June 19-22, 2017
Chicago, IL
Delivering on the promise of data science
Click here for upcoming PAW events

All level tracks Blue circle sessions are for All Levels
Red triangle sessions are Expert/Practitioner Level


Agenda Overview – Chicago – June 2017

Pre-Conference Workshops: Monday, June 19, 2017
Full-day Workshop • Room: Salon A5
Supercharging Prediction with Ensemble Models
Dean Abbott, Abbott Analytics
Full-day Workshop • Room: Salon A3
Spark on Hadoop for Machine Learning:
Hands-On Lab

James Casaletto, MapR Technologies

DAY 1, Tuesday, June 20, 2017
(PAW Manufacturing runs in parallel on this day - dual registration required)
8:00-8:55am Registration & Networking Breakfast
Room: Salon A
8:55-9:00am Conference Welcome
Room: Salon A
Eric Siegel, Predictive Analytics World
9:00-10:00am
Keynote• Room: Salon A5
How Predictive Modelers Can Benefit from Big Data without Big Headaches
Dean Abbott, SmarterHQ
10:00-10:30am Exhibits & Morning Coffee Break
Room: Salon A
  Track 1: All Levels
Room: Salon A3
Track 2: Expert/Practitioners
Room: Salon A5
Seasonality and Other Contextual Factors Retail Analytics
10:30-11:15am Case Study: Paychex All level tracks
Retention Modeling in
Uncertain Economic Times

Mark Heiler, Paychex
Case Study: SmarterHQ
Automated Retail Analytics -
Omni-Channel and at Scale

William Komp, SmarterHQ
Thought Leadership Cross-Enterprise Deployment; Banking
11:20am-12:05pm
What is the Analytic Maturity of Your Company and Five Ways to Improve ItAll level tracks
Robert Grossman, Open Data Group
Visualization of Analytics Results - Critical for Communication
Bryan Bennett, Northwestern University
12:05-1:30pm Lunch in Exhibit Hall
Room: Salon A
1:30-2:15pm
Keynote • Room: Salon A5
The Centrality of a Detailed Understanding of your Audience
Haile Owusu, Mashable
2:15-2:35pm Gold Sponsor Presentation • Room: Salon A5
Driving high-impact business outcomes with the Art of Analytics
  Track 1: All Levels
Room: Salon A3
Track 2: Expert/Practitioners
Room: Salon A5
2:40pm-3:00pm Goverment applications Churn Modeling (for Marketing & HR)
Case Study: City of ChicagoAll level tracks
Using Data Science to Predict Water Quality in Lake Michigan's Swimming Beaches
Nick Lucius, City of Chicago
Using Survival Analytics for Predicting Churn
Pasha Roberts, Talent Analytics, Corp.
3:05pm-3:25pm Next Best Offer; Banking
Case Study: Banco Hipotecario (Bank in Argentina) All level tracks
Building Your Own Real-Time Decision System - Lessons Learned
Federico Rosenhain, Banco Hipotecario
3:25-3:55pm Exhibits & Afternoon Break
Room: Salon A
  Track 1: All Levels
Room: Salon A3
Track 2: Expert/Practitioners
Room: Salon A5
  Agile Analytics Lifetime Value; B2B
3:55-4:15pm
Case Study: Allstate InsuranceAll level tracks
Our Success with Agile Analytics
Afsheen Alam, Allstate Insurance
Case Study: Microsoft
Predicting Customer Lifetime Value for a Subscription Based Business

Chao Zhong, Microsoft
4:20-4:40pm Predictive Investing (VC)
Case Study: OpenView Venture Partners All level tracks
Predicting the Future Success of B2B Software Companies
Kwan Lee, CTO, AcademicMerit
Non-Profit Applications Crediting Scoring; Advanced Methods
4:45-5:30pm Data Science for Social Good: How Predictive Analytics Can Help Governments and Non-ProfitsAll level tracks
Lauren Haynes, Center for Data Science and Public Policy at The University of Chicago
An R Based Variable Transformation and Selection Tool for Credit Scorecards
Thomas Brandenburger, South Dakota State University
Allison Lempola, RProfet
5:30-7:00pm Networking Reception
Room: Salon A

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DAY 2, Wednesday, June 21, 2017
(PAW Manufacturing runs in parallel on this day - dual registration required)
8:00-9:00am Registration & Networking Breakfast
Room: Salon A
9:00-10:00am Special Plenary Session • Room: Salon A5
What to Optimize? The Heart of Every Analytics Problem
John Elder, Elder Research
  Track 1: All Levels
Room: Salon A3
Track 2: Expert/Practitioners
Room: Salon A5
10:00am - 10:45am Leadership/Management Modeling Methods
Case Studies: GAP, SAP, Lenovo, IBMAll level tracks
Change Management for Establishing a Data-Driven Culture
Holly Lyke-Ho-Gland, APQC
Michael Sims, APQC
Integrating Segmentation with Predictive Models-Building More Robust Solutions
Richard Boire, Environics Analytics
10:45-11:15am Exhibits & Morning Coffee Break
Room: Salon A
  Management Analytics Uplift Modeling
11:15-11:35am Case Study:Nokia
Measuring the Impact of Culture Change Using Advanced AnalyticsAll level tracks
Steven Ramirez, Beyond the Arc
Jim Whiting, Nokia
Case Study: Telenor; US Bank
Uplift Modeling: Optimize for Influence and Persuade by the Numbers

Eric Siegel, Predictive Analytics World
11:40am-12:00pm Healthcare Analytics
Early Screening for Autism By
Combining Question-Based and Video-Based Predictors
All level tracks
Halim Abbas, Cognoa
12:00-1:15pm Lunch in Exhibit Hall
Room: Salon A
1:15-2:00pm
Keynote • Room: Salon A5
Case Study: American Savings Bank
Driving Growth And Profitability Through Scoring Modeling,
Programming, and Price Optimization

Herman Jopia, American Savings Bank
2:00-3:00pm Expert Panel • Room: Salon A5
Women in Predictive Analytics: Opportunities and Challenges
Moderator: Greta Roberts, Talent Analytics, Corp.
Panelists: Jennifer Lewis Priestley, Kennesaw State University
Jeanne G. Harris, Columbia University of New York
Lauren Haynes, Center for Data Science and Public Policy at The University of Chicago
3:00-3:30pm Exhibits & Afternoon Break
Room: Salon A
  Track 1: All Levels
Room: Salon A3
Track 2: Expert/Practitioners
Room: Salon A5
Cyber Security Advanced Methods
3:30-4:15pm Case Study: Health Care Service CorporationAll level tracks
Challenges of Information and Cyber Security Using Predictive Analytics
Steven Ulinski, Health Care Service Corporation
Case Study: Louisiana State Uni. & Louisiana Dept of Corrections
How to Revolutionize Your Model Optimization
Edward Shihadeh, Auspice Analytics
4:15-5:00pm Deployment Considerations Best Practices
Case Study: National Consumer Panel All level tracks
Combining Inferential Statistics with Predictive Modeling to Evaluate Changes in Your Business

Thomas Schleicher, National Consumer Panel
Q&A: Ask Dean and Robert Anything (about Best Practices)
Dean Abbott, SmarterHQ
Robert Grossman, Open Data Group

Post-Conference Workshop: Wednesday, June 21, 2017
Three hours: 5:30-8:30pm • Room: Salon A4
R Bootcamp: For Newcomers to R
Max Kuhn, RStudio

Post-Conference Workshops: Thursday, June 22, 2017
Full-day Workshop • Room: Salon A1
R for Predictive Modeling: A Hands-On Introduction
Max Kuhn, RStudio
Full-day Workshop • Room: Salon A5 The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes

John Elder, Elder Research, Inc.
Full-day Workshop • Room: Salon A4
Advanced Methods: Data Preparation and Modeling Techniques
Dean Abbott, Abbott Analytics

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