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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
MOndaY KeYnOTe SeSSIOnS 6
MOndaY cOncUrrenT SeSSIOnS 10
TUeSdaY KeYnOTe SeSSIOnS 16
TUeSdaY cOncUrrenT SeSSIOnS 20
faST facTS 24
nOTeS 26
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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.
AgEn
dA
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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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