the five myths of predictive analytics · ©2011-2012 aryng.com « the five myths of predictive...

3/6/2012

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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


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“Data to Decisions” CoursesBusiness AnalyticsPredictive AnalyticsMarketing AnalyticsGoogle AnalyticsA/B Testing

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Our Clients Include …


Agenda: Predictive Analytics Myths

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MYTH #5

“It’s the new kid in town!”


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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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


“Arranged Marriage?”

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Astrology Time and Space equation to describe any moment in terms of planets, angles and distances.

Astrology and Mathematics


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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MYTH #4

Perfect!


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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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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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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Consider Simpler Techniques Instead

Advanced Techniques

Simpler Techniques


MYTH #3

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• 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


• 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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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


MYTH #2

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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"™


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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Build and Forget?

MYTH #1


Product, pricing, policy changesCompetitive landscape changeEconomic condition changesInnovation …

Model Deteriorates Over Time!

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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


Key Take-Aways

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the five myths of predictive analytics · ©2011-2012 aryng.com « the five myths of predictive...

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