shapeup.com Copyright 2015 ShapeUp Inc.All Rights Reserved. Proprietary & Confidential

Samir A. BatlaDirector, BI & Data AnalyticsJohanna KincaidData Scientist

PREDICTING ENROLLMENT IN HEALTH & WELLNESS PROGRAMS

OUR MISSION UNITE EMPLOYEES TO MAKE WORKPLACES HEALTHIER, HAPPIER, AND MORE SUCCESSFUL

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OUR HISTORY

Drs. Rajiv Kumar and Brad Weinberg founded ShapeUp in 2006 while studying at Brown Medical School

Launched initially as a non-profit community challenge called Shape Up RI, their social wellness idea went viral and reached over 10% of the adult population in Rhode Island

Six outcome-based studies and 600 customers later, ShapeUp now serves 10 Fortune 50 and more than twenty Fortune 500 companies worldwide

ShapeUp operates in 138 countries and is translated into 25 languages, reaching 1.6 million participants globally

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WHAT IS PREDICTIVE ANALYTICSMany definitions, that include:

• Data Mining

• Machine Learning

• Advanced Analytics

• Artificial Intelligence

• Etc.

The practice of analyzing existing data to make predictions about the future.

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INSIGHTS FROM ANALYTICS• Predict enrollment, engagement,

activity

• Gain deeper population insight• identify trends• influencing attributes

• Drive strategic decision making• Address under-performing areas• Reward above average performance

• Score participants to assess their likelihood of meeting milestonesThe things we can learn from predictive analytics will allow us to design

better competitions and programs to meet our mission of making healthier, happier and more successful workplaces

We have just embarked on our journey – we did an experiment to predict future competition enrollment.

We focused on three predictive attributes:

•Postal Codes•Divisions•Labor Codes (Unions, non-Unions)Why these three variables? Answer is simple – completeness. Next: were any missing attributes significant?

Trained model on previous enrollments to predict enrollment in 2015

PREDICTIVE ANALYTICS AT SHAPEUP

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TRAINING DATA

Labor Code

Division

Postal Code

2013 2014

100 XYZ 90210 1 0100 ABC 02903 1 1200 XYZ 60601 0 1300 123 94102 0 0100 321 90210 1 1

2015?????

Trai

ning

Dat

a

Variables Classifications

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PROCESS

Training Data2 yrs; ~ 350k

Classifications

New Data~ 200k

New Classification

Exploratory Data Analysis / Algorithm Development

Predictive Model

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ENROLLMENT BY LABOR CODECo

unts

Non-union

What’s happening here?

Labor Code

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ENROLLMENT BY LABOR CODE

Zero Enrollment

Non-union

Log(

Coun

t)

Labor Code

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ENROLLMENT BY POSTAL CODELo

g(Co

unt)

Postal Codes (first two)

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ENROLLMENT BY POSTAL CODE YOY

13

ENROLLMENT BY DIVISIONLo

g(Co

unt)

Divisions

Zero Enrollment100% Enrollment

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MODEL PERFORMANCE – UNTIL THINGS CHANGEYears of Training Data Training Predicted Actual Error %

2

1

.5549871

.5354515

.6206801

.6510264

.6192993

.6192993

0.14%

3.17%

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BEWAREUnknowns unknowns.

But predictive analytics is not a dubious endeavor. It’s flawed when it’s overly-complex. What we don’t want to do is make guarantees; however, we can, in fact, use it to understand what’s happening, what might happen and drive decision making.

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IN CLOSING…Predictive Analytics is helping ShapeUp:

Help our customers understand their population and prepare for future programs and competitions

Better understand book-of-business customer populations to design and offer new products that aren’t obvious

Enrich the relationship between Account Managers and customers – become consultative

More questions are coming to light

Understand Data

Prepare Data

Model Data

Evaluate

Deploy

Monitor

Business Goal

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PARTICIPANT SENTIMENT

“It help shift a focus of care for our employees. Also, when our employees are healthier they function better at their jobs.”“I like that we do this as a company...working with others is always easier....Thank you!”“Company giving those employees, who wish to participate, an opportunity to improve their health. Thank You!”

THANK YOU!shapeup.com