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SEPTEMBER 30 – OCTOBER 4 ● BOSTON, MA

CONFERENCE GUIDE

Scott NicholsonChief Data ScientistAccretive Health (formerly of LinkedIn)

Robert JewellDir. Global Bus Dev & PartnershipsIBM Watson Solutions

Anne RobinsonDir. of Supply Chain Strategy & AnalyticsVerizon Wireless

Marc SmithChief Social Scientist Connected Action Consulting Group

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Welcome

Welcome to Predictive Analytics World!You have come to the leading business event, loaded with predictive analytics case studies, expertise and resources. This conference brings professionals and experts together to keep predictive analytics on a forward trajectory, strengthening the impact delivered and establishing new opportunities.

PAW is a part of Data Driven Business Week. This multi-conference “überevent” spans topics in analytics and beyond, reflecting the growing importance and visibility of the industry. You benefit from this cross-pollination by access to cross conference expositions, shared workshops, and cross-registration options.

Each of the millions of business decisions driven by analytics are based on concrete evidence and sound mathematics. That is truly an upgrade to the way we do business. And everywhere you turn, this upgrade is installed in new, innovative ways by driving different types of operational decisions with the scores produced by predictive models. PAW’s extensive array of case studies prove that these innovations deliver.

Enjoy, take advantage, and have a great conference!

Sincerely,

Eric Siegel Ph.D.Program ChairPredictive Analytics World

Predictive Analytics World Stay Engaged

Connect with your peers, the latest conference news and more on social media:

Twitter: @PAWConConference Hashtag #PAWConFacebook: facebook.com/PAWConLinkedIn Group: Predictive Analytics World

ContentsAgenda Overview .......................... 2

Conference Workshops .................. 7

Conference Floorplan .................... 8

Session Descriptions .................... 10

Workshop Descriptions ............... 20

Keynote Bios ................................. 26

Exhibitors Floorplan ..................... 28

Sponsors ........................................ 29

Sponsor Profiles ............................ 31

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FREE WIFI


DAY 1: Monday, October 1, 2012

7:30-9:00am Registration & Breakfast l Room: Commonwealth Hall

9:00-9:45am

Keynote l Room: Harborview Ballroom 2 & 3

Case Study: LinkedIn and Accretive HealthBeyond Big Data: Better Living Through Data Science

Scott Nicholson, Accretive Health (formerly of LinkedIn)

9:45-10:05am

Gold Sponsor Presentation l Room: Harborview Ballroom 2 & 3

Raising the Bar for Predictive Analytics Deployment: The Newest TechniquesJason Verlen, IBM Software Group

10:05-10:15am


Modeling Renewal Probability in Order to Boost it at TripAdvisorMichael Berry, TripAdvisor

10:15-10:40am Breaks / Exhibits l Commonwealth Hall

Track 1: All Levels Room: Harborview Ballroom 1

Track 2: Expert/Practitioners Room: Harborview Ballroom 2 & 3

10:40-11:25am

Thought Leadership HR Analytics

The Practical Data Scientist l

Dan Woods, Evolved Media and a Forbes Contributor

Case Study: U.S. Special Forces sHiring and Selecting Key Personnel

Using Predictive Analytics Dean Abbott, Abbott Analytics, Inc.

11:30am-12:15pm


Charting Collections of Connections in Social Media: Creating Maps and Measures with NodeXL

Marc Smith, Connected Action Consulting Group

12:15-12:30pm

Platinum Sponsor Presentation l Room: Harborview Ballroom 2 & 3

Managing Forward: Analytics For Today’s Multi-Channel, Multi-Device Consumer

Eric Feinberg, ForeSee

Agenda Overview

l FOR ALL LEVELS s FOR ExPERT/PRACTITIONERS


Agenda Overview

12:30-12:45pm

Lightning Round of 2-Minute Sponsor Presentations l Room: Harborview Ballroom 2 & 3

12:45-1:40pm Lunch / Exhibits l Room: Commonwealth Hall

1:40-2:25pm


Case Study: VerizonInfluencers, Skeptics, and Data Geeks:

Using Analytics to Drive Organizational ChangeAnne G. Robinson, Verizon Wireless

2:25-2:55pm


How Big Data Delivers a Competitive AdvantageKent McCormick, Lattice Engines



3:00-3:45pm

Big Data Self-Updating Models

Big Data and Big Analytics Trends: The Promise and the Hype l

Gregory Piatetsky-Shapiro, KDNuggets

Case Study: Penske sMarketing Mix Optimization:

Forecasting and Decision Making Under Uncertainty

Chris Dickey, The Martin AgencyDavid Henkel, Penske

Neeraj Kulkarni, Martin AgencyJohn Busbice, MIDA

3:50-4:10pm

Predictive Project Management Market Mix Optimization

Case Study: Tangent Design Engineering l Applying Predictive Analytics to

Improve Project Management Brett Bender, LiquidPlanner

Case Study: Ace Cash Express sData Driven Modeling

Senthil Ramanath, Ace Cash Express

Sponsored LabCase Study: Predicting Sales through Brand Research Data

Closing the Chasm Between Marketing and SalesAmitabh Bose, WNS Global Services

4:10-4:35pm Breaks / Exhibits Room: Commonwealth Hall



Agenda Overview



4:35-5:20pm

PA for Financial Regulations Healthcare Analytics

Case Study: Goldman Sachs l

Utilizing Predictive Analytics to Analyze Changing Regulation

Vikas Agrawal, Goldman Sachs

Case Study: Pfizer sRight Medicine, Right Patient

Max Kuhn, Pfizer

5:25-6:10pm

Economic Research and Forecasting Clinical Healthcare

Case Study: Rebellion Research l

Applying Machine Learning to Global Economics

Alexander Fleiss, Rebellion Research

Case Study: Sisters of Mercy Health Systems sFramework for Detection of Clinical

States & Disease Onset Using Electronic Health Record (EHR) Data

Jeni Fan & Juergen A. Klenk, Booz Allen Hamilton

6:10-7:30pm Reception / Exhibits l Room: Commonwealth Hall

7:30-10:00pmBoston Predictive Analytics Meet Up l Room: Harborview Ballroom 1

Lightning Talks: Data Deluge!, U.S. Jobs Outlook, D3 DataViz, R Data Mining, Random Forests

DAY 2: Tuesday, October 2, 2012

8:00-9:00am Registration & Breakfast l Room: Commonwealth Hall

9:00-9:45amKeynote l Room: Harborview Ballroom 2 & 3

Putting IBM Watson to Work

Robert Jewell, IBM Watson Solutions

9:45-10:05am


Forensic Analytics – Discover Insights That Can Help You Move ForwardCarol Tannous, Deloitte Financial Advisory Services LLP

10:05-10:40am Breaks / Exhibits l Room: Commonwealth Hall

10:40-11:25am

Expert Panel l Room: Harborview Ballroom 2 & 3

Big Data for Predictive AnalyticsModerator: Eric Siegel, Ph.D., Predictive Analytics WorldSatish Lalchand, Deloitte Financial Advisory Services LLP

Jason Verlen, IBM Software GroupEric Feinberg, ForeSee



Agenda Overview

11:30-11:40am Lightning Round of 2-Minute Sponsor Presentations l Room: Harborview Ballroom 2 & 3

11:45am-12:30pm

Sponsored Labs Room: Harborview Ballroom 2 & 3

Lab Session Live Topical Demo

Building Customer Relationships Through IBM SPSS Predictive Analytics l

Tom Hamilton, ING U.S.Jason Verlen, IBM Software Group

12:30-1:30pm Lunch / Exhibits l Room: Commonwealth Hall

1:30-2:15pmSpecial Plenary Session l Room: Harborview Ballroom 2 & 3

Becoming an Ace with a Robot as your Wingman! John Elder, Elder Research, Inc.

2:20-2:25pm


Quest for Big InsightSanjit Bhoumick, WNS Global Services



2:30-2:50pm

Sales Force Optimization True Lift Modeling

Case Study: Hewlett-Packard l

Sales Productivity Analysis - Optimizing Time Spent to Attain Maximum Returns for Sales Reps

Guruprasad Srinivasan and Subhamitra Chatterjee, Hewlett-Packard

Case Study: Staples sTrue-Lift Modeling: Mining for

the Most Truly Responsive Customers and Prospects

Jane Zheng, Focus Optimal

2:55-3:15pm

Predicting B-2-B Buying

Case Study: Hewlett-Packard l

Behavioral Analysis of Account Purchases and Their Predictability Govindarajan Krishnaswamy, Aparna Seshadri

and Ronobijay Bhaumik, Hewlett-Packard

3:15-3:55pm Breaks / Exhibits l Room: Commonwealth Hall



Agenda Overview



3:55-4:15pm

Financial Services Detecting Cannibalization

Case Study: Commerzbank, Lloyds, Ursus Advisors l

Optimization in Financial ServicesFrank Bria, Tower Group

Case Study: TripAdvisor sCannibalization Analysis Using Matched Pairs at TripAdvisor

Michael Berry, TripAdvisor 4:20-4:40pm

Vendor Recommendations(Beyond Product Recs)

Case Study: Intuit and Mint l

Restaurant Recommendations Using Financial Likeness

Saikat Mukherjee, Intuit

4:45-5:30pm

Crowdsourcing Data Mining Customer Valuation

Machines Learn, But Can They Teach? l Anthony Goldbloom, Kaggle

Case Study: United Group Holdings sValue Proposition

Segmentation (VPS) Methods

Amjad Zaim, Cognitro Analytics



Conference Workshops


Conference Workshop: Tuesday, October 2, 2012

THREE HOUR WORKSHOP s

6:30-9:30pmR Bootcamp: For Newcomers to R

Room: Washington

Max Kuhn, Pfizer

Post-Conference Workshops: Wednesday, October 3, 2012

FULL-DAy WORKSHOPS s

9:00am-4:30pm

R for Predictive Modeling: A Hands-On IntroductionRoom: Washington

Max Kuhn, Pfizer

Modeling Methods: The Best and the Worst of Predictive AnalyticsRoom: Harborview Ballroom 1

John Elder, Elder Research, Inc.

Post-Conference Workshop: Thursday, October 4, 2012

FULL-DAy WORKSHOP s

9:00am-4:30pm

Advanced Methods Hands-On: Predictive Modeling TechniquesRoom: Cambridge 1

Dean Abbott, Abbott Analytics

Workshop sponsored by:

Post-Conference Workshop: Friday, October 5, 2012

FULL-DAy WORKSHOP l

9:00am-4:30pm Making Text Mining Work: Practical Methods and Solutions

Room: Back Bay

Andrew Fast, Elder Research Inc.


Conference Floorplan


Monday, October 1, 2012

7:30-9:00am v Room: Commonwealth Hall

Registration & Breakfast

9:00-9:45am v Room: Harborview Ballroom 2 & 3

Keynote

Case Study: LinkedIn and Accretive Health

Beyond Big Data: Better Living Through Data ScienceThe ‘big data’ theme is overrated and can be misleading. Ultimately data and data analytics cannot get you completely over the finish line; you also need a combination of asking the right questions, context/product intuition, and in some cases an understanding of the psychology behind decision-making. This end-to-end ownership and expertise are the role of the data scientist, and help your big/huge/fat data achieve the inflection point that leads to big insights. Using lessons from consumer internet (LinkedIn and online advertising), health care analyt-ics (Accretive Health) and behavioral economics, we will discuss examples of how the combination of data science and different representations of ‘big data’ generate insights that help people make better decisions about their lives.

Speaker: Scott Nicholson, Chief Data Scientist, Accretive Health (formerly of LinkedIn)


Gold Sponsor Presentation

Raising the Bar for Predictive Analytics Deployment: The Newest TechniquesAlthough the use of predictive analytics has come a long way in recent years, it is clear that there are now much higher expec-tations for wider and more accurate deployment methods. So while more organizations see the value of analytics, few are comfortable with their current tools and abilities to create and deploy useful solutions. In this session we’ll explore the very newest techniques and capabilities that have emerged to help

you ingrain predictive analytics into the DNA of your organiza-tion, and deploy solutions that empower your team to make the right decisions and consistently deliver the best results.

Speaker: Jason Verlen, Director, SPSS Product Strategy & Management, IBM Software Group



Modeling Renewal Probability in Order to Boost it at TripAdvisor Speaker: Michael Berry, Analytics Director, TripAdvisor


Breaks / Exhibits

Session Descriptions



10:40-11:25am v Room: Harborview Ballroom 1

Track 1: Thought Leadership

The Practical Data Scientist l

The term Data Science has been derided as hype wrapped around the traditional role of the analyst. But if we look at the type of data we have today, the software we use to manipu-late it, and the wide range of statistics, machine learning, and analytics tools at our disposal, it is fair to say that we are in a new world. Based on more than 20 interviews with top data scientists and a variety of other research, Dan Woods, CTO, Chief Editor/Analyst and Founder, Evolved Media, and a Forbes Contributor.com and a contributor to Forbes.com, defines a practical approach to data science, one focused on experimen-tation, gradual development of skills, and achieving business value. Woods defines a reference model for data science, explores various types of maturity models, suggests organi-zational structures, and reviews technology that allows for a quick start without a large budget.

Speaker: Dan Woods, CTO, Chief Editor/Analyst and Founder, Evolved Media, and a Forbes Contributor


Track 2: HR Analytics

Case Study: U.S. Special Forces s

Hiring and Selecting Key Personnel Using Predictive AnalyticsHiring and selection of personnel in specialized work environ-ments incurs huge direct and opportunity costs for organiza-tions. One of the largest challenges is that the selection process is often left in the hands of those with either high experience in the domain area but little experience in selection or vice versa.

Predictive Analytics and statistics can play a critical role in formalizing and automating much of the selection process. This session provides an overview of the selection processes using both measures of skills and psychological measures to quantify IQ, domain knowledge, grit, and determination. Examples will be drawn from hiring practices for Special Forces (such as Army Rangers and Navy SEALs) and predictive analytics teams.

Speaker: Dean Abbott, President, Abbott Analytics, Inc.



11:30am-12:15pm v Room: Harborview Ballroom 2 & 3

Keynote

Charting Collections of Connections in Social Media: Creating Maps and Measures with NodeXLNetworks are a data structure common found across all social media services that allow populations to author collections of connections. The Social Media Research Foundation’s NodexL project makes analysis of social media networks accessible to most users of the Excel spreadsheet application. With NodexL, Networks become as easy to create as pie charts. Applying the tool to a range of social media networks has already revealed the variations present in online social spaces. A review of the tool and images of Twitter, flickr, YouTube, and email networks will be presented.

We now live in a sea of tweets, posts, blogs, and updates com-ing from a significant fraction of the people in the connected world. Our personal and professional relationships are now made up as much of texts, emails, phone calls, photos, videos, documents, slides, and game play as by face-to-face interac-tions. Social media can be a bewildering stream of comments, a daunting fire hose of content. With better tools and a few key concepts from the social sciences, the social media swarm of favorites, comments, tags, likes, ratings, and links can be brought into clearer focus to reveal key people, topics and sub-communities. As more social interactions move through machine-readable data sets new insights and illustrations of human relationships and organizations become possible. But new forms of data require new tools to collect, analyze, and communicate insights.

Speaker: Marc Smith, Chief Social Scientist, Connected Action Consulting Group

12:15-12:30pm v Room: Harborview Ballroom 2 & 3

Platinum Sponsor Presentation

Managing Forward: Analytics For Today’s Multi-Channel, Multi-Device ConsumerWhen done right, customer satisfaction measurement can yield more than just insights into how well your company, brand, or channel (e.g., web, mobile, store) is performing today. It can also predict the likelihood of customers to engage in critical future behaviors. However, not all methodologies are created

equal. They must answer three essential questions of manage-ment while demonstrating success not only in theory but in the marketplace.

Speaker: Eric Feinberg, President & CEO to Senior Director, Mobile, Media, and Entertainment and keep Foresee


Lightning Round of 2-Minute Sponsor Presentations

12:45-1:40pm v Room: Commonwealth Hall

Lunch / Exhibits


KeynoteCase Study: Verizon

Influencers, Skeptics, and Data Geeks: Using Analytics to Drive Organizational Change“What gets measured gets done” often is true when it comes to tactical execution. When applied to large-scale strategy, however, the implications of this adage are even more signifi-cant.

Advanced analytics can help reveal the true performance driv-ers in an organization. By leveraging the power of analytics in combination with the principles of change management, learn how to effectively lead your organization into a new era of operational success.

Speaker: Anne G. Robinson, Dir. of Supply Chain Strategy and Analytics, Verizon Wireless


Platinum Sponsor Presentation How Big Data Delivers a Competitive AdvantageThere’s a lot of discussion as to whether Big Data can live up to its hype. Apply it to a businesses’ front line – sales - and the benefits become tangible.



Personalized and predictive selling is one of Big Data’s more interesting applications. From Amazon’s Recommendations to Google’s targeted ads, we are all being touched by Big Data whether or not we know or like it. While the power of Big Data is recognizable on the retail side, what is less visible is its application to B2B sales. From a sales rep’s perspective, Big Data answers a major question: how do I find the customers who are most receptive to my product or service at a given time? The best reps already have a talent for this. Big Data democratizes this excellence by automating the skills of excellent reps by delivering insight out of massive amounts of internal, external and social data.

This session will discuss the five steps to generate insight from Big Data, using customer case studies as an example of how to apply predictive analytics to selling complex product and service offerings to gain competitive advantage.

Speaker: Kent McCormick, Ph.D., President & CTO, Lattice Engines

3:00-3:45pm v Room: Harborview Ballroom 1

Track 1: Big Data

Big Data and Big Analytics Trends: The Promise and the Hype l

We will look at the current trends and buzzwords in Big Data, Data Mining and Predictive analytics field and examine how much hype and reality is in the promise of Big Data. We also analyze the growing and changing demand for data scientist skills and see which skills are the hottest.

Speaker: Gregory Piatetsky-Shapiro, Editor, KDNuggets


Track 2: Market Mix OptimizationCase Study: Penske s

Marketing Mix Optimization: Forecasting and Decision Making Under UncertaintyMost marketing mix solutions either fall short either due to reliance on imperfect information or failing to take into ac-count management assessments and business uncertainties. We have developed a novel analytic approach based on a mix of Bayesian statistics and our own proprietary media tools, which

help us to predict and optimize the offline and online media. Key features include Monte Carlo scenario analysis, forecasting under uncertainty (constrained media, lack of attribution data etc.), quantifying short and long-term channel effects. Using a client case study, we will highlight our approach and a frame-work to make timely and effective business decisions.

Speakers: Chris Dickey, SVP, Director of Analytics & CRM, The Martin Agency; David Henkel, Manager - Digital Optimization, Penske; Neeraj Kulkarni, Senior Statistician, Martin Agency; John Busbice, Founder, MIDA


Track 1: Predictive Project Management

Case Study: Tangent Design Engineering l

Applying Predictive Analytics to Improve Project ManagementProject managers today are struggling to keep control over multiple projects in today’s complex work environment. Almost all projects are in a state of constant change and managers are tasked with making continual adjustments to reflect compet-ing priorities, scheduling changes, and resource allocation. It’s estimated that even small teams will require billions of calcula-tions each month to accurately adjust their project schedules. Businesses today need predictive project management solu-tions that use advanced statistical algorithms to automatically adjust and accurately predict project schedules to positively impact the bottom line. Tangent Design Engineering is a great example.

Speaker: Brett Bender, Principal Software Engineer, LiquidPlanner


Track 2: Self Updating ModelsCase Study: Ace Cash Express s

Data Driven ModelingModels break down over a period - we call this stability of the model. The more the modeler gets creative, the faster the mod-el breaks-down. In this presentation, you will learn:

• The techniques and the benefits of building a self-updating model, so you never have to worry about models collecting dust



• Ways to regulate an automated model, so human control is not lost

• Methods you can employ in reporting against ever-changing model

Speaker: Senthil Ramanath, Head of Credit Risk Analytics, Ace Cash Express

3:50-4:10pm v Room: Cambridge

Sponsored LabCase Study: Predicting Sales Through Brand Research Data

Closing the Chasm Between Marketing and Sales For marketing managers, consumer insight is what helps build brands. The brand’s Key Performance Indicators (KPIs) are the measures that they live by. Every brand deploys extensive track-ing of these brand performance measures and consumer senti-ment across categories and markets at regular intervals.

However, in today’s challenging economic environment, spends on research are being put under the scanner, and the ROI on such initiatives is often questioned. Increasingly, marketing managers are being challenged by their sales and operations planning counterparts on the efficacy of such measures and their relevance to sales. Marketing Mix Modeling and other advertising testing models explain the effects of promotions on sales, but they don’t establish the connect with the brand’s KPIs. This puts added pressure on marketers with their decision to conduct research for what in effect is seen as a status check on brands with no direct implications on business.

Through our case study on a global beverage major, we will showcase how consumer tracking research can predict to-tal brand sales potential and provide foresight to the sales organization. We will be taking this initiative on behalf of the marketing fraternity.

Speaker: Amitabh Bose, Sr. Director – Capability, WNS Global Services


Break / Exhibits


Track 1: PA for Financial Regulations

Case Study: Goldman Sachs l

Utilizing Predictive Analytics to Analyze Changing RegulationAs regulatory expectations increase, organizations must utilize predictive analytics techniques to predict the impact of regula-tory change. Regulations such as the Volker Rule, Anti-Money Laundering and Model control regulation require companies to more effectively conduct surveillance and analysis. This session focuses on:

• Learning how to effectively analyze and predict the impact of new regulation to your business

• Take away practical tips to generate accurate alerts, model data feeds against your products and tune thresholds

• Determine the right technology to resolve common data challenges and maintain clean data

• Learn how to avoid mishandling complex analyses and reporting

Speaker: Vikas Agrawal, Global Head of Analytics, Goldman Sachs


PAWQuarterPageWoman_Boston_2012_10.indd 1 8/23/2012 4:35:06 PM



Track 2: Healthcare AnalyticsCase Study: Pfizer s

Right Medicine, Right PatientCan predictive modeling improve patient care? A wealth of data exists in large healthcare databases on patient disease characteristics and their response to specific treatments. Max will discuss some of the technical and non-technical issues in providing care providers with quantitative results related to how individual patients might response to therapies.

Speaker: Max Kuhn, Director of Nonclinical Statistics, Pfizer


Track 1: Economic Research and ForecastingCase Study: Rebellion Research l

Applying Machine Learning to Global EconomicsGlobal Economic research is provided by the biggest banks and ratings institutions, yet the predictive powers of these firms is notably and infamously low. Bloomberg reported that major Wall Street research is typically 46% accurate. However, this is a field that deals with an extremely large and accessible data set. One that is ideal for machine learning. Yet, there are no machine learning powered research or ratings firms on Wall Street. Robotic ratings and research firms could dominate this field, yet are not even in existence today.

Speaker: Alexander Fleiss, Chairman, Rebellion Research


Track 2: Clinical HealthcareCase Study: Sisters of Mercy Health Systems s

Framework for Detection of Clinical States & Disease Onset Using Electronic Health Record (EHR) DataThis case study describes the application of predictive analytics to the detection of disease onset and clinical states through the use of electronic health records (EHR). The framework pre-

sented here aims to improve prediction of a patient’s risk for developing severe sepsis and septic shock through a risk score generated as a function of measurements of patient vitals over time. A risk score threshold of 0.71 was found to yield the high-est sensitivity while minimizing false negatives in the patient database. This predictive model can also be generalized to predict outcomes of other application domains.

Speakers: Jeni Fan, Associate, Booz Allen Hamilton & Juergen A. Klenk, PhD, Principal, Booz Allen Hamilton


Reception / Exhibits


Boston Predictive Analytics Meet Up

Lightning Talks: “Data Deluge!, U.S. Jobs Outlook, D3 DataViz, R Data Mining, Ran-dom Forests”The goal of the Meetup group is to help the local community further it’s understanding and proficiency regarding Predic-tive Analytics through informative lectures, hands-on tutorials, and networking events. Our group has three main focal points: business applications, advanced mathematics, and computer science. Past events have included sentiment analysis, web content recommendations, social media and network analysis; as well as several events pertaining to the Big Data / Hadoop ecosystem.

Boston’s Meetup Community: John Verostek

Tapping the Data Deluge!: Jeffrey Breen

U.S. Jobs Outlook: John Muller

Data Visualizations Using D3: Lynn Cherny

Data Mining with R / Rattle: David Weisman

Random Forests Case Study: Dan Gerlanc

www.meetup.com/Boston-Predictive-Analytics



Tuesday, October 2, 2012


Registration & Breakfast


Keynote

Putting IBM Watson to WorkIBM’s Watson captured the imagination of over 34 million viewers when it beat the all time champions of the US game show, Jeopardy! To do so, it navigated the complexities of human speech, churned through 200 million pages of unstruc-tured data in under 3 seconds, delivered a confidence based response, all while learning and getting smarter with each outcome. But as impressive as this accomplishment was, it was only the beginning. IBM is working with leading organizations across industries to put Watson to work. The possibilities are endless! Join Bob Jewell, Director of Business Development and Partnerships for IBM Watson Solutions, in an engaging discus-sion of how IBM Watson can fundamentally transform the way businesses and individuals make decisions and how next generation systems will be designed.

Speaker: Robert Jewell, Director, Global Business Development & Partnerships, IBM Watson Solutions


Platinum Sponsor Presentation

Forensic Analytics – Discover Insights That Can Help you Move ForwardInternal audit, compliance groups and the like are increas-ingly being asked to do more work with less resources. In the world of forensic analytics we are utilizing advanced analytic techniques to help those charged with the tasks of investigat-ing fraud, waste, abuse and corruption combat their resource constraints. Forensic Analytics applies a variety of techniques and methodologies to transform disparate data sources into forensic insights for timely action. But what happens when the fraud or corruption has already occurred? Utilizing predictive modeling to gain forensic insights into the vast amount of data can yield promising results, especially when looking at damag-

es. This presentation explores the use of predictive modeling to look at what could have been, had unfair lending practices at a large financial institution not occurred.

Speaker: Carol Tannous, Senior Manager in the Data Analytics Practice, Deloitte Financial Advisory Services LLP


Breaks / Exhibits


Expert Panel

Big Data for Predictive AnalyticsIf Big Data begs the question, “What to do with all this data?” predictive analytics answers, “Learn from it to predict behav-ior.” But just how much predictive payoff comes with going so big? This expert panel will address the new demands on predictive analytics solutions and best practices as data grows to enormity, and will recommend tactics to fully leverage data’s growing magnitude to improve the business performance of predictive analytics initiatives.

Speakers: Satish Lalchand, Director, Deloitte Financial Advisory Services LLP, Jason Verlen, Director, SPSS Product Strategy & Management, IBM Software Group, Eric Feinberg, Senior Director of Mobile, Media and Entertainment, Foresee

Moderator: Eric Siegel, Ph.D., Conference Chair, Predictive Analytics World


Lightning Round of 2-Minute Sponsor Presentations

11:45am-12:30pm v Room: Harborview Ballroom 2 & 3

Sponsored Lab Lab Session: Live Topical Demo l

Building Customer Relationships Through IBM SPSS Predictive AnalyticsBuilding life-long customer relationships is a key goal for ING U.S. Financial Services. To build stronger customer relationships, we recently launched a new customer experience program across our U.S. contact centers. At the heart of this program is a predictive analytics capability that is designed to maximize



the value of customer touchpoints. In the first 12 months since launch, predictive analytics has guided more than 300,000 customer interactions and resulted in 24,000 positive customer actions. This presentation will describe how predictive analytics has been used to deliver the right message to the right cus-tomer at the right time.

Speakers: Tom Hamilton, Director, Business Intelligence Competency Center, ING, Jason Verlen, Director, SPSS Product Strategy & Management, IBM Software Group


Lunch / Exhibits


Special Plenary Session

Becoming an Ace with a Robot as your WingmanHumans and computers have strengths that are more comple-mentary than alike – to the point where a sophisticated algo-rithm may be the best “2nd person” to put on a complex task. Yet, our and computer analytic weaknesses are surprisingly severe. To explore how to improve the man/machine partner-ship, we compare and contrast natural and artificial intelli-gence, with special attention to the growing realization of how challenging it is to think truly rationally.

Speaker: John Elder, CEO & Founder, Elder Research, Inc.



Quest for Big Insight- Path to Actionable Insights from the Data DelugeAll firms today seek to leverage all of their data to make fact-based actionable business decisions. But how many are truly getting the ROI they want or the insights they need?

Technology has made it possible to harness a wealth of trans-actional data and even as industry was coming to terms it, the gamut of Big Data has opened up a virtual deluge, pun intended.

Insights however continue to remain the key to creating com-petitive advantage; in this session, we discuss how companies have leveraged WNS’ proprietary analytics decision engine WADE to derive insight from data and drive customized and scalable business solutions enabling fact-based choices.

Speaker: Sanjit Bhoumick, Senior Vice President – Sales, WNS Global Services


Track 1: Sales Force OptimizationCase Study: Hewlett-Packard l

Sales Productivity Analysis - Optimizing Time Spent to Attain Maximum Returns for Sales RepsAny organization needs a very efficient and effective sales force in order to be competitive. Among various efficient and effective parameters, we focused on time spent pattern of the sales representatives and how it would influence their sales performance (Win Rates). To achieve this, a non-linear causality between the Win Rates and Time Spent pattern was designed. The analysis predicted maximum win rates that can be achieved with optimal time spent. It helped to recommend future strate-gies for sales organization for better reallocation of time spent across job activities, which in turn would help sales to enhance ROI.

Speakers: Guruprasad Srinivasan, Project Manager, Subhamitra Chatterjee, Marketing Analyst, Hewlett-Packard


Track 1: Predicting B-2-B BuyingCase Study: Hewlett-Packard l

Behavioral Analysis of Account Purchases and their PredictabilityAnalyzing purchase behavior in the enterprise space is a na-scent area of research - to determine what a customer account is likely to buy next, when it will buy, what is the probability of winning a deal and finally, the expected value of the purchase. Our holistic solution dynamically captures changes in influenc-ing variables in real time, acting as an early warning system that helps sales teams prioritize opportunities, take necessary action and allocate resources optimally.



This has assisted the sales organization at HP to pursue the most profitable opportunities within the right accounts, maxi-mize profitability and improve market share.

Speakers: Govindarajan Krishnaswamy, Analytics & Solutions, Aparna Seshadri, Business Analytics Solution Development & Ronobijay Bhaumik, Lead, Sales Processes and Execution Portfolio, Global Business Intelligence, Hewlett-Packard


Track 2: True Lift ModelingCase Study: Staples s

True-Lift Modeling: Mining for the Most Truly Responsive Customers and ProspectsStop spending direct marketing dollars on customers who would purchase anyway!

True-lift modeling can identify:• which customers will purchase without receiving a

marketing contact• which customers need a direct marketing nudge to make

a purchase• which customers have a negative reaction to marketing

(and purchase less if contacted)This discussion will describe:• the pros and cons of various approaches to true-lift

modeling• metrics for evaluating model performance • the basic requirements needed to succeed with true-lift

modeling• scenarios where this modeling method is most applicable

Speaker: Jane Zheng, Chief Scientist, Focus Optimal


Breaks / Exhibits


Track 1: Financial ServicesCase Study: Commerzbank, Lloyds, Ursus Advisors l

Optimization in Financial ServicesFinancial institutions are improving business performance by using optimization techniques in additional to behavioral and statistical modeling. Hear how retail banks are using prescrip-

tive along with predictive analytics to get more customers, get them more profitably, price them appropriately, and retain them strategically.

We will cover the barriers to adoption and introduce an orga-nizational readiness checklist. Attendees should leave ready to kick off the projects internally to implement optimization.

Speaker: Frank Bria, Research Director, Tower Group


Track 1: Vendor Recommendations (Beyond Product Recs)Case Study: Intuit and Mint l

Restaurant Recommendations Using Financial LikenessImagine you are in a new neighborhood and want to discover the ‘right’ restaurant for ‘you’. Instead of reading a host of reviews, we present a recommender system that learns from your historical spend transactions. The system predicts ap-propriate restaurants from financial transactions of users in Mint, a personal finance tool from Intuit. In contrast to domain specific apps, our recommender can be scaled across different verticals which have financial transaction data from users and hence is more general purpose. We will describe the challenges in using spend data for recommendation, scaling to millions of merchants and transactions with Hadoop and Mahout, and evaluating the performance of the app.

Speaker: Saikat Mukherjee, Data Scientist, Intuit


Track 2: Detecting CannibalizationCase Study: TripAdvisor s

Cannibalization Analysis Using Matched Pairs at TripAdvisorIn 2010, TripAdvisor launched our Business Listings product that sends travelers directly to hotel web sites, bypassing on-line travel agencies. Is the new product stealing revenue from our traditional CPC business? This case study explains why the question is hard to answer, describes the analytic approach we employed, and reveals the answer to the question.

Speaker: Michael Berry, Business Intelligence Director, TripAdvisor




Track 1: Crowdsourcing Data Mining

Machines Learn, But Can They Teach? l

In 2012, a British particle physicist, a data analyst for the National Weather Service in Washington, D.C., and a gradu-ate student from Germany (none of whom had a background in education) collaborated on the Kaggle platform to win the $100,000 Hewlett Foundation Automated Student Assessment Prize, a competition to build an innovative algorithm that could score students’ essays used in state standardized tests. Software scoring programs do not independently assess the merits of an essay; instead they predict, very accurately, how a person would have scored the essay. This is a critical distinction because it means that the software replicates the same scores as trained educators for significantly less time and money. The winning algorithm outperformed the current state-of-the-art in commercial grading software and achieved the same level of agreement with a trained human grader as two human grad-ers have with each other. Anthony Goldbloom, the founder and CEO of Kaggle, discusses what these results mean for the future of education technology and crowd-sourced competitive analytics.

Speaker: Anthony Goldbloom, Founder & CEO, Kaggle


Track 2: Customer ValuationCase Study: United Group Holdings s

Value Proposition Segmentation (VPS) MethodIn today’s competitive market, effective management of cus-tomer relations lies in the ability to optimize the dual creation of firm (shareholder) and customer value. Accordingly, the challenge for many companies is to be able to understand cus-tomers by their needs to deliver the winning value proposition profitably. This session will show how our proposed VPS model addresses the basic managerial concern of balancing relation-ships from both the seller’s (customer loyalty) and the buyer’s (customer benefit), by considering both the service provider’s financial performance (i.e. customer value to the firm) and the value customers receive from the the provider’s offerings.

Speaker: Amjad Zaim, Chief Executive Officer, Cognitro Analytics




Tuesday, October 2, 2012

Three hours: 6:30pm-9:30pm v Room: Washington

R Bootcamp: For Newcomers to R sIntended Audience: Practitioners who wish to learn the nuts and bolts of the R language; anyone who wants “to turn ideas into software, quickly and faithfully.”

Knowledge Level: Experience with handling data (e.g. spreadsheets) or hands-on familiarity with any programming language.

Workshop Description

This half-day workshop launches your tenure as a user of R, the well-known open-source platform for data analysis. The workshop stands alone as the perfect way to get started with R, or may serve to prepare for the more advanced full-day hands-on workshops, “R for Predictive Modeling”.

Designed for newcomers to the language of R, “R Bootcamp” covers the R ecosystem and core elements of the language, so you attain the foundations for becoming an R user. Topics include common tools for data import, manipulation and export. If time allows, other topics will be covered, such: as graphical systems in R (e.g. LATTICE and GGPLOT) and automated reporting.

The instructor, a leading R developer and the creator of six R packages, including CARET, a core R package that streamlines the process for creating predictive models, will guide attendees on hands-on execution with R, covering:

• A working knowledge of the R system• The strengths and limitations of the R language• Core language features• The best tools for merging, processing and arranging data

Hardware: Bring Your Own Laptop

Each workshop participant is required to bring their own laptop running Windows or OS X. The software used during this training program, R, is free and readily available for download.

Attendees receive an electronic copy of the course materials and related R code at the conclusion of the workshop.

Schedule

• Workshop starts at 6:30pm

• End of the Workshop: 9:30pm

Instructor: Max Kuhn, Director, Nonclinical Statistics, Pfizer

Wednesday, October 3, 2012

Full-day: 9:00am - 4:30pm v Room: Washington

R for Predictive Modeling:A Hands-On Introduction sIntended Audience: Practitioners who wish to learn how to execute on predictive analytics by way of the R language; anyone who wants “to turn ideas into software, quickly and faithfully.”

Knowledge Level: Either hands-on experience with predictive modeling (without R) or hands-on familiarity with any program-ming language (other than R) is sufficient background and preparation to participate in this workshop.

The three-hour “R Bootcamp” is recommended preparation for this workshop.



Workshop DescriptionThis one-day session provides a hands-on introduction to R, the well-known open-source platform for data analysis. Real ex-amples are employed in order to methodically expose attendees to best practices driving R and its rich set of predictive modeling packages, providing hands-on experience and know-how. R is compared to other data analysis platforms, and common pitfalls in using R are addressed.

The instructor, a leading R developer and the creator of CARET, a core R package that streamlines the process for creating predictive models, will guide attendees on hands-on execution with R, covering:

• A working knowledge of the R system

• The strengths and limitations of the R language

• Preparing data with R, including splitting, resampling and variable creation

• Developing predictive models with R, including decision trees, support vector machines and ensemble methods

• Visualization: Exploratory Data Analysis (EDA), and tools that persuade

• Evaluating predictive models, including viewing lift curves, vari-able importance and avoiding overfitting

Hardware: Bring Your Own Laptop

Each workshop participant is required to bring their own laptop running Windows or OS X. The software used during this train-ing program, R, is free and readily available for download.

Attendees receive an electronic copy of the course materi-als and related R code at the conclusion of the workshop.

Schedule• Workshop starts at 9:00am• Morning Coffee Break at 10:30am - 11:00am• Lunch provided at 12:30 - 1:15pm• Afternoon Coffee Break at 2:30pm - 3:00pm• End of the Workshop: 4:30pm

Instructor: Max Kuhn, Director, Nonclinical Statistics, Pfizer

Wednesday, October 3, 2012

Full-day: 9:00am - 4:30pm v Room: Harborview Ballroom 1

The Best and the Worst of Predictive Analytics: Predictive Modeling Methods and Common Data Mining Mistakes sA free copy of John Elder’s book Statistical Analysis and Data

Mining Applications is included.

Intended Audience: Interested in the true nuts and bolts

Knowledge Level: Familiar with the basics of predictive modeling.

Attendees will receive an electronic copy of the course notes via USB drive.


Predictive analytics has proven capable of enormous returns across industries – but, with so many core methods for pre-dictive modeling, there are some tough questions that need answering:

• How do you pick the right one to deliver the greatest impact for your business, as applied over your data?

• What are the best practices along the way?

• And how do you avoid the most treacherous pitfalls?

This one-day session surveys standard and advanced methods for predictive modeling.

Dr. Elder will describe the key inner workings of leading al-gorithms, demonstrate their performance with business case studies, compare their merits, and show you how to pick the method and tool best suited to each predictive analytics project. Methods covered include classical regression, decision trees, neural networks, ensemble methods, uplift modeling and more.

The key to successfully leveraging these methods is to avoid “worst practices”. It’s all too easy to go too far in one’s analysis and “torture the data until it confesses” or otherwise doom predictive models to fail where they really matter: on new situ-ations.

Dr. Elder will share his (often humorous) stories from real-world applications, highlighting the Top 10 common, but deadly, mistakes. Come learn how to avoid these pitfalls by laughing (or gasping) at stories of barely averted disaster.


If you’d like to become a practitioner of predictive analytics – or if you already are, and would like to hone your knowledge across methods and best practices, this workshop is for you!

What you will learn:

• The tremendous value of learning from data• How to create valuable predictive models for your business• Best Practices by seeing their flip side: Worst Practices

Schedule• Workshop starts at 9:00am• First AM Break from 10:00 - 10:15am• Second AM Break from 11:15 - 11:30am• Lunch from 12:30 - 1:15pm• First PM Break: 2:00 - 2:15pm• Second PM Break: 3:15 - 3:30pm• Workshops ends at 4:30pm

Attendees receive a free copy of John Elder’s book Statis-tical Analysis and Data Mining Applications, an electronic copy of the course notes via USB drive, and an official cer-tificate of completion at the conclusion of the workshop.

Instructor: John Elder, CEO & Founder, Elder Research, Inc.

Thursday, October 4, 2012

Full-day: 8:45am - 4:30pm v Room: Cambridge 1

Advanced Methods Hands-on:Predictive Modeling Techniques s

Workshop sponsored by:

Intended Audience: Practitioners: Analysts who would like a tangible introduction to predictive analytics or who would like to experience analytics using a state-of-the-art data mining software tool.Technical Managers: Project leaders, and managers who are responsible for developing predictive analytics solutions, who want to understand the process.

Knowledge Level: Familiar with the basics of predictive modeling.


Once you know the basics of predictive analytics and have prepared data for modeling, which algorithms should you use?

What are the similarities and differences? Which options affect the models most? This workshop dives into the key predictive analytics algorithms for supervised learning,including decision trees, linear and logistic regression, neural networks, k-nearest neighbor, support vector machines, and model ensembles. At-tendees will learn “best practices” and attention will be paid to learning and experiencing the influence various options have on predictive models so that attendees will gain a deeper under-standing of how the algorithms work qualitatively.

Participant background

Participants are expected to know the principles of predictive analytics. This hands-on workshop requires all participants to be involved actively in the model building process, and therefore must be prepared to work independently or in a small team throughout the day. The instructor will help participants under-stand the application of predictive analytics principles, and will help participants overcome software issues throughout the day.

Software

While the majority of concepts covered during this workshop apply to all predictive analytics projects - regardless of the par-ticular software employed - this workshop’s hands-on experi-ence is achieved via StatSoft STATISTICA. A license will be made available to participants for use on that day (included with workshop registration).

Hardware: Bring your Own Laptop

Each workshop participant is required to bring their own laptop running Windows. Instructions will be provided to install a trial license for the analytics software used during this training program.

Attendees receive a course materials book and an official certificate of completion at the conclusion of the work-shop.

Schedule• Software installation a 8:45am• Workshop program starts at 9:00am• Morning Coffee Break at 10:30 - 11:00am• Lunch provided at 12:30 - 1:15pm• Afternoon Coffee Break at 2:30 - 3:00pm• End of the Workshop: 4:30pm

Instructor: Dean Abbott, President, Abbott Analytics



Friday, October 5, 2012

Full-day: 9:00am - 4:30pm v Room: Back Bay

Making Text Mining Work: Practical Methods and Solutions l

A free copy of Dr. Fast’s book on Practical Text Mining is included.

Intended Audience: Practitioners seeking tools to analyze unstructured text data.

Knowledge Level: No previous experience required though some technical background in statistics or predictive analytics will be useful.

Attendees will receive an electronic copy of the course notes via USB drive.


In their 2011 Hype Cycle report, Gartner has Text Analytics sliding into the “Trough of Disillusionment”, highlighting the difficulty of achieving its great promise. Despite this verdict, text mining and text analytics can be valuable tools, if you know where to look for the solution. This workshop will address:

• The text mining solutions available now and the problems for which they are best suited

• Best practices in the key text mining areas

• How to set positive but realizable expectations for the return on investment of a text mining project

This one-day session surveys standard and advanced methods for text mining. Dr. Fast will describe the key inner workings of leading algorithms, demonstrate their performance with busi-ness case studies, compare their merits, and show how to pick the approach best suited for your project. Methods covered include search indexes, text classification, information extrac-tion, document similarity and more.

The key to successfully leveraging these methods is to find the right “hammer” for your text “nails” and understand the limits of those techniques.

Dr. Fast will share his experience mining text on real-world ap-plications in several fields, highlighting the range of available so-lutions and how to combine technologies to maximize the value of the vast store of (untapped) unstructured data.

If you’d like to become a text mining practitioner – or if you already are, and would like to hone your knowledge across methods and best practices, this workshop is for you!

What you will learn:

• The tremendous value of learning from unstructured textual data

• How to choose the proper text mining solution

• Text mining best practices

Schedule

• Workshop starts at 9:00am

• First AM Break from 10:00 - 10:15am

• Second AM Break from 11:15 - 11:30am

• Lunch from 12:30 - 1:15pm

• First PM Break: 2:00 - 2:15pm

• Second PM Break: 3:15 - 3:30pm

• Workshop ends at 4:30pm

Attendees receive a free copy of Andrew Fast’s book on Practical Text Mining, an electronic copy of the course notes via USB drive, and an official certificate of comple-tion at the conclusion of the workshop.

Instructor: Andrew Fast, Director of Research Elder Research, Inc.


conversations with thought leaders

AnalyticallySpeaking

It’s not every day that you hear from world-renowned thought leaders on analytics. We do it every month.

During a series of webcasts, our distinguished guests will share insights that come with years of developing best practices and enjoying great success with analytics.

• Dean Abbott, President, Abbott Analytics

• Robert A. Stine, Wharton School of Business, University of Pennsylvania

• Kaiser Fung, Vice President, Business Intelligence and Analytics, Vimeo

• David Salsburg, Lecturer, Yale University and Retired Senior Research Fellow, P� zer Inc.

• Michael Berry and Gordon Linoff, Co-Founders, Data Miners Inc.

You’re about to witness thought leadership at its best. Find the complete schedule online.

jmp.com/speaking

SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. © 2012 SAS Institute Inc. All rights reserved. S96495US.0812

96495_JMP_PAW_FullAd.indd 1 8/16/12 4:39 PM


Online Workshop

Predictive Analytics Applied – An Online IntroductionNew to predictive analytics? Take this online course to ramp up before Predictive Analytics World.

Online 5 ½-hour training program:•On-demandatanytime–startnowfor3monthsofaccess•Self-pacede-learning–atyourconvenience•Internationally-friendly–takenfromover16countries

Intended Audience:• Managers. Project leaders, directors, CXOs, vice presidents, investors and decision makers of any kind involved with analytics,

direct marketing or online marketing activities.

• Marketers. Personnel running or supporting direct marketing, response modeling, or online marketing who wish to improve response rates and increase campaign ROI for retention, upsell and cross-sell.

• Technology Experts. Analysts, BI directors, developers, DBAs, data warehousers, web analysts, and consultants who wish to ex-tend their expertise to predictive analytics.


Business metrics do a great job summarizing the past. But if you want to predict how customers will respond in the future, there is one place to turn — predictive analytics. By learning from your abundant historical data, predictive analytics delivers something beyond standard business reports and sales forecasts: actionable predictions for each customer. These predictions encompass all channels, both online and off, foreseeing which customers will buy, click, respond, convert or cancel. If you predict it, you own it.

The customer predictions generated by predictive analytics deliver more relevant content to each customer, improving response rates, click rates, buying behavior, retention and overall profit. For online applications such as e-marketing and customer care recommendations, predictive analytics acts in real-time, dynamically selecting the ad, web content or cross-sell product each visitor is most likely to click on or respond to.

Predictive Analytics Applied is a self-paced online course instructed by the founding chair of Predictive Analytics World that covers the following topics:

• Applications: Business, marketing and web problems solved with predictive analytics. The many ways its predictions can be used to drive various business decisions.

• Core Technology: How a predictive model works and how it’s created. What a predictive model looks like under the cover. What data is required for predictive modeling.

• Evaluation: How well a predictive model works and how much revenue it generates

• Management: Project leadership and business process for predictive analytics; the organizational challenges and how to overcome them.

• Illustrations: Live demos and detailed case studies

Hands-on: “Get your hands dirty” with a revealing Excel-based exercise, bringing a predictive model to life and seeing it improve before your eyes

System requirements to view this online training program:• High-speed Internet connection

• Adobe Flash Player 9 installed

You will receive access to the online training program by way of an email sent within two business days of registration (please check your SPAM folder if you do not see the message within two business days).

Knowledge Level: No background in statistics or modeling is required. The only specific knowledge assumed for this training program is moderate experience with Microsoft Excel or equivalent.

To get more information or to register for this course, go to:www.predictiveanalyticsworld.com/boston/register.php

Instructor: Eric SiegelPh.D., Conference Chair, Predictive Analytics World


Keynote Bios

Robert JewellDirector, Global Business Development & PartnershipsIBM Watson Solutions

A 30 year veteran of the IT industry, Bob began his career at IBM in Sales and held a number of management positions before leaving in 1993. After leaving IBM, Bob held various Senior Executive positions in Sales and General Manage-ment at several start-ups and Venture backed companies where he participat-ed in 2 IPO’s and one acquisition. These companies include Seer Technologies, Level 3 Communications, Altio Ltd. and Bowstreet, Inc. At Bowstreet, Bob was VP of Global Sales, Services and Business Development until the acquisition of Bowstreet by IBM in December of 2005.

Bob has held several executive positions in IBM Software Group and Corporate Strategy since the acquisition. Currently Bob is Director of Global Business Development for IBM Watson Solutions where he and his team are respon-sible for commercializing the IBM Watson technologies demonstrated in the Jeopardy! Challenge.

Keynote: Putting IBM Watson to Work

Scott NicholsonChief Data ScientistAccretive Health (formerly of LinkedIn)

Scott Nicholson is Chief Data Scientist at Accretive Health and has a PhD in Economics from Stanford. His team works to find innovative uses of data to help doctors make better decisions about care and to help people be more proactive about their own care. Before moving into the health care industry Scott was a Team Lead, Senior Data Scientist and Economist at LinkedIn where his work focused on using predictive modeling to increase user engagement and identify economically relevant insights from the rich LinkedIn data. Before LinkedIn Scott built real-time bidding and ad selection algorithms at an online advertising startup.

Keynote: Beyond Big Data: Better Living Through Data Science

Anne G. RobinsonDirector of Supply Chain Strategy & AnalyticsVerizon Wireless

Anne G. Robinson is the Director of Supply Chain Strategy and Analytics for Verizon Wireless. Her team is responsible for leading strategic efforts across the Supply Chain organization, leveraging advanced analytics to implement processes and procedures that lead to improved device life cycle management, working capital optimization and cost reduction.

Prior to joining Verizon Wireless, Dr. Robinson spent seven years with Cisco Systems. Her responsibilities included managing advanced analytics, business intelligence, and performance management teams across the supply chain. She and her team were also responsible for evaluating and improving the distribution inventory network as well as establishing a statistical forecasting capability for predicting product demand. As the driving force for many foun-dational and cross-functional process innovations, she helped establish Cisco’s presence and recognition as a leader in business intelligence and analytics, including being inducted into the balanced scorecard hall of fame.

A PhD in Industrial Engineering from Stanford University, Anne is President-Elect of INFORMS, a professional organization focused on applying advanced analytical methods for making better business decisions. She has served on several advisory boards including the SAS Analytical Customer Advisory Board and the SAS-Teradata Product Advisory Board, and is a topical editor for the Encyclopedia of Operations Research and Management Science. A frequent tweeter, you can follow Dr. Robinson @agrobins.

Keynote: Influencers, Skeptics, and Data Geeks: Using Analytics to Drive Organizational Change

Marc SmithChief Social ScientistConnected Action Consulting Group

Marc Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action Consulting Group and lives and works in Silicon Valley, California. Smith co-founded the Social Media Research Foundation (http://www.smrfounda-tion.org/), a non-profit devoted to open tools, data, and scholarship related to social media research.

Smith is the co-editor with Peter Kollock of Communities in Cyberspace (Rout-ledge), a collection of essays exploring the ways identity; interaction and social order develop in online groups. Along with Derek Hansen and Ben Shneider-man, he is the co-author and editor of Analyzing Social Media Networks with NodeXL: Insights from a connected world, from Morgan-Kaufmann which is a guide to mapping connections created through computer-mediated interac-tions.

Smith received a B.S. in International Area Studies from Drexel University in Philadelphia in 1988, an M.Phil. in social theory from Cambridge University in 1990, and a Ph.D. in Sociology from UCLA in 2001. He is an affiliate fac-ulty at the Department of Sociology at the University of Washington and the College of Information Studies at the University of Maryland. Smith is also a Distinguished Visiting Scholar at the Media-X Program at Stanford University.

Keynote: Charting Collections of Connections in Social Media: Creating Maps and Measures with NodexL

For more speaker bio’s, please visit www.predictiveanalyticworld.com/boston/2012/speakers.php


Exhibitors Floorplan

Exhibitors by Booth Number

104 INFORMS106 NetProspex107 FICO113 StatSoft114 Sitespect116 iPerceptions118 ClickTale120 UCI122 MarketOne128 Silverpop129 Salesforce.com/Data.com130 Demandbase132 Trakken Technologies GmbH134 Teradata136 Act-On Software141 WNS201 IBM206 Deloitte Global Services228 ForeSee234 JMP235 Lattice Engines240 Mu Sigma241 Tealium305 IIA306 SiteTuners317 TagMan319 GCE: The Cloud Company321 Salford Systems323 Pervasive325 comScore, Inc327 Ensighten331 SweetSpot333 University of British Columbia Continuing Studies

335 DAA340 GoogleP1 AnanlyticsProsP3 LocalyticsP4 ShufflepointP5 NumericP6 iDashboardsP8 Rapid-iP9 Boston Predictive AnanlyticsP10 KxEN

Exhibitors by Alphabetical Order

Act-On Software ........................... 136AnanlyticsPros ................................ P1Boston Predictive Ananlytics ......... P9ClickTale ........................................ 118comScore, Inc ................................ 325DAA ............................................... 335Deloitte Global Services ............... 206Demandbase ................................. 130Ensighten ...................................... 327FICO ............................................... 107ForeSee ......................................... 228GCE: The Cloud Company ............ 319Google .......................................... 340IBM ................................................ 201iDashboards .................................... P6 IIA .................................................. 305INFORMS ....................................... 104iPerceptions .................................. 116JMP ................................................ 234KxEN ............................................. P10 Lattice Engines ............................. 235Localytics ......................................... P3 MarketOne ................................... 122Mu Sigma ...................................... 240NetProspex .................................... 106Numeric ........................................... P5 Pervasive ....................................... 323Rapid-i ............................................. P8 Salesforce.com/Data.com ............. 129Salford Systems ............................. 321Shufflepoint .................................... P4 Silverpop ....................................... 128Sitespect ........................................ 114SiteTuners ..................................... 306StatSoft ......................................... 113SweetSpot ..................................... 331TagMan ......................................... 317Tealium ......................................... 241Teradata ........................................ 134Trakken Technologies GmbH ....... 132UCI ................................................. 120University of British Columbia Continuing Studies ....................... 333

WNS ............................................... 141

Shared Data Driven Business Week Exhibit Hall


Thank you To Our Sponsors

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ASSOCIATION PARTNERS MEDIA PARTNERS

IT NEWS, RESOURCES, EVENTS

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Colors: 4/c Designer: M.Kryszak


Sponsor Profiles

Platinum Sponsors

Deloitte

www.deloitte.comBooth 206

About Deloitte’s Analytics Approach.

An organisation’s data is full of potential. Stored through-out the business, it has a wealth of possibilities. Leading businesses recognise that a better understanding of data (particularly as a predictor of the future or as an identifier of existing issues) can create new opportunities and make a significant difference to managing performance. Analytics is, in our opinion, the natural evolution of business intelligence processes, tools and technologies. While business intelligence focuses on historical analysis, analytics builds upon this set of technologies and techniques to re-focus on the future; help-ing predict future trends, opportunities and threats.

Deloitte’s deep industry expertise and advanced analytics capability can help decision-makers to maximise the value of their data. By looking at an organisation from the inside out we can turn everyday information into useful and actionable insights. Deloitte is one of the world’s leading professional services firms, providing audit, tax, consulting, and financial advisory services to public and private clients spanning mul-tiple industries. With a globally connected network of mem-ber firms in more than 140 countries, we bring world-class capabilities and deep local expertise to help clients succeed wherever they operate. Our 170,000 professionals are com-mitted to becoming the standard of excellence.

ForeSee www.foresee.comBooth 228

As a pioneer in customer experience analytics, ForeSee con-tinuously measures satisfaction across customer touch points and delivers critical insights on where to prioritize improve-ments for maximum impact. Because ForeSee’s superior technology and proven methodology connect the customer experience to the bottom line, executives and managers are able to drive future success by confidently optimizing the ef-forts that will achieve business and brand objectives. The re-sult is better business for companies and a better experience for consumers. Visit us at www.ForeSee.com for customer experience solutions and original research.

Lattice Engines www.lattice-engines.comBooth 235

Lattice Engines is revolutionizing B2B sales by harnessing big data to develop the most informed sales pros engaging re-ceptive customers in the most compelling ways. Our big data analytics platform delivers real-time, actionable, account-specific insight directly to your reps via CRM, the web, or mobile device. Fortune 5000 companies rely on our solution to generate more pipeline opportunity and close more deals, improving sales performance by 15% or more.

Lattice Engines is privately held and backed by Sequoia Capi-tal with headquarters in San Mateo, CA.

To learn more about Lattice Engines visit www.lattice-engines.com

Gold SponsorsIBM www.ibm.com/spssBooth 201

IBM Business Analytics software delivers complete, consis-tent and accurate information that decision-makers trust to improve business performance. A comprehensive port-folio of business intelligence, predictive analytics, financial performance and strategy management, and analytic ap-plications provides clear, immediate and actionable insights into current performance and the ability to predict future outcomes. Combined with rich industry solutions, proven practices and professional services, organizations of every size can drive the highest productivity, confidently automate decisions and deliver better results.As part of this portfolio, IBM SPSS Predictive Analytics soft-ware helps organizations predict future events and proac-tively act upon that insight to drive better business outcomes. Commercial, government and academic customers worldwide rely on IBM SPSS technology as a competitive advantage in attracting, retaining and growing customers, while reducing fraud and mitigating risk. By incorporating IBM SPSS software into their daily operations, organizations become predictive enterprises – able to direct and automate decisions to meet business goals and achieve measurable competitive advan-tage. For more information, visit www.ibm.com/spss


Sponsor Profiles

JMP www.jmp.comBooth 234

JMP Pro, statistical discovery software from SAS, gives you the power of data visualization, exploration, statistical data anal-ysis and data mining in an in-memory, desktop-based envi-ronment. It dynamically links statistics with graphics to make information accessible in ways a spreadsheet never could, letting you explore relationships, see hidden trends and easily communicate your findings. JMP Pro, Version 10, our new release, adds model comparison provisions for comparing fits across multiple fit predictions, one-click bootstrapping for most statistics in JMP reports and an advanced platform for partial least squares (PLS) regression with enhanced features. Import, process, model, and visualize data, even those with millions of records , in just seconds.

Mu Sigma www.mu-sigma.comBooth 240

Mu Sigma is a leading provider of decision sciences and ana-lytics services, helping companies institutionalize data-driven decision making.

Mu Sigma works with market-leading companies across multiple verticals, solving high impact business problems in the areas of Marketing, Supply Chain and Risk Analytics. With over 50 Fortune 500 clients and about 1300 analytics profes-sionals, Mu Sigma has disrupted the analytics industry by in-tegrating the disciplines of business, math, and technology in a sustainable global delivery model. Further, analytical assets developed by Mu Sigma’s innovation and development team ensure a competitive edge to clients. Mu Sigma is head-quar-tered in Chicago with its main delivery center in Bangalore, India and is arguably the world’s largest pure-play decision sciences and analytics services company.

WNS Research & Analytics www.wns.comBooth 141

The WNS Research & Analytics practice brings together deep analytics expertise with the process excellence and rigor of a global services delivery model, thereby enabling clients to harness the power of information and take actionable deci-sions to outperform. We deploy this through client-centric analytical centers of excellence that leverage a 2000+ team of statistical, data mining and research experts to mine both cloud-based and enterprise-level data. Our proprietary award winning innovation ? WNS Analytics Decision Engine (WADESM) is the result of our experience in helping compa-nies recognize the value of all the data at their disposal. Our solutions are rooted in a comprehensive understanding of the business issues in each of our key industry verticals as they relate to revenue growth, operational efficiency, product / market strategy, customer experience and a range of risk management challenges to give our clients the visibility they need to predict the best course to success.

Silver SponsorsPervasive Software bigdata.pervasive.comBooth 323

Pervasive Software and its Big Data products deliver strategic advantages to businesses by providing extreme performance capabilities at an economical price point to customers around the globe. Specializing in applications spanning claims pro-cessing, risk analysis, fraud detection, data mining, predictive analytics, sales optimization and marketing analytics, Perva-sive offers solutions that can quickly crunch through big data and scale to meet any business need throughout a company’s continued growth cycle. With a single, unified platform for end-to-end data access, transformation, analytics, visualiza-tion and reports on both Hadoop and high-performance servers. Pervasive Big Data ensures that data scientists and business analysts derive rapid insight from terabytes of data on commodity hardware. For additional information, go to bigdata.pervasive.com.


StatSoft, Inc. www.statsoft.comBooth 113

StatSoft, Inc., founded in 1984, is one of the largest producers of enterprise and desktop software for Data Analysis, Data Mining, Quality Improvement, and Web-enabled Analytics. Its products are used worldwide at most major corporations, universities, and government agencies and are supported with training and consulting services by 30 offices on all continents. STATISTICA Enterprise is a highly scalable, web-enabled platform, used by a variety of industries in mission-critical applications wherever predictive modeling helps increase productivity and profitability. The StatSoft platform has enjoyed unprecedented record of recognition from end-users (also, winning all major independent surveys of users) and reviewers for more than two decades. These indepen-dent ratings show that while easier to use and more cost-effective than its competitors, the StatSoft analytics platform offers unmatched performance, scalability, uncompromising attention to detail and overall quality, which ensures success for its users.

Bronze SponsorsFICO www.fico.comBooth 107

FICO (NYSE:FICO) delivers superior predictive analytics that drive smarter decisions. The company’s groundbreaking use of mathematics to predict consumer behavior has trans-formed entire industries and revolutionized the way risk is managed and products are marketed. FICO’s innovative solutions include the FICO® Score – the standard measure of consumer credit risk in the United States — along with indus-try–leading solutions for managing credit accounts, identi-fying and minimizing the impact of fraud, and customizing consumer offers with pinpoint accuracy. Most of the world’s top banks, as well as leading insurers, retailers, pharma businesses and government agencies rely on FICO solutions to accelerate growth, control risk, boost profits and meet regulatory and competitive demands. FICO also helps millions of individuals manage their personal credit health through www.myFICO.com. Learn more at www.fico.com. FICO: Make every decision count™.

GCE: The Cloud Company www.GCEcloud.comBooth 319

For more than a decade, GCE has been an established indus-try leader in the development of innovative technology solu-tions. The GCE Cloud offers a wide range of business services, including financial management, asset management, procure-ment, Big Data & analytics, and litigation support services.

The GCE Cloud is built upon a world-class technical infra-structure that ensures rapid scalability and reliability. GCE consistently delivers cutting-edge technology solutions to our customers – solutions that allow them to fully focus on their core missions and not be diverted by underlying, costly technology issues.

Salford Systems www.salford-systems.comBooth 321

Salford Systems is an award-winning analytics software de-velopment and consulting company with a proven record of technical and practical excellence. We offer a highly accurate, ultra-fast predictive analytics and data mining platform for developing models from databases of any size, complexity, or organization. Our technologies span classification, regression, missing value analysis, and clustering/segmentation. Core components of our Salford Predictive Modeler™ (SPM) plat-form include CART®, MARS®, TreeNet® and RandomForests®. Our automation accelerates the process of model building by conducting substantial portions of the model exploration and refinement process for the analyst. While the analyst is always in full control, we optionally anticipate the analyst’s next best steps and package a complete set of results from alterna-tive modeling strategies for easy review. Applications span fraud detection, credit scoring, market research segmenta-tion, direct marketing, drug discovery and risk management. Industries using Salford Systems products and services include banking, insurance, healthcare, telecommunications, trans-portation, manufacturing, and education.

Sponsor Profiles


University of California, Irvine Extensionwww.unex.uci.eduBooth 120

University of California, Irvine Extension offers an online Web Intelligence Certificate Program offered jointly with University of British Columbia (UBC) Continuing Studies, in partnership with the Digital Analytics Association (DAA). The program provides award-winning education on web analytics and leading-edge courses on data warehousing and business intelligence. To receive the certificate, students must com-plete the four online courses required for the UBC Award of Achievement in Web Analytics and a minimum of five units of coursework from among the UC Irvine Extension electives. For more information on this as well as our new certificate in Predictive Analytics, please visit www.extension.uci.edu or “like” us at www.facebook.com/UCIExtension.

Turnkey Pods

Boston Predictive Analytics

www.bostonpredictiveanalytics.comPod 9

Boston Predictive Analytics designs and delivers robust ana-lytics to address business intelligence challenges for enterpris-es. Using an array of techniques and tools, Boston Predictive Analytics leverages open source solutions, code libraries and talent to deliver low cost machine learning solutions.

While clients are in a wide array of industries, they share a common need of tackling analytics in an efficient manner. At Boston Predictive Analytics, engagements follow a proven path, from development of an analytic plan to delivery of data that mobilize analytics.

Boston Predictive Analytics focuses its work in four data-intensive areas:

• Customer Optimization• Next purchase recommenders• Cross-sell or upsell analytics• Customer attrition analytics• B2C & B2B loyalty indices

• Channel classification systems• Prospect Identification• Landing page analytics• Direct mail and e-mail analytics• Prospect and inbound lead scoring• Prospect-vendor matching• Fraud Detection• Fraud propensity scoring• Credit card fraud detection• Usage abnormality analytics• Network Health• Node failure analytics• Network speed analytics

Rapid-I ww.rapid-i.comPod 8

Rapid-I provides software, solutions, and services in the fields of predictive analytics, data mining, and text mining.

Its flagship product RapidMiner is the world-leading open-source system for knowledge discovery, data mining and sentiment analysis. RapidMiner is praised for being extremely easy to use, blazing fast, and very easy to integrate with any IT infrastructure, from the smallest text file to Big Data Hadoop clusters. RapidMiner enjoys the support of a thriv-ing community of contributors continuously discovering new applications and creating new extensions, covering a wide range of industries as well as research. Some notable Rapid-Minerextensions include R, Weka, and Hadoop. Processes designed with RapidMiner can be deployed to our RapidAna-lytics server with one click, hence instantly put to fruition as interactive reports and dashboards, as well as web services. In addition, Rapid-I has created a unique Marketplace where independent developers can publish and monetize their inno-vative extensions, further future-proofing every investment in RapidMiner and RapidAnalytics.

Thousands of applications of RapidMiner in more than 40 countries give their users a competitive edge. Among the users are well-known companies as Bank of America, PayPal, Merrill Lynch, BNP Paribas, MITRE, LexisNexis, GfK, Telenor, Ford, Honda, Nokia, Miele, Philips, IBM, HP, Cisco, Akzo Nobel, Aureus Pharma, PharmaDM, Cyprotex, Celera, Revere, and many medium-sized businesses benefitting from the power and flexibility of Rapid-I technologies.

Sponsor Profiles


KXEN www.kxen.comPod 10

KxEN is revolutionizing the way companies use predictive analytics to make better decisions. Based on patented innova-tions, the company’s flagship product, InfiniteInsight™, deliv-ers orders of magnitude improvements in speed and agility to optimize every step in the customer lifecycle - including acqui-sition, cross-sell, up-sell, retention and next best activity. With traditional predictive analytics approaches, businesses spend over two-thirds of their time on activities that are manual, repetitive and prone to human error. InfiniteInsight™ has proven that a large portion of this effort can be automated while delivering accurate and robust predictive models. In days, not months. Proven with over 400 deployments at com-panies such as Bank of America, Barclays, Wells Fargo, Lowe’s, Meredith Corporation, Rogers, and Vodafone, KxEN solutions deliver predictive power and infinite insight™. KxEN is head-quartered in San Francisco, California with field offices in the U.S., Paris and London.

Association Partners

IDMA www.IDMA.orgThe Insurance Data Management Association, Inc. (IDMA) is an independent, non-profit, professional association dedicat-ed to increasing the level of professionalism, knowledge, and visibility of insurance data management through education, research, and peer-to-peer networking.

For more information, visit www.IDMA.org

International Institute for Analytics www.iianalytics.comBooth 305

The International Institute for Analytics (IIA) is dedicated to the advancement of analytics in everyday business practices. Under the direction of Tom Davenport, IIA brings together the world’s leading analytics practitioners and researchers to provide unique insights to both business and IT leaders on the most current research findings and industry best practices.

For more information visit: http://iianalytics.com

INFORMS www.informs.orgBooth 104

The Institute for Operations Research and the Management Sciences (INFORMS) is the largest professional society in the world for those in the field of operations research (O.R.), management science, and business analytics. INFORMS serves the scientific and professional needs of Operations Research-ers and Analytics Professionals including educators, scientists, students, managers, analysts, and consultants. The Institute serves as a focal point for professionals, permitting them to communicate with each other and reach out to colleagues and the varied clientèle of the profession’s research and practice. Plan to attend INFORMS next Conference on Busi-ness Analytics and Operations Research, April 7-9, 2013, San Antonio, Texas.

Media Partners

AnalyticBridge www.analyticbridge.com

Analyticbridge is the leading social network for professionals with focus on predictive modeling, business analytics, quanti-tative finance, econometrics, web mining, text mining, opera-tions research, advanced web analytics, actuarial and decision sciences, scoring technology, KPIs and lift measurement, six sigma, risk management, bioinformatic, military intelligence and fraud detection. Founded in 2007, the network has grown to 35,000 members and operates the largest quant, bio-statistics and data mining LinkedIn groups.

CustomerThink www.customerthink.comCustomerThink is a global online community of business lead-ers striving to create profitable customer-centric enterprises. Each month, the site reaches over 200,000 subscribers and visitors from 200 countries via email, RSS, LinkedIn and Twit-ter. CustomerThink currently serves over 80,000 visitors per month. Our main areas of coverage are Customer Relation-ship Management, Customer Experience Management and Social Business. This is the place to learn about every facet of customer-centric business management in articles, blogs, interviews, and news.

Sponsor Profiles


Data Science Central www.datasciencecentral.comData Science Central is an online resource for Big Data Prac-titioners. Featuring news, commentary, and social network-ing, DSC covers analytics, visualization, integration, tools and trends, and also provides an outlet for career opportunities.

KDnuggets www.kdnuggets.comKDnuggets, Data Mining Community’s Top Resource for Data Mining and Analytics News, Software, Jobs, Consulting, and more.

IT Briefcase IT NEWS, RESOURCES, EVENTS

www.itbriefcase.net IT Briefcase is a focused online publication that attracts busi-ness and IT professionals who are actively researching busi-ness integration solutions.

Our growing audience can expect to view the most up to date industry news, articles, whitepapers, webcasts, and blogs in additional to IT Briefcase original editorial content showcased in the “Fresh Ink” and “IT Analyst Blog” sections of our web-site. Some of the topics we cover include Data and Analytics, Cloud Computing, Application Integration, Health IT and Open Source.

Smart Data Collectivewww.smartdatacollective.com Smart Data Collective is a curated writer’s forum and dis-cussion site published by Social Media Today LLC. We cover business intelligence, data analytics, risk management and related topics for an audience of business leaders and IT experts. In addition to our regular blog coverage, we also produce webinars, e-books, moderated Tweet chats and other forms of digital content. We provide a platform for rec-ognized, global authorities to share their insights about Big Data. Smart Data Collective is a rich resource for executives who seek cutting-edge analysis of the accelerating growth of data in our interconnected world

topseos www.topseos.com The independent authority on search vendors, topseos.com, evaluates and ranks the top internet marketing companies. Categories ranked by topseos include: search engine optimi-zation, pay per click management, affiliate marketing, social media optimization, and many more.

Since 2002, topseos has been a trusted resource for businesses looking to launch or improve internet marketing campaigns. The pathfinder service allows topseos to work directly with you to help find companies that best fit your business needs. Why waste time searching through thousands of sites with false promises? Go straight to the authority, gain insight into the industry, work with the best.

Visibility Magazine www.visibilitymagazine.com Visibility Magazine, founded in 2007, has become the guide to latest trends in internet marketing. Visibility conducts interviews with CEOs, shares opinions, reviews products, and provides a wealth of information about the movements in the industry. Additionally, Visibility will reach many fringe businesses that may have been contemplating entering or expanding their Internet marketing campaigns. Visibility is published quarterly and covers a wide range of topics includ-ing, but not limited to, organic optimization, pay-per-click marketing, website analytics, affiliate marketing, and press release distribution. Visibility embodies high-quality content, good sense, superior taste, and the character of conscientious journalism.

Sponsor Profiles

PRODUCED BY

Strengthening the Business ImpactThrough Predictive Analytics Deployment

www.pawcon.com

DÜSSELDORFNOV 6 - 7, 2012

LONDONNOV 27 - 28, 2012

SAN FRANCISCOAPR 14-19, 2013

JUNE 10-13, 2013

TORONTOMAR 18-21, 2013MAR 18-21, 2013

DÜSSELDORFNOV 6 - 7, 2012

LONDONNOV 27 - 28, 2012

SAN FRANCISCOAPR 14-19, 2013

JUNE 10-13, 2013

TORONTOMAR 18-21, 2013MAR 18-21, 2013

CHICAGOCHICAGO

EVENTS CALENDAR

www.risingmedia.com

Stockholm • Oct 15 - 16, 2012

Düsseldorf • Nov 6 - 7, 2012

Melbourne • Nov, 2012

London • Nov 27 - 28, 2012

Toronto • Mar 18 - 21, 2013

San Francisco • Apr 14 - 18, 2013

Chicago • June 10-13, 2013

Ft. Lauderdale • Oct 9 - 11, 2012

Stockholm • Oct 15 - 16, 2012

Toronto • Mar 18 - 21, 2013

München •�Apr 9 - 10, 2013


London • Nov 27 - 28, 2012

Toronto • Mar 18 - 21, 2013


Chicago • June 10-13, 2013


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Ft Lauderdale • Oct 28 - Nov 1, 2012

Las Vegas • Nov 11 - 15, 2013

Helsinki • Oct 17 - 18, 2012

Toronto • Mar 18 - 21, 2013


Chicago • June 13 - 14, 2013

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London • Nov 27 - 28, 2012


Chicago • June 11 - 12, 2013

London • Nov 15 - 16, 2012

Berlin • Feb 2013

Hamburg • Nov 12 - 13, 2012

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.....................San Francisco • Apr 15 - 17, 2013



· day 1: monday, october 1, 2012 7:30-9:00am registration & breakfast lroom: commonwealth hall...

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