The Bull, The Bear and The Planets: Trading the Financial Markets Using Astrology
The Five Myths of Predictive Analytics...Astrology Time and Space equation to describe any moment in...
Transcript of The Five Myths of Predictive Analytics...Astrology Time and Space equation to describe any moment in...
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« The Five Myths of Predictive Analytics » 1©2011-2012 Aryng.com
The Five Myths of Predictive Analytics
Piyanka JainPresident & CEO, Aryng Inc.
@AnalyticsQueen #PAWCON
email: [email protected]
Aryng.com/whitepaper.html
« The Five Myths of Predictive Analytics » 2©2011-2012 Aryng.com
Analytics Training for
Business Impact
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Onsite Training & Mentoring
Onsite Training & Mentoring
Strategic Analytics
Consulting
Online Training
“Data to Decisions” CoursesBusiness AnalyticsPredictive AnalyticsMarketing AnalyticsGoogle AnalyticsA/B Testing
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« The Five Myths of Predictive Analytics » 3©2011-2012 Aryng.com
Our Clients Include …
« The Five Myths of Predictive Analytics » 4©2011-2012 Aryng.com
Agenda: Predictive Analytics Myths
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« The Five Myths of Predictive Analytics » 5©2011-2012 Aryng.com
MYTH #5
“It’s the new kid in town!”
« The Five Myths of Predictive Analytics » 6©2011-2012 Aryng.com
When was the first application of Predictive Analytics?
A. 1960’s – Advent of computing powerB. 1930’s – Wall street crashC. 19th century – Birth of science as professionD. Before 15th century
Trivia
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« The Five Myths of Predictive Analytics » 7©2011-2012 Aryng.com
Predictive Analytics Coming of Age
1930 – Econometric society
1965– Computing power with IBM 360
1977 – Oracle’s commercial Relational Database
2000 – 2010: Narrowing of algorithms
2011: PA hits mainstream
First credit score model by
Fisher and Durand
« The Five Myths of Predictive Analytics » 8©2011-2012 Aryng.com
“Arranged Marriage?”
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« The Five Myths of Predictive Analytics » 9©2011-2012 Aryng.com
Astrology Time and Space equation to describe any moment in terms of planets, angles and distances.
Astrology and Mathematics
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Mathematical Calculation
36 predictive attributes
to describe a person
Bride: 36 Attributes
Groom: 36 Attributes
Higher the overlapping
attributes, greater the probability of
good match
Predictive Model and Arranged Marriages
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« The Five Myths of Predictive Analytics » 11©2011-2012 Aryng.com
MYTH #4
Perfect!
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Even the best model has tons of misclassification
Trying to predict “greens”
11 3
2 13
Green
Red
Green Red
Actual
Pre
dict
ed
Models Are Not Perfect
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« The Five Myths of Predictive Analytics » 13©2011-2012 Aryng.com
Model predicts by looking at likely-hood
Income > $40,000
Renter High Debt
Bad Risk Good Risk Bad Risk Good Risk
Yes
Yes No
No
Yes No
Model Prediction Is an Estimation
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« The Five Myths of Predictive Analytics » 15©2011-2012 Aryng.com
Is always the best
technique!
MYTH #4
Predictive Analytics and Testing 16Copyright ©2011-2012 Aryng
When Not to Use Predictive AnalyticsCONSTRAINTS
Organizational Support, Opportunity Size
MONTH 1 MONTH 2 MONTH 3
FT 1 FT2
Historical Data and Minimum responders
Response
No Response
Required Accuracy of Prediction
Is ROI positive? Commitment for
actionability?
Need more accuracy?
Is minimum count
available?
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Predictive Analytics and Testing 17Copyright ©2011-2012 Aryng
Consider Simpler Techniques Instead
Advanced Techniques
Simpler Techniques
Predictive Analytics and Testing 18Copyright ©2011-2012 Aryng
MYTH #3
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Predictive Analytics and Testing 19Copyright ©2011-2012 Aryng
• Data specification and pull• Data cleaning and
preparation• Variable transformation and
selection• Model training and validation• Choosing the best model
based on business context
No “Press a Button” Solution
« The Five Myths of Predictive Analytics » 20©2011-2012 Aryng.com
• Data Scientist?• Needs qualified analyst with
hands-on experience in modeling
Model Building Needs Skills
Predictive Analytics Overview
Hands-on training
(commonly used techniques)
Build Models with access to mentors
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« The Five Myths of Predictive Analytics » 21©2011-2012 Aryng.com
Commonly Used Predictive and Advanced Techniques
Logistic Regression
Linear Regression
Decision Tree
Other techniques: Clustering (K-means), PCA, Factor Analysis, Time Series, Survival Analysis, Neural Network
« The Five Myths of Predictive Analytics » 22©2011-2012 Aryng.com
MYTH #2
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« The Five Myths of Predictive Analytics » 23©2011-2012 Aryng.com
STEPS
Effective Predictive Analytics Framework
2. Analysis
Plan
3. Data
Collection
4. Build
Model/ Derive
Insights
5.Recommendations
1. Business Question
f r o m i n q u i r y t o i n s i g h t s
f r o m i n s i g h t s t o i m p a c t
BADIR™: 5 steps from "data to decisions"™
« The Five Myths of Predictive Analytics » 24©2011-2012 Aryng.com
Predictive Analytics Using BADIR Process
ProblemOffering all products to all customers led to Bad Customer Experience and Wasted Marketing $.
Results
Reduced marketing spending by 70%Delivered incremental profits of $20M+
Process to solutionUsing BADIR process, we built the Next Best Product Recommendation Model optimized for adoption & profit.
STEPS2. Analysis
Plan3. Data
Collection4. Build
Model/Insight5.Recommen
dations1. Business Question
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« The Five Myths of Predictive Analytics » 25©2011-2012 Aryng.com
Build and Forget?
MYTH #1
« The Five Myths of Predictive Analytics » 26©2011-2012 Aryng.com
Product, pricing, policy changesCompetitive landscape changeEconomic condition changesInnovation …
Model Deteriorates Over Time!
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« The Five Myths of Predictive Analytics » 27©2011-2012 Aryng.com
STEPS
BADIR Framework and Model Tweaks
2. Analysis
Plan
3. Data
Collection
4. Build
Model/ Derive
Insights
5.Recommendations
1. Business Question
f r o m i n q u i r y t o i n s i g h t s
f r o m i n s i g h t s t o i m p a c t
C l i m a c t i c C h a n g e
N e w P o l i c i e s
P r o d u c t C h a n g e s
« The Five Myths of Predictive Analytics » 28©2011-2012 Aryng.com
Key Take-Aways
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« The Five Myths of Predictive Analytics » 29©2011-2012 Aryng.com
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