and Contextual
• Decision Making is Easier and Faster

24. Analytical Capabilities
Past Present Future
Information What happened? What is What is going to
happening? happen?
Analytics Features Reports Alerts Forecasts
Insight How and why did Why is it What might
it happen? happening? happen?
Analytics Features Modeling Recommendations Prediction and
Optimization
Source: Thomas Davenport, Jeanne Harris, Robert Morison from the book Analytics at Work

25. Analytical Capabilities
Predictions
Recommendations
Forecasts
Performance
Reports
Raw data

26. Hands on assignment

27. Your Key Takeaways!
• Plan Data Early
• Make data work for you!
• Map data needs to business tasks and goals

28. Thank you!