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UNSW Data Science Society
Lucy Bailey
12Jun19
WHY?
Data Driving Business Value
Data Culture
7 key elements
Critical success factor
= Aligned to Vision
2
Theory
Data vs Information vs Knowledge
Why the ‘Why’ is important
How to Guide
Q&A
Practice
3
Agenda
Theory
Data vs Information vs Knowledge
Why the ‘Why’ is important
How to Guide
Q&A
Practice
4
Agenda
Part 1
Shout out your height
Observations
Data = Raw Material
Part 2
Stand in height order
Observations
Information = Usable
How could it be used
Observations
Knowledge = Valuable
Part 3
“Science is the study of the nature
and behaviour of natural things
and the knowledge that we obtain
about them.” collinsdictionary
“Scientist is someone who
systematically gathers and uses
research and evidence, making a
hypothesis and testing it, to gain
and share understanding and
knowledge.” sciencecouncil.org
Data Science
Why Data Science?
Data
• Raw Material
Science
• Latin ‘Scire’ to know
Scientist
• Knowledge Broker
1
2
3
9
Recap
Data is just a raw material
Value derived when information is applied
Data Scientist are Knowledge Brokers
Theory
Data vs Information vs Knowledge
Why the ‘Why’ is important
How to Guide
Q&A
Practice
10
Agenda
Golden Circle - Simon Sinek
11
Simon Sinek
Golden Circle
WHAT – everyone knows
HOW – most people know
WHY – few people know
What
How
Why
WHAT did we do?
HOW did we do it?
WHY did we do it?
Outside In
What
How
Why
WHY doing it?
HOW to do it?
WHAT would we do?
Inside Out
What
How
Why
1
2
3
15
Recap
People buy WHY, not How
Inspired leaders start with WHY
Starting with WHY > better WHAT
Theory
Data vs Information vs Knowledge
Why the ‘Why’ is important
How to Guide
Q&A
Practice
16
Agenda
How to Guide
1. Understand strategic
context
2. Define value aligned to
goals
3. Ensure value delivery
Economic
EnviroSocial
S W
O T
1. Strategic Context
a. Internal Strengths &
Weaknesses
b. External Opportunities &
Threats
c. 4 categories initiating
Objectives
Survive
Continue
Combo
Grow
2. Aligned to Goals
a. Identify goals that will
benefit
b. Define and quantify the
value
c. Prioritise by value
Business
Value
Under-
stand
Data
Prepare
Data
Model
Data
Evaluate
Model
Deploy
Measure
3. Deliver Value
a. Start and end with
business value
b. Collaborate with
business users
c. Monitor throughout &
reprioritise
Start
& End
Collaborate
Monitor
1
2
3
21
Recap
What are the strategies and why
Align to goals and quantify net value
Start and end with value, monitor & reprioritise
Theory
Data vs Information vs Knowledge
Why the ‘Why’ is important
How to Guide
Q&A
Practice
22
Agenda
Theory
Data vs Information vs Knowledge
Why the ‘Why’ is important
How to Guide
Q&A
Practice
23
Agenda
Orange Sky
Theory
Data vs Information vs Knowledge
Why the ‘Why’ is important
How to Guide
Q&A
Practice
25
Agenda
1
2
3
26
Recap
Key take outs?
What do you pledge to do?
Feedback?
www.escient.com.au
Lucy Bailey
Principal Consultant
lucy.bailey@escient.com.au

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