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Data Analysis Goes Wrong by
Microsoft Sr PM
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WARM-UP
Data Analysis Goes Wrong
Michael Makhlevich | Microsoft Sr PM
Michael Makhlevich
S P E A K E R
A G E N D A
2.
1.
With which data to start and how it will
end?
Where to start?
4.
3.
Summary
Did it end well?
Where to start?
Data analysis lifecycle
Get the data
Prepare the
data
Analyze the
data
Evaluate the
result
Communicate
Data analysis lifecycle
Problem Get the data
Prepare the
data
Analyze the
data
Evaluate the
result
Communicate
*simplified from Jeff Hammerbachermodel
PMs always start with the problem
PMs always start with the problem
1. Is that really a problem?
2. Is that tangible or perceptional
problem?
PMs always start with the problem
PMs always start with the problem
1. Is that really a problem?
2. Is that tangible or perceptional
problem?
3. How important is this problem?
4. Have I solved it?
PMs always start with the problem
DATA DRIVEN
DATA DRIVEN
CUSTOMER DRIVEN
DATA INFORMED
Where to start?
Where to start?
With a good question in hand
With which data to start and how it will end?
Data analysis lifecycle
Problem Get the data
Prepare the
data
Analyze the
data
Evaluate the
result
Communicate
*simplified from Jeff Hammerbachermodel
The Cobra Effect
India during British rule
Goal: #venomous cobras in Delhi
Action: bounty for every dead cobra
Result: people breed cobras to get the
bounty, not decreasing the population.
SEO
SEO
Search Engine Optimization
Adversarial data influence
Anti-facial recognition shirt Autonomous car sensing
Clever Hans
Observer effect
itself, but the nature exposed to our
-Werner Heisenberg
Observed system is affected by
the act of observation
Incentive alignment
Luis von Ahn
Consulting Professor in the Computer
Science Department at Carnegie Mellon
University
Where there's smoke, there's fire
Where there's smoke, there's fire
0
1
2
3
4
5
6
7
1 2 3 4 5 6 7
Capsule popularity
play a data game
Pre pandemic world, you are flying to ____, yay!
How would you find a great restaurant?
play a data game
play a data game
The Shed At Dulwich
#1 restaurant in London Dec 2017
play a data game
What inherently happens when you eat in a restaurant (and enjoy)?
You show off You are in a place You pay
With which data to start and how it will end?
With which data to start and how it will end?
Data rooted in reality and take incentives into
account
Did it end well?
Data analysis lifecycle
Problem Get the data
Prepare the
data
Analyze the
data
Evaluate the
result
Communicate
*simplified from Jeff Hammerbachermodel
Incentive alignment
Andrés Iniesta
Wikipedia
442 La Liga games
35 goals
86 assists
Did it end well?
Did it end well?
Do a sanity check
S U M M A R Y
2.
1.
Find data rooted in reality
Start with the problem
4.
3.
Always do a sanity check
Data effects back, understand incentives
S U M M A R Y
2.
1.
Find data rooted in reality
Start with the problem
4.
3.
Always do a sanity check
Data effects back, understand incentives
Problem Get the data
Prepare the
data
Analyze the
data
Evaluate the
result
Communicate
Stay in touch!
Michael Makhlevich | miki.makhlevitch@gmail.com
WWW.PRODUCTSCHOOL.COM
Thank You!
WWW.PRODUCTSCHOOL.COM
Part-time Product Management
Training Courses
and Corporate Training
productschool.com

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