Innovators’ summIt

See data. Solve problems.

October 14-16, 2007 Grand Traverse Resort and Spa Traverse City, Michigan

Break through to discovery.

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Welcome to the Innovators’ Summit, custom designed for you.

Data visualization inspires innovation. As the developers of statistical discovery

software, we like to hear inspiring stories of discoveries — discoveries in business,

in healthcare, in product development, you name it.

After years of hearing these remarkable stories ourselves, we thought it was time

to bring innovators together to benchmark best practices, share stories of analytic

excellence, and compare strategies for becoming a catalyst for change.

As Dimitri Mavris, Director of Georgia Tech’s Aerospace Systems Design Lab,

said after a conference many years ago: “I watched a demo about mice, and

I saw rockets.” When you hear Dimitri speak on Monday, perhaps you’ll hear

about rockets and see your own path to innovation.

Innovators’ summIt

John SallCo-Founder and Executive Vice President, SAS

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TABLE Of cOnTEnTs

SUMMIT agenda 4

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faST facTS 24

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sunday, October 14

11:00 a.m.-5:00 p.m. Registration open

11:00 a.m. Complimentary Golf Outing or Spa Session (See details in Fast Facts, page 24.)

6:00 p.m Cocktail Reception

7:00 p.m. Welcome Dinner

Monday, October 15

7:30 a.m. Registration and Continental Breakfast

8:30 a.m. Welcome

9:00 a.m. Extending the Reach of Analytic Excellence Moderator: Scott Lasater, TQM Network

Michael Schrage, MIT

Stu Hunter, Princeton Univ.

Chris Nachtsheim, Univ. of Minnesota

Dimitri Mavris, Georgia Tech

Noon Lunch

1:30 p.m. Concurrent Breakout Sessions Tim Pletcher Bruce Knoebel Central Michigan University Eastman Kodak

2:15 p.m. Break

2:30 p.m. Concurrent Breakout Sessions Steve Fowler Michael Schrage First Solar MIT

3:15 p.m. Break

3:30 p.m. Concurrent Breakout Sessions Cy Wegman & Kevin Norwood Jane Damschroder Procter & Gamble CheckFree

4:15 p.m. Q&A with afternoon speakers

4:30-5:30 p.m. Cocktail Reception

A mix of plenary addresses, panel discussions and small-group sessions offer a variety of opportunities for exploring the path to innovation. We’re setting aside time for recreational opportunities, too.

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The agenda is subject to change without notice.

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Tuesday, October 16

8:00 a.m. Continental Breakfast

9:00 a.m. Plenary Keynotes and Panel Discussion Applying Creative Analytics for Innovation Moderator: Scott Lasater, TQM Network

John Sall, SAS

Dick De Veaux, Williams College

Bradley Jones, SAS

Noon Lunch

1:30 p.m. Concurrent Breakout Sessions Mike Cramer Sara Bennett & Eric Myers McDonald’s PNC Bank

2:15 p.m. Break

2:30 p.m. Concurrent Breakout Sessions Chris Peterson Byron Wingerd Capital One Emergent BioSolutions

3:15 p.m. Q&A for afternoon speakers

3:30 p.m. Closing Reception

SCOTT LASATERDirector of Lean Six Sigma Enterprise Institute, TQM Network

Scott Lasater, who will serve as moderator for plenary sessions

Monday and Tuesday mornings, is known around General

Electric as “the guy who taught Six Sigma to (retired CEO) Jack

Welch.” More recently, he has advised Jeff Immelt, the current

GE CEO, on the integration of Lean and Six Sigma. As Master

Black Belt and Director of Global Lean Six Sigma Training, he

has trained more than 5,000 business leaders around the world.

Recently appointed Director of the Lean Six Sigma Enterprise

Institute for the TQM Network, Lasater continues this success. In the last three years alone,

his Black Belt students saved their own organizations more than $450 million.

Lasater has trained and implemented business optimization, quality management and

statistical methods for a variety of organizations, including Wal-Mart, Home Depot, Colgate-

Palmolive, Navistar, Quizno’s, Regal-Beloit, Rheem, Carrier, the State of Indiana and The

Cleveland Clinic. He has a master’s degree in applied industrial statistics from the University

of Tennessee and bachelor’s in psychology from Duke University. Most disturbing, however,

may be his background as a professional drummer and stand-up comedian.

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MICHAEL SCHRAGEMIT Researcher and Author

Making Models Matter More: From Analytic Excellence to Operational Influence

The purpose of computing is insight, not numbers. But converting statistically compelling

“insights” into “influence” that changes minds and changes behavior is hard. Increasingly,

organizational challenges are more difficult for modelers to surmount than technical challenges.

Drawing upon extensive real-world research and practice, this talk will offer usable frameworks

for how models can be platforms for persuasion as well as tools for analysis.

An MIT researcher and executive education lecturer, Michael

Schrage has been co-director of the MIT Media Labs eMarkets

Initiative and a pioneer in the economic sociology of modeling,

simulation and experimentation in organizations. His work

focuses on how models, prototypes and simulations are

used to align “innovation markets.” He has advised a variety

of global organizations, including Microsoft, Google, BT, BP,

Wells Fargo, Mars, Fidelity/Devonshire Partners and Siemens.

He is the author of Serious Play: How the World’s Best Companies Simulate to Innovate

(Harvard Business School Press, 1999) and other books and articles on the economics

of innovation.

Extending the Reach of Analytic ExcellenceMICHAEL SCHRAGEMIT Researcher and Author

STU HUNTERProfessor Emeritus, Princeton University

CHRIS NACHTSHEIM Chair, Operations and Management Sciences, Carlson School of Management, University of Minnesota

DIMITRI MAVRIS Boeing Professor of Advanced Aerospace Systems Analysis Guggenheim School of Aerospace Engineering, Georgia Institute of Technology

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STU HUNTERProfessor Emeritus, Princeton University

Modern Time Series Approaches for Quality in Manufacturing: Moving Beyond Run Rules and Control Charts

Move beyond today’s commonly used control chart methodology to improve your processes

using modern time series approaches. Shewhart, Cusum and Exponentially Weighted Moving

Average (EWMA) charting methods are based on the assumption that the successively plotted

points are stochastically independent. The charts are known to be “robust” to many violations

of assumptions, but in modern manufacturing being “robust” is not enough when it results in

ignoring information resting in a data trace. The good news is that today’s software makes it

easy to fit stochastic models to time sequenced data and then to forecast, adjust and minimize

variability about a target. The quick identification of special causes of poor performance is also

assured. In today’s world of quality challenges, the time series aspects of process data should

no longer be ignored.

This presentation will exposit the use of autocorrelations in process modeling, emphasize

forecasting for control, elucidate the bounded control chart and describe the remarkable time

series qualities of the EWMA. The influence of changing time intervals between observations

will also be discussed. The intersecting roles of the classical quality engineer with that of the

engineering process control engineer will become obvious.

J. Stuart Hunter, PhD, is Professor Emeritus at Princeton’s

School of Engineering and Applied Science. His areas of

concentration include industrial applications of statistics, the

fractional factorial, and response surface experimental design.

Hunter co-authored Statistics for Experimenters with George

E.P. Box and W.G. Hunter. He is the author of the textbooks

Design of Experiments and Statistics for Problem Solving and

Decision Making. He was the founding editor of Technometrics,

the quarterly journal co-published by the American Society for Quality (ASQ) and the

American Statistical Association (ASA). He served as ASA president in 1993. His many

honors include two from ASQ: the Brumbaugh Award in 1959 and 1985 and Shewhart

Medal in 1970. He received his bachelor’s degree in electrical engineering from North

Carolina State University, as well as a master’s degree in engineering mathematics and

a doctorate in experimental statistics from the same institution.

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CHRIS NACHTSHEIMChair, Operations and Management Sciences Carlson School of Management, University of Minnesota

Custom Design of Experiments Using JMP® Software: No Pain. Just Gain.

This presentation offers a modern approach to designing experiments that makes DOE simpler,

cheaper and even more powerful than textbook methods. It is geared toward innovators who:

Find that textbook designs don’t quite match experimental requirements.

Have dozens of factors to screen.

Sometimes need to run mixture experiments while also changing process variables.

Want to perform response surface experiments with categorical factors.

Occasionally find that a completely randomized design is too hard or too expensive.

Need to prevent process drift from damaging experiment results.

Prefer to specify the number of runs instead of having the sample size dictated.

Christopher Nachtsheim, PhD, specializes in experimental

design, regression, and analysis of variance, and has

co-authored several related books, including Applied Linear

Regression Models and Applied Linear Statistical Models.

He teaches university courses and works as a consultant

on experimental design and using data analysis for decision

making. His clients include government organizations and

companies in the oil and gas, consumer products and banking

industries. He has served as an examiner for the Malcolm Baldrige National Quality Award.

Nachtsheim holds a PhD in operations research from the University of Minnesota, and

an MS in operations research and statistics from Rensselaer Polytechnic Institute.

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DIMITRI MAVRISBoeing Professor of Advanced Aerospace Systems Analysis Guggenheim School of Aerospace Engineering, Georgia Institute of Technology

Advanced Systems Design at Georgia Tech’s ASDL

The Aerospace Systems Design Laboratory creates unique and innovative methodologies for

the design and assessment of technologies of complex vehicles, systems, and system-of-

systems. ASDL’s portfolio of methodologies and applications includes formulation, development

and implementation of comprehensive approaches to the design of affordable and high-quality

complex systems.

The methodologies developed at ASDL enable communication between the technical details

and program management structure by speeding up design cycle time through the use of

surrogate modeling and probabilistic assessment of assumptions. Technologists present the

engineering data in a format that is communicable to specialists in other areas of expertise,

project managers and decision-makers. In his presentation, Mavris will demonstrate the enabling

capabilities built into JMP to facilitate the mode of communication by showing examples that

have been created in conjunction with ASDL activities.

Dimitri Mavris, PhD, serves as Director of Georgia Tech’s

Aerospace Systems Design Laboratory (ASDL), which he

co-founded in 1992. He teaches classes on advanced design

methods, fixed-wing vehicle design, and air-breathing

propulsion design and involves students in his research.

Mavris seeks undergraduate participation in the aerospace

engineering community by creating opportunities within

ASDL and by sponsoring design teams such as the AIAA

Design-Build-Fly competition.

He has pursued closer ties between the academic and industrial communities. ASDL

has been designated a Center of Excellence in Robust Systems Design and Optimization

under the General Electric University Strategic Alliance, and by NASA under the University

Research Engineering Technology Institute (URETI) on Aeropropulsion and Power

Technology program. ASDL is a member of the Federal Aviation Administration’s Center

of Excellence.

In 2004, Mavris was recognized as a Fellow of the National Institute of Aerospace.

He serves as Co-Director of NASA Glenn’s URETI on Aeropropulsion and Power and

is a two-time winner of Georgia Tech’s prestigious Outstanding Development of

Graduate Assistants Award.

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TIM PLETCHERDirector of Applied Research, Central Michigan University Research Corp.

Developing the Corporation’s Analytics Road Map

This presentation shares some of the wisdom gleaned from the work to develop a BI Road Map

by CMU Research Corporation’s Business Intelligence (BI) research committee. The material

covered integrates the committee’s efforts and strategies suggested in contemporary literature

on how best to evolve an organization from a culture of purely intuition-oriented decision making

to one that values and is capable of data driven, fact-based, and model-assisted corporate

decision making.

Through the Central Michigan University Research Corp.

(CMU-RC), Tim Pletcher directs business intelligence and data

mining projects in concert with faculty experts. His work has

supported such companies as General Motors, Dow Chemical,

International Paper, Eli Lilly, EDS and Henry Ford Health System.

CMU-RC (www.cmurc.com) provides a low-risk means for

companies to gain insight from their data and apply advanced

analytics for data and model-driven decision making.

Pletcher also shares an appointment with The Herbert H. and Grace A. Dow College of

Health Professions at CMU, where he is Director of Information Technology. He is program

director for the Michigan Health Information Alliance, focused on using health information

technology and the creation of a Health Information Exchange to improve the quality of

care in Michigan’s Central Medical Trading Area. Before joining CMU-RC, Pletcher was

Chief Technology Officer at a start-up company in New York City specializing in electronic

commerce and customized supply chain automation. For more than a decade he was

Director for Advanced Technology and Business Information Systems at the University of

Michigan Health System (UMHS). He earned his bachelor’s degree from the University of

Michigan, and a master’s degree from CMU.

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BRUCE KNOEBELSenior Research Statistician, Eastman Kodak

The Application of Mixture Designs for Formulation and Commercialization of Inkjet Inks

Inkjet inks are comprised of a number of chemical components that are mixed together to

produce a solution with certain physical, chemical and image performance properties.

Because the properties of an ink are determined by the relative proportions of the components

in an ink, experimental designs and evaluations require the use of mixture design methodologies

to maximize both their efficiency and their efficacy.

This talk will present the types of designs that have been used to identify an optimal ink

formulation in research as well as the types of designs that have been used to demonstrate

the robustness of an ink formulation for production.

While commercial software is used for the mixture design and initial analysis of the mixture data,

custom in-house software has been developed for a more complete and in-depth analysis,

understanding and display of our data. The software uses a combination of Microsoft Excel

(for data input and output tables) and SAS (DDE, Macro, IML, Graph) to generate the needed

analyses and data displays. An overview of the numerical output and graphical displays from

the software will be presented.

Bruce Knoebel, PhD, works in the Inkjet Ink Research Division

of Research Labs at the Eastman Kodak Company, applying

and developing methods for the application of mixture designs

to inkjet ink formulations and commercialization. Since joining

Kodak in 1985 he has provided statistical support across a

broad range of technologies throughout the company, including

film emulsion design and thin film coating, synthetic chemical

development, image science, electrostatics, vacuum deposition

and medical imaging.

In addition to his consulting responsibilities, Knoebel has also developed and taught

numerous courses to hundreds of Kodak employees.

Knoebel holds a PhD from Virginia Tech, where he also earned master’s degrees in forest

biometrics and statistics. He is a certified Six Sigma Black Belt Instructor.

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STEVE FOWLERDirector of Continuous Improvement, First Solar

First Solar: Selecting Six Sigma Strategies that Shine

When the business environment is dynamic and growth-oriented, not all Six Sigma tools

can foster innovation and improvement. This session looks at what works — and what

doesn’t — for First Solar, a maker of solar electric power modules. Examples include a practical

robust optimization of a non-contact surface resistivity measurement system and the use of

POV to prioritize further engineering characterization, root cause and design of experiments.

Steve Fowler works to foster a mindset of world-class

continuous improvement at First Solar, an industry leader in

the manufacturing of thin film solar modules. He also seeks to

ensure that First Solar achieves optimum deployment of the

most effective continuous improvement tools throughout the

organization. Fowler seeks breakthrough improvements by

identifying and optimizing the most critical process variables that

affect key performance metrics. Earlier in his career, he worked

14 years in the disk drive industry as an integrator and optimization specialist of thin film

magnetic recording heads. Before joining First Solar, he worked for Applied Magnetics

Corp. in Goleta, CA, and Read-Rite and Maxtor Corp. in Milpitas, CA. He received his

BSEL degree in 1990 from California State Polytechnic University in San Luis Obispo.

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MICHAEL SCHRAGEResearcher and Author

Modeling Economics 101: Innovation Risk Management

Building upon and extending the themes of the Monday morning keynote, this workshop goes

into greater detail and depth as to how simple economic principles can help modelers get

more value and more use from the models they build. Ideally, this session will be interactive and

participants are expected to bring issues, concerns and examples for the group to discuss.

Attendees should leave the session with next steps in mind and in plan.

An MIT researcher and executive education lecturer, Michael

Schrage has been co-director of the MIT Media Labs eMarkets

Initiative and a pioneer in the economic sociology of modeling,

simulation and experimentation in organizations. His work

focuses on how models, prototypes and simulations are used

to align “innovation markets.” He has advised a variety of global

organizations, including Microsoft, Google, BT, BP, Wells Fargo,

Mars, Fidelity/Devonshire Partners and Siemens. He is the

author of Serious Play: How the World’s Best Companies Simulate to Innovate

(Harvard Business School Press, 1999) and other books and articles on the economics

of innovation.

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KEVIN NORWOODLaundry Modeling & Simulation Research Fellow, Procter & Gamble

CY WEGMANCorporate Modeling Simulation & Analysis Section Head, Procter & Gamble

Design of Experiments at P&G

Design of experiments is an integral part of product and process development at P&G. DOE is

used to build empirical models of product and process performance that drive better innovation,

efficiency and speed to market. P&G uses a wide range of DOE, statistical analysis, visualization

and optimization tools in JMP. This presentation will show some of the philosophy behind the

use of DOE and give some examples of practical application.

Kevin Norwood, PhD, works in Procter & Gamble’s Laundry

Formulation business, identifying, developing and deploying

modeling techniques. Recently he has expanded his work to

emphasize integration of models across disciplines. He came

to work at P&G in 1991 and has held various assignments in

R&D, in such areas as Analytical Science and Technology and

Formulation, where he has spent the majority of his career. He

received a PhD in physical chemistry from Iowa State University.

Cy Wegman oversees all design of experiment (DOE) and

process definition courses for P&G and supports P&G business

units around the world in the area of DOE. He has worked

at P&G for 30 years. For the last 10 years, he has worked in

Corporate Modeling & Simulation with other experts in reliability

engineering, optimization and empirical modeling. Earlier,

Wegman worked in P&G’s Family Care business, focusing on

DOE and statistical process control. He also has worked in

brand initiatives, process startups, material supply, reliability and quality control. Before

joining P&G Wegman worked in paper manufacturing for 10 years. He graduated in 1977

from Rose-Hulman Institute of Technology with a bachelor’s degree in civil engineering.

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JANE DAMSCHRODERSenior Business Analyst, CheckFree Corp.

Missing e-Bills Detection

The Electronic Commerce division of CheckFree Corp. provides solutions that enable thousands

of financial services providers and billers to offer the convenience of receiving and paying

household bills online, via phone or in person through retail outlets. One of the solutions offered

is the electronic delivery of bills via the Internet, a service currently provided at more than 2,000

sites. Through cooperative distribution agreements with over 450 billers, CheckFree delivers

more then 58.7 million bills electronically each quarter. Replacement of paper bills with electronic

delivery results in a significant cost savings to the biller and improved convenience and security

to the consumer.

The goal of this project was to develop a system and processes that would allow proactive

identification of potentially “missing bills.” Once a bill is identified as missing, the biller can send

the affected bills to CheckFree and CheckFree, in turn, delivers the bill to the consumer, thereby

avoiding any late payment issues.

The Missing e-Bills application is based on the Exponentially Weighted Moving Averages

(EWMA) data model. The EWMA model is used to determine when unusual behavior is exhibited

by a biller.

Jane Damschroder works in CheckFree’s Electronic

Commerce Division, providing operational analysis and support

for CheckFree solutions that enable thousands of financial

services providers and billers to offer the convenience of

receiving and paying household bills online, via phone or in

person through retail outlets. She was recently recognized

as a top company performer with her selection to the 2007

Chairman’s Club, an associate incentive program which honors

approximately 100 associates companywide each year. Before joining CheckFree in 1995,

Damschroder was Manager of Project Services at Survey Sampling Inc., a global provider

of Internet, telephone, mail and in-person sampling solutions to the survey research

industry. She is a graduate of Bowling Green State University.

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Applying creative Analytics for innovationJOHN SALL Co-Founder and Executive Vice President, SAS

DICK DE VEAUX Professor, Department of Mathematics and Statistics, Williams College

BRADLEY JONES Senior Manager for Statistical Research and Development, SAS

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JOHN SALLCo-Founder and Executive Vice President, SAS

Dynamic Graphics Drive Discovery, and Discovery Drives Innovation

Innovation does not arise from blind creativity. Visualizing data gives us eyes on problems and

opportunities. We see data from products and processes, data from experiments, data from

needs and desires, and even data that we make from computer models. This is the way we see

forward to new solutions. One key to innovation is to put computer visualization techniques to

work in the richest and easiest ways. The result helps us see more things and gives us more

insight into problems and opportunities. There are many new ways to harness the computer and

its graphics power that extend our investigative skills.

Who knew data analysis could be fun? John Sall did. That’s

why Sall, one of the founders of business intelligence software

giant SAS, began a SAS business unit in 1989 devoted to

creating interactive and highly visual data analysis software for

the desktop. The resulting software, JMP, dynamically links

statistics with graphics, empowering users to explore their

data interactively.

Nearly 20 years later, he remains the lead architect for JMP

statistical discovery software, now used by more than 200,000 researchers and engineers

to promote quality initiatives, empower Six Sigma programs and create R&D environments

where innovation rules.

In addition to his responsibilities at JMP, Sall is also Executive Vice President of SAS, which

he co-founded in 1976. He received a bachelor’s degree in history from Beloit College in

Beloit, WI, and a master’s degree in economics from Northern Illinois University in DeKalb.

Sall has held several positions in the Statistical Computing Section of the American

Statistical Association (ASA) and was named an ASA Fellow in 1998. He is a past

president of the North Carolina chapter. He serves on the board of directors of the

Nature Conservancy.

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Professor, Department of Mathematics and Statistics, Williams College

Data Mining in the Real World: Five Lessons Learned in the Pit

Data mining has been defined as a process that uses a variety of data analysis and modeling

techniques to discover patterns and relationships in data that may be used to make accurate

predictions and decision. Isn’t this what statistics does? Are the two really different? Through

a series of case studies, we will try to illuminate some of the challenges of data mining and

highlight some of the differences between data mining and traditional statistical analysis. We’ll

also show how to avoid the major pitfalls as you embark on your own data mining project.

Richard D. De Veaux, PhD, is an expert in applied statistics.

His professional interests include data mining methodology and

its application to problems in science and industry, as well as

model selection and other problems for large data sets.

De Veaux holds a doctorate in statistics and a master’s degree

in education from Stanford University. A summa cum laude

graduate of Princeton University, he earned bachelor’s degrees

in civil engineering and mathematics. A Fellow of the American

Statistical Association and the author of many research papers, he is co-author, with Paul

Velleman and David Bock, of several critically acclaimed textbooks, including Intro Stats

and Stats: Data and Models.

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BRADLEY JONESSenior Manager for Statistical Research and Development, SAS

Design and Analysis of Computer Experiments: A New Approach

In an effort to speed the development of new products and processes, many companies are

turning to computer simulations to avoid the expense and lost time of building prototypes. These

computer simulations are often very complex, and it may take hours to complete a single run. If

there are many variables affecting the results of the simulation, then it makes sense to design an

experiment to gain the most information possible from a limited number of computer simulation

runs. The absence of noise is the key difference between computer simulation experiments

and experiments in the real world. Since there is no variability in the results of computer

experiments, optimal designs based on reducing variance have questionable utility. Replication,

usually a “good thing,” is clearly undesirable in computer experiments. Thus, a new approach to

experimentation is necessary.

JMP® 7 introduces new designs and also a new fitting method specifically created to address

the unique behavior of computer simulation models. This talk takes a case study approach

using computer models to demonstrate both the new computer simulation design and analysis

features in JMP 7.

Bradley Jones leads the development of design of experiments

(DOE) capabilities in JMP software from SAS. Jones architected

the JMP Custom Designer, a general and powerful tool for

generating optimal experimental designs. He holds a patent

on the use of DOE for minimizing registration errors in the

manufacture of laminated circuit boards and is the inventor of

the prediction profile plot for interactive exploration of multiple

input and output response surfaces.

Prior to joining SAS in 1997, Jones was the principal statistician at The MathWorks Inc.,

where he designed and implemented the MATLAB Statistics Toolbox, a set of over 200

statistical functions. Jones is widely published on DOE in research journals and the

trade press.

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MIKE CRAMER Director of Operations Research for Worldwide Restaurant Innovation, McDonald’s

Maximizing Restaurant Capability: McDonald’s Pursuit of Operational Excellence

McDonald’s is the world’s largest QSR company, with over 33,000 restaurants in 118 nations.

Our quest for excellence as a service provider has propelled us to new innovative dimensions,

with a concentration on creating the “Flexible Operating Platform” that will enable strategic

growth in all top markets. To reach our goals, we have invested in innovation and operations

research. A significant part of that investment is the design and development of a unique

portfolio of tools to accelerate operating platform design, development, testing and

deployment. This portfolio includes Lean Six Sigma methodologies, video ethnography,

data mining/analysis, engineered standards, dynamic ergonomic assessment and discrete

event/agent-based modeling.

We will review our portfolio of tools and techniques and demonstrate how we have used these

to make critical business decisions.

Mike Cramer leads a corporate group of 12 analysts providing

decision support for operations at 34,000 restaurants in

118 global markets. His team’s work includes data modeling,

ethnography and data mining. Before joining McDonald’s

three years ago, Cramer was CLO for Hub One Logistics for

eight years. He also has worked for Kellogg’s in Logistics and

Competitive Intelligence, and for Tompkins Associates, an

engineering consulting and implementation firm. He serves on

the Council of Logistics Management, INFORMS and was a 1996 Edelman Award Finalist.

He graduated in 1984 with a bachelor’s degree in information science from North Carolina

State University.

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SARA BENNETTBusiness Analyst, Program Evaluation, PNC Financial Services Group

ERIC MYERSVice President & Group Manager, Predictive Analytics and Program Evaluation PNC Financial Services Group

Building a Test-and-Learn Discipline at PNC

This presentation speaks about our challenges, opportunities and successes in building a

test-and-learn discipline within PNC. It addresses such issues as cultural and organizational

challenges, how we have approached these challenges and the results we are seeing. Using

several case studies, we will discuss our journey and highlight what has worked for us – and

what hasn’t worked. Finally, we will talk about what’s next in our world and how we hope to

continue to develop analytical excellence within PNC.

Sara Bennett leads the implementation of a test-and-learn

culture at the analytical level, finding innovative methods for

applying test-and-learn principles to PNC’s marketing activities.

She also manages the day-to-day analytical activities around

test-and-learn and the education of nonstatistical business

partners on the value of sound experimental design. Bennett

joined PNC Financial in 2006 and has 10 years of experience

as a statistical analyst. Earlier, she worked for Highmark Blue

Cross Blue Shield and Mellon Financial. Bennett earned a bachelor’s degree from Carnegie

Mellon University and a master’s from Duquesne University.

Eric Myers provides leadership in creating, identifying and

delivering data-driven insights and actions that will achieve

breakthrough results for PNC Financial Services Group. In

1999, he created the data mining team at PNC. He continues

to lead that group while now developing a new test-and-learn

discipline. Myers has 15 years of experience in the fields of

statistical modeling, statistical consulting, data mining and

experimental design. He joined PNC Financial in 1996. Earlier,

he held analytical positions with Kraft Foods and Reese Brothers. Myers earned a

bachelor’s degree from Clarion University and a master’s from West Virginia University.

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CHRIS PETERSONSenior Statistical Analysis Manager, Capital One Financial

Driving Business Strategy Through Rigorous Analytics

Like many other industries, the financial services sector is highly competitive, heavily regulated

and operates in a rapidly changing marketplace. However, the availability of vast data resources

containing information about customer behavior implies that a significant competitive advantage

can be achieved by effectively utilizing that information. To this end, Information Based Strategy

(IBS) has been at the heart of Capital One’s business philosophy since the early 1990s and an

integral part of the company’s success.

However, as the competitive landscape evolves the analytic competencies needed to sustain

or grow any competitive advantage must also increase. This presentation will explore different

ways companies can use improved data quality, data access, targeted testing, analytic tools and

methods to drive business strategy and better compete in the future.

At Capital One Financial, Chris Peterson focuses on strategic

credit policy testing, risk management and financial forecasting.

Before joining Capital One’s Richmond, VA, office a year ago,

Peterson worked at Intel Corp. for several years in a variety of

areas, including technology development, inventory modeling,

supply chain optimization, accelerated life and degradation

modeling, supplier audit methodology and advanced predictive

modeling. He received numerous divisional and corporate

awards for his contributions. Peterson holds a master’s degree in statistics from Brigham

Young University with thesis work in detecting and monitoring spatial defect densities in

IC fabrication.

TuEs

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BYRON WINGERDPrincipal Scientist, Emergent BioSolutions

Using Monte Carlo Simulation to Predict Defect Rates for Process Control Scenarios in a Biological Process

You may not be in the vaccine production market, but we bet you can benefit directly from

lessons learned in how to improve production from pilot-scale to large-scale manufacturing.

This talk will focus on issues with building models based on the variation in production data,

validating the model predictions to actual data, employing the model with Monte Carlo

simulation across design points that fill the space of all the Xs (space-filling designs) in your

models and, finally, conducting what-if scenarios to determine process specifications for the

scaled-up factory production process.

Byron Wingerd, PhD, is a member of the Technical

Development and Continuous Improvement groups at the

BioDefense Operations campus for Emergent BioSolutions, a

biopharmaceutical company in the business of protecting lives.

Working at the company’s Lansing, MI, office, he is currently

involved in a vaccine manufacturing scale-up project and the

improvement of existing process metrics and controls. Wingerd

received a joint doctoral degree from the Department of Cell

and Molecular Biology and the Department of Microbiology at Michigan State University.

He was trained as a Green Belt in Six Sigma by Dr. Tom Little as part of the Emergent

BioSolutions Lean6 Initiative.

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Innovation is fun and exciting — but it’s also hard work. So we’re offering some opportunities for relaxation, described below. You’ll also find helpful hints about dining and airport transportation. If you have questions about these or other topics related to the Innovators’ Summit, please feel free to ask any member of the JMP team or contact Robin Hughes at (919) 601-7733.

cOMPLiMEnTARy gOLf OuTingSunday, 11 a.m., The Bear

If you preregistered for the optional golf outing, make

your way to The Bear course Sunday morning in time for

the 11 a.m. shotgun start. Unfortunately, we cannot

accommodate participants who did not sign up in advance.

Golf outing details:

Box lunch will be provided.

If you requested rental clubs, they will be available at the pro shop.

Please wear proper attire: collared shirt, long pants or walking shorts. The resort does

not allow T-shirts, tank tops, athletic shorts, cutoffs or jeans on the golf course. Metal

spikes are not permitted. Golf shoes may be respiked at the pro shop for $8 per pair.

No coolers are allowed on the course.

sundAy sPA sEssiOnBy appointment

Instead of golf, would you enjoy a massage? Or maybe

a facial? If you registered in advance for a complimentary

Sunday treatment at the Spa Grand Traverse, you should

have received notification of your appointment. If you do not

have that information, or if you would like to know whether

complimentary sessions are still available, please contact

Robin Hughes at (919) 601-7733.

fAsT

fAc

Ts

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MOndAy nigHT dinnER On yOuR OWn

Select from one of several resort restaurants, or gather some fellow conference-goers and

consult the concierge for suggestions about dining opportunities in town. The resort offers

a wide range of dining choices:

AERIE – Located on the 16th floor of the Tower, the newest of the resort’s restaurants

features linen tablecloths and a scenic view of Grand Traverse Bay and the resort’s fine

golf courses. There’s an extensive wine list to pair with a menu featuring regional fare.

SWEETWATER AMERICAN BISTRo – With a wide selection of simple fare — from pizza

and burgers to fish and chicken — this restaurant is located just off the Grand Lobby.

THE GRILLE – Enjoy dinner at this Clubhouse restaurant and choose from entrees

including fish, ribs or pasta — or soup and salad.

GRAND LoBBy BAR, JACK’S SPoRTS BAR and MARKETPLACE also offer

food selections.

AiRPORT TRAnsPORTATiOn

For complimentary shuttle transportation to Cherry Capital Airport (TVC) at the end of the

summit, please make arrangements in advance at the hotel bell stand. You also can contact

the bell captain at (231) 534-6420, or dial ext. 6420 from a hotel phone.

Need a cab? Contact Traverse City Cab Company at (231) 929-2826.

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nOTE

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You’re there. You’re here, you’re there, you’re in places you’ve never been, discovering things you never expected.

With JMP® software, you don’t just see your data. You explore it. You experience it. You understand it.

JMP statistical discovery software is dynamic, interactive and fun. It’s data exploration at its best.

It’s data visualization from SAS. www.jmp.com/there

SaS and all other 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. copyright © 2007 SaS Institute Inc. cary, nc, USa. all rights reserved. 452069US.0907