Past Center for Business Analytics Events

Christina Qi Analytics Summit 2023 Opening Keynote

Christina Qi, CEO @ Databento

"2023:  Fantastic Machines and How to Tame Them"

Bio:  Christina is an expert in the field of Artificial Intelligence and cloud computing and holds her BS in Management Science from MIT. A Forbes "30 Under 30" honoree, Christina is a Member of MIT's Board of Trustees. She has deep expertise in data science, data management, and related fields. In her talk, she will explore the meteoric rise and unintended consequences of the latest trends, including CHatGPT and Lensa, and the inevitable decision that every company will have to make (bot or no bot)?. Through personal stories and unexpected encounters, she’ll discuss data access and affordability (why does the cost of data rise each year?) as well as common biases when analyzing data (why does it work in simulation but not in the real world?). She  will explore the advantages and short comings of theses technologies in our daily lives.

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Xiao-Li Meng Analytics Summit 2023 Closing Keynote

Xiao-Li Meng, Jones Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review

“Being, Training, and Employing Data Scientists:   Wisdoms and Warnings from Harvard Data Science Review”

Abstract: “What Does It Take to Be a Successful Data Scientist?” “Is Data Science Education a Jack of All Trades?” “How Can We Train Data Scientists When We Can’t Agree on Who They Are?” These thought-provoking questions are the titles of articles in Harvard Data Science Review (HDSR). This talk surveys and reflects on data science training, employment and deployment in the BIG (Business, Industry, and Government) world based on such articles, and many more.

Bio: Xiao-Li Meng, the Founding Editor-in-Chief of Harvard Data Science Review and the Whipple V. N. Jones Professor of Statistics, is well known for his depth and breadth in research, his innovation and passion in pedagogy, his vision and effectiveness in administration, as well as for his engaging and entertaining style as a speaker and writer.


  1. Business Intelligence
  2. Advanced Analytics
  3. Operations Analytics
  4. Public Analytics
  5. Commercial Analytics

The Data Science Symposium 2022 was held on November 8, 2022 in the Lindner College of Business at the University of Cincinnati.  This in-person, all-day event included three featured speakers, two sixty-minute Tech Talk track sessions with four presentations in each track (eight total), and a post event reception.

Featured Speakers (everyone attends)

  1. Bill Inmon (Father of the Data Warehouse), Forest Rim Technology:  "Data Lakes Part 2"
  2. Stefan Karisch Amazon: “Operations Research & Analytics at Amazon"
  3. Ethan Swan,  ReviewTrackers:   "From Models to Value through ML Engineering"
Tech Talk Session Speakers : Two sessions with four concurrent talks in each:  (choose one talk in each session).  
  • Spencer Baucke, PhData:  "Enabling Power BI and Snowflake"
  • Dungang Liu, UC: "Sing a song without P-values: embracing analytics tools leading to insights and actions"
  • Doug Meiser: Amend Consulting, "How to Prepare Your Data Science Teams for a Recession"
  • Jesse Piburn, Oak Ridge National Labs: "Advances in Geographic Data Science..."
  • Jeff Gunderson, Delta Analytics: "Collaboration with Jupyter Notebooks"
  • Derrick Martin & Darryl Gleason, Nationwide Insurance: "Emerging Trends in Data Science"
  • Yan Fu, Ford Motor Company  "Leveraging Data, Insight and Analytics to Help Build a Better Sustainable World"
  • Kris Still & Johhny Avant, CoStrategix: "The Sounds of Silence: Reducing Noise One Iteration at a Time with Transfer Learning and Synthetic Data"
Andrew Walter Keynote Speaker

Opening Keynote Speaker

"Waiting is Not an Action:  World-Class Data & Analytics Leadership is Needed Now!"

Andy Walter
P&G (retired) / AJW-Advisory LLC

With two years now of incredible disruption, transformation, and acceleration across every industry, the Data & Analytics Leadership needed now is changing rapidly. Andy Walter – Board Director & Strategic Advisor and Author of Waiting is Not an Action, will explore the latest industry trends and insights from over twenty Analytics Leaders, and provide actionable steps for you now and into the future.



Kathy Koontz Keynote Speaker

Closing Keynote Speaker

"Building a Modern Data Strategy"

Kathy Koontz
Amazon Web Services 

Applying old organizational models and methodologies to modern cloud technology won’t allow companies to achieve the kind of results and agility they expect. Companies need an operating model, organizational model, and data literacy approach that enables data-driven decision making throughout an organization. In this session, we will explore:


  • The people, process and technology considerations in building a modern data strategy
  • Methods for driving agility across the business
  • Getting your teams into a data-first mindset


Supply Chain Analytics Track Speakers

  1. Evaluating Roadway Safety Performance: An Iterative Approach
    Peter Fortunato & David Shuey: OKI Regional Govts
  2. Leveraging Emerging Supply Chain Technologies to Drive Efficiency
    Adrian Kumar: DHL
  3. Title TBD
    Ian Smith from REDI Cincinnati     
Operations Analytics Track Speakers
  1. Prescriptive Analytics in Action - Inventory Management
    Doug Meiser and Joe Ratterman: Amend Consulting, Nick Austin: F&M Mafco
  2. Whole Hospital Modeling for Patient Flow
    Tyler French: UC Health & Denise White: University of Cincinnati
  3. Test Analytics
    Ryan Fitzpatric: GE Aviation
Marketing/Retail Analytics Track Speakers
  1. Using ML to Improve Data Quality and Drive Customer Preference
    Perry Seal & Mini Rajkumar: Kroger,  Kris Still: CoStrategix
  2. Marketing Analytics (B2B Commercial Sales)
    Branden Pauly: Meritor
  3. Building an Innovation Ecosystem
    Dan Whitacre: Kroger

Analytics Management and Leadership Track Speakers

  1. Data Centricity as the best solution to manage complexity in the digial age
    Ruben Sardaryan: Infocratic
  2. Predictive Analytics in Business context and end-to-end machine learning applications"
    Ankita Mangal: Procter and Gamble
  3. Analytics Leadership in a Time of Crisis
    Zahir Balaporia: FICO
Analytics Technology Track Speakers
  1. Predicting Trends That Matter: How to Use Social Data and AI to Develop Impactful Predictions
    Michael Howard: NicheFire & Joe Kikta: USBank
  2. AI About the Data Lakehouse
    Bill Inmon: Forest Rim Technology
  3. Beyond the Noise: Generating Recommendations with Graph Data Science
    Zach Blumenfeld, NEO4J
Post-Event Networking
  • Third Eye Brewing (across the street from the Convention Center)

Analytics Summit 2022: Selected Videos from Ruben Sardaryan and Bill Inmon

Due to travel difficulties, these speakers presented via Zoom and allowed us to share their talks.  All other presentations were live and were not recorded.  

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The Data Science Symposium 2021 was held virtually on October 12, 2021. Speakers included:

  • Paul Bessire, VP of Data at Coterie Insurance, presenting on “Data Science and the Business of Sports.”
  • Dwitiya Sawant, Senior Manager, Global Data Science, McDonald's and Mathew Zettinger, Data Scientist, McDonald's, presenting on "Understanding Delivery Order Inaccuracies."
  • Denise White,  Assistant Professor - Educator at University of Cincinnati, presenting on "Simulating Large Systems: Challenges and Approaches to the Design of a Whole Hospital Model."
Speaker Paul Bessire VP of Data Coterie Insurance

Paul Bessire, VP of Data, Coterie Insurance

Title“Data Science and the Business of Sports”

Abstract: Through various examples spanning everything sports related - from tickets, to hiring, to strategy, to gambling - learn why sports
is both the ultimate catalyst and proving ground for innovation in data science and what this means for all business.

Bio: Paul Bessire has been in predictive analytics and data science for 15+ years. He has used data and technology to become one of the world's foremost disruptors in sports analytics and is now focused on doing something similar in insurtech.
 Paul recently joined Coterie after four years in consulting where he and team help middle-market clients, nonprofits and sports teams make more efficient decisions using information and technology.


Speaker Mathew Zettinger, Data Scientist, McDonalds

Dwitiya Sawant, Senior Manager, Global Data Science, McDonald's
Mathew Zettinger, Data Scientist, McDonald's

Title: "Understanding Delivery Order Inaccuracies"

Abstract: The explosion of third-party food delivery is quickly changing the way restaurants serve their customers. But this new channel also brings challenges, as an incorrect order can leave a customer frustrated without an easy resolution. McDonald’s is turning to data and analytics to better understand why inaccurate orders happen, building tools to help identify the factors that contribute to inaccuracies, improve the accuracy of delivery orders, and enhance the customer experience. In this talk we will explore how McDonald’s uses modeling, optimization, and engineering tools to uncover insights on delivery order inaccuracies.: 

Bio: Dwitiya Sawant is Senior Data Science Manager at McDonald’s Corporation leading Data Science work in the Operations and Delivery domain. Dwitiya has worked in the field of data science for over a decade and is currently leading a team of Data Scientists and Data Engineers at McDonald’s. Through her career she has helped companies in diverse domains including CPG, Finance, Communications and Insurance solve their business problems with modern Data Science solutions. Prior to McDonald’s she worked for data science teams at Nielsen, PwC and Intrado. Dwitiya is passionate about the work she does day to day at McDonald’s and is a strong supporter of Women in Tech and Women in Leadership roles. Other than Data Science, Dwitiya is trained in Indian classical dance, loves to spend time refining her dance skills and feels blessed to be mom of a little boy.:  

BioMatt Zettinger is a Data Scientist on the Global Data and Analytics Hub at McDonald’s, where he constructs models and analyses to drive value for a variety of business units. He holds a bachelor’s degree in engineering from the University of Illinois at Urbana-Champaign. Prior to McDonald’s he spent time building credit models in the financial technology space and forecasting demand in the retail/consumer packaged goods industry.


Speaker Denise White, Assistant Professor, University of Cincinnati

Denise White, Assistant Professor-Educator, University of Cincinnati

Title: "Simulating Large Systems: Challenges and Approaches to the Design of a Whole Hospital Model"

Abstract: Hospitals differ from most systems in the complexity of operations and the unparalleled variability and uncertainty of demand.
 How do you model a system where virtually every entity has a uniquely defined path and set of needs?  Using simulation modeling, we explore how data analysis techniques, appropriate definition of stochastic and probabilistic elements, and streamlined design can be used to develop a complete model of patient flow through a large hospital.  We explore unique business challenges in managing the operations and demonstrate how to incorporate decision making based on hospital status into a simulation model.

Bio: Denise L. White, PhD, MBA, is an Assistant Professor – Educator at the University of Cincinnati where she is the Director of the Master of Science in Business Analytics and teaches courses in analytics, operations management and healthcare.  She also holds a position as an Assistant Professor- Research at the James M. Anderson Center for Health Systems Excellence at Cincinnati Children’s Hospital Medical Center. Before joining UC as a full-time faculty member, she was the Director of Quality and Transformation Analytics at Cincinnati Children’s where she was responsible for overseeing analytic staff members supporting hospital-wide improvement efforts

Media Sponsor

Analytics Summit 2021: Session 1 - April 6

KEYNOTE SPEAKER  12:05 - 12:45 PM

Rama Akkiraju
IBM Fellow

Making AI work for companies: RACE your FACTS - a methodology perspective

Abstract: There is renewed interest among companies these days to implement and deploy AI models in their business processes either to increase automation or to improve human productivity. AI models are making their way as chatbots in customer support scenarios, as doctors' assistants in hospitals, as legal research assistants in the legal domain, as marketing manager assistants in marketing, and as face detection applications in the security domain, just to name a few use cases. Making AI work for enterprises requires a whole new and different set of concerns to be addressed than those for traditional software applications or for consumer-facing AI models such as targeted advertising and product recommendations. These new concerns include robustness (R), accuracy and adaptability (A), continuous learning (C), explainability (E), fairness (F), accountability (A), consistency (C) and transparency (T). In addition, building high quality and scalable AI models requires a specific kind of discipline, methodology, and tools. Data Scientists and practitioners need prescriptive guidance, tools, methods, and best practices on how to procure data, and build, improve and manage their AI models while addressing the concerns mentioned above. In this talk, I will present our best practices for making AI work for enterprises based on our first-hand experience of building scalable AI models for enterprises.

Bio: Rama Akkiraju is an IBM Fellow, Master Inventor and IBM Academy Member at IBM’s Watson Division where she is the CTO of AI Operations, an effort to optimize information technology (IT) operations management using Artificial Intelligence (AI). Prior to this role, Rama also led the AI mission of enabling natural, personalized and compassionate conversations between computers and humans. Rama has been named by Forbes as one of the ‘Top 20 Women in AI Research’ in May 2017, has been featured in ‘A-Team in AI’ by Fortune magazine in July 2018 and named ‘Top 10 pioneering women in AI and Machine Learning’ by Enterprise Management 360 in April 2019. Rama is the also the recipient of the University of California, Berkeley’s Athena award for Technical and Executive Leadership for 2020.

In her career, Rama has worked on agent-based decision support systems, business process management, electronic market places, and semantic Web services, for which she led a World-Wide-Web (W3C) standard. Rama has co-authored 4 book chapters and over 100 technical papers. Rama has 30+ issued patents and 25+ pending. She is the recipient of 4 best paper awards in AI and Operations Research. Rama served as the President for ISSIP, a Service Science professional society for 2018 and continues to actively drive AI projects through this professional society. Rama holds a Master’s degree in Computer Science and has received a gold medal from New York University for her MBA for highest academic excellence.  

Mary Cummings
Pratt School of Engineering faculty
studio portrait

Speaker 2: 12:50 -1:30 PM

Missy Cummings
Professor in the Department of Electrical and Computer Engineering
Duke University

Future Pitfalls and Promises of Safety on Autonomous Systems

Abstract: With vehicle technology getting more sophisticated year after year, the autonomous operation of cars, trucks, and even airplanes is on the near horizon. How will this technology change the way we drive and fly? What are the potential sociotechnical impacts of this type of engineering? Dr. Missy Cummings – a former Navy fighter pilot and current expert on autonomous system collaboration from Duke University – will answer those questions and provide recommendations for the path forward.

Bio:  Professor Mary (Missy) Cummings received her B.S. in Mathematics from the US Naval Academy in 1988, her M.S. in Space Systems Engineering from the Naval Postgraduate School in 1994, and her Ph.D. in Systems Engineering from the University of Virginia in 2004. A naval pilot from 1988-1999, she was one of the U.S. Navy's first female fighter pilots. She is currently a Professor in the Duke University Electrical and Computer Engineering Department, and the Director of the Humans and Autonomy Laboratory. She is an AIAA Fellow, a member of the Defense Innovation Board and a member of the Veoneer, Inc. board.

Analytics Summit 2021: Session 2 - May 4

LCOB,Andrew Harrison, OBAIS

Technical Talk: 1:40 - 2:20 PM

Andrew Harrison
Assistant Professor
Lindner College of Business University of Cincinnati

Data Integration: The Foundation of Analytics

Abstract: In modern digital systems, data is plentiful. However, firms continue to struggle with squeezing value from that data because it is often unorganized, incomplete, or inaccurate. During this presentation, Andrew will present strategies for developing mediated schemas to untangle messy data. These data integration strategies represent best practices for incorporating data from multiple systems with differing data models (i.e., relational, dimensional, and key-value data sources) into a polyglot data system. This presentation will describe how diverse data sources can be integrated via schema alignment, record linkage, and data fusion to produce fast, flexible data structures that act as the foundation for analytical reporting.

Bio  Andrew Harrison is an Assistant Professor of Information Systems in the Lindner School of Business at the University of Cincinnati. His research interests include consumer fraud, deception, security systems, privacy, media capabilities, and virtual worlds. 

Michael Cavaretta Analytics Summit 2021 Speaker

Speaker 1: 12:05 -12:45 PM

Michael Cavaretta
Senior Manager, Manufacturing Analytics, Global Data, Insights, and Analytics
Ford Motor Company

Manufacturing Analytics at Ford Motor Company

Abstract:  Manufacturing Analytics at Ford Motor Company - In existence for over 100 years, Ford considers itself primarily a manufacturing company. But, manufacturing has changed significantly over the years. Take Industry 4.0. It is the evolution of production from mechanization, mass production, automation to the Smart Factory and is composed of new technologies like edge computing, the Industrial Internet of Things and Artificial Intelligence. Industry 4.0 promises to make remake manufacturing. This talk will touch on how Ford's investments in Industry 4.0 through a sample of use-cases.

Bio: Michael Cavaretta is an Analytics Executive at Ford, having had multiple roles in Global, Insights, Data and Analytics (GDIA). Since joining in 2015, he’s worked in connected vehicles, analytics infrastructure, customer data and manufacturing and the Industrial Internet of Things. In addition to leading analytics teams, he has managed large IT projects of $40M / year with 100+ direct reports. Before joining GDIA, he spent over 15 years applying data analytics to business problems as part of Research and Advanced Engineering. While there, he led multiple analytic projects across all areas of Ford Motor Company, including sales and marketing, warranty and quality, manufacturing, and HR, saving the company hundreds of millions of dollars. Michael received his Ph.D. in Computer Science with a focus on Artificial Intelligence and Machine Learning in 1995.  


Mandy Humbert Analytics Summit 2021 Speaker

Speaker 2: 12:50 - 1:30 PM

Mandy Humbert
Sr. Director of Engineering and Data Science

Treating Data like an Asset to improve business information flow

Abstract:  Have you ever shown up to a meeting with a set of metrics that contradict the same metrics someone else has brought?  Have you ever heard your company say that they overwrite data, or delete data after a few years or months?  Is your data poorly defined or undefined?  How do we convince Executive Management that Data is an Asset and we need to protect it as we would any other company asset?

Bio: Mandy Humbert is the Sr. Director of Engineering and Data Science at Schneider in Green Bay, WI. In her current role, she focuses on delivering visionary leadership, people engagement and development, and strategic planning. Mandy has built a COE in Data Visualization to drive a trusted source of Enterprise information for tactical and strategic decision making. She also has created and launched a Data Governance program that systemized the implementation of new processes and ensured full penetration into the data value chain. She is an accomplished leader in Analytics and Data Science with a passion for building diverse teams and partnerships. When not working, Mandy enjoys reading and spending time with her four children and two dogs.

Spencer Baucke Technical Speaker

Technical Talk: 1:40 - 2:20 PM

Spencer Baucke
Principal Consultant, Data Viz Lead – Power BI

Tableau & Power BI: Find the tool that's right for you

Abstract: Big Data was the buzz word in 2015, now Tableau v Power BI is the latest craze in BI. Certified in both, Spencer walks through his take on deploying both at enterprise and some tips on choosing which tool is right for you and your organization.  

Bio:  Spencer is passionate about enabling organizations to leverage their data through data visualization, most notably Power BI and Tableau. Spencer is a former Tableau Public Featured Author, 14x Tableau Pubic Viz of the Day winner, and co-founder of the Tableau community initiative #SportsVizSunday. Spencer has also been a speaker at TC18 in New Orleans, TCE19 in Berlin, and TC19 in Las Vegas. In addition to Tableau, Spencer enjoys leveraging data and analytics in Power BI. Spencer is DA-100 exam certified, co-founder of #WorkoutWednesday Power BI, and has enabled organizations to develop, share, and utilize Power BI reports across their enterprise.

Analytics Summit 2021: Session 3 - June 8

Cynthia Rudin Analytics Summit 2021 Speaker

Speaker 1: 12:05 -12:45 PM

Cynthia Rudin
Professor of Computer Science
Duke University

Why use Interpretable Machine Learning? Because Predicting Manhole Fires and Brain Seizures is More Difficult Without It

Abstract: With widespread use of machine learning, there have been serious societal consequences from using black box models for high-stakes decisions, including flawed bail and parole decisions in criminal justice. Explanations for black box models are not reliable, and can be misleading. If we use interpretable machine learning models, they come with their own explanations, which are faithful to what the model actually computes. In this talk, I will introduce interpretable machine learning, and discuss several important applications to energy grid reliability, healthcare, and criminal justice.

Bio: Cynthia Rudin is a professor of computer science, electrical and computer engineering, and statistical science at Duke University, and directs the Prediction Analysis Lab, whose main focus is in interpretable machine learning. She is also an associate director of the Statistical and Applied Mathematical Sciences Institute (SAMSI). Previously, Prof. Rudin held positions at MIT, Columbia, and NYU. She holds an undergraduate degree from the University at Buffalo, and a PhD from Princeton University. She is a three-time winner of the INFORMS Innovative Applications in Analytics Award, was named as one of the "Top 40 Under 40" by Poets and Quants in 2015, and was named by as one of the 12 most impressive professors at MIT in 2015. She is past chair of both the INFORMS Data Mining Section and the Statistical Learning and Data Science section of the American Statistical Association. She has also served on committees for DARPA, the National Institute of Justice, and AAAI. She has served on three committees for the National Academies of Sciences, Engineering and Medicine, including the Committee on Applied and Theoretical Statistics, the Committee on Law and Justice, and the Committee on Analytic Research Foundations for the Next-Generation Electric Grid. She is a fellow of the American Statistical Association and a fellow of the Institute of Mathematical Statistics. She is a Thomas Langford Lecturer at Duke University during the 2019-2020 academic year.

Alexander Antony Speaker

Speaker 2: 12:50 - 1:30 PM

Alexander Antony
Sr. Data Scientist
GE Aviation

Forecasting the Aviation Market Recovery

Abstract: COVID-19 has had a significant impact on many industries, but few have been as heavily disrupted as commercial aviation. When combined with government travel restrictions, the spread of the disease has led to a historic decline in air travel around the world. This talk will discuss how advanced forecasting methods, such as Bayesian Structural Time Series models, can be leveraged to shed light on the aviation market recovery in the aftermath of COVID-19.

Bio: Alex Antony is a Senior Data Scientist at GE Aviation in Cincinnati, OH. Prior to joining GE, Alex worked as a data scientist on Wright-Patterson Air Force Base and as a statistical consultant. Alex holds both a MS in Applied Statistics and a PhD in Political Science with a focus on Quantitative Methodology from Indiana University.

Bradley Boehmke headshot

Technical Talk: 1:40 - 2:20 PM

Brad Boehmke
Director of Data Science

Scaling Productivity with an Inner Source Ecosystem

Abstract:  The open source ecosystem provides many resources that most organizations leverage and benefit from. The beauty of this ecosystem is that many packages and tools exist to make you more effective and efficient; plus, you have the opportunity to contribute back to the source code. At 84.51° we have started to create our own inner source ecosystem of internal packages and tools to help make our 250+ data scientists more productive. This talk will discuss how we did it, the benefits and challenges, along with providing tips that you can take back to your organization to start building similar capabilities.

Bio: Brad Boehmke, PhD, is the Director of Data Science at 84.51°, Professor at three universities, author of the Data Wrangling and Hands-On Machine Learning with R books, and creator of multiple R open source packages and data science short courses. Brad's team focuses on developing algorithmic processes, solutions, and tools that enable 84.51° and its analysts to efficiently extract insights from data and provide solution alternatives to decision-makers. He has a wide analytic skill set covering descriptive, predictive, and prescriptive analytic capabilities applied across multiple domains including retail, healthcare, cyber intelligence, finance, Department of Defense, and aerospace. Summary of his works is available online at

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Data Science Symposium 2020 Virtual Event Speakers

Jason Pontin: Keynote Speaker Data Science Symposium 2020

Jason Pontin, Keynote Speaker, Data Science Symposium 2020.

Jason Pontin: Contributing Writer To Wired And Senior Advisor At Flagship Pioneering

"Future Impacts of Technology"

Abstract: Jason Pontin will provide a lively tour of the future of data science, including emerging techniques in machine learning and quantum computing, and the revolution they are driving in healthcare, energy, and other fields. Along the way, he'll discuss the opportunities and challenges for any organization that seeks to harness the revolution in data science—revealing his experiences in investing and creating companies that directly use data science to solve big problems and create extraordinary value for shareholders and society.

Jason Pontin is a Senior Advisor at venture capital firm Flagship Pioneering, which conceives, creates, resources and grows first-in-category life sciences companies. He is also an expert on innovation, and a renowned journalist. Jason addresses audiences around the world with speech topics on both how we can all think like a futurist, as well as the future of work, encompassing AI, Robotics and Big Data. He has a regular column at WIRED magazine on disruptive technologies. Formerly, he was editor and publisher of the MIT Technology Review, where he was responsible for the publication’s editorial direction, media platforms and business strategy.

Data Science Symposium 2020 Keynote Speaker Marshall Fisher

Marshall Fisher: UPS Professor, The Wharton School

"Sell what you’ve made vs. make what’s selling, Where is the world headed?"

Abstract: Footwear and apparel retailers can choose three paths: 1) get fast, so they can make what’s selling (as exemplified by Zara), 2) develop accurate forecasts so they can produce in advance to the sales quantities well matched to demand, or 3) live with the excess inventory and markdowns that result from long lead times and inaccurate forecasts. We compare these approaches and describe a forecasting method that leverages social media to enhance preseason forecast accuracy for footwear and apparel.

Marshall Fisher is the UPS Professor of Operations, Information and Decisions at the Wharton School of the University of Pennsylvania and co-director of the Fishman-Davidson Center for Service and Operations Management.  He holds an SB degree in electrical engineering, an MBA, and a PhD in operations research, all from MIT. Dr. Fisher joined the faculty of the Wharton School in 1975. Prior to that he was a systems engineer in the Boston Manufacturing and Distribution Sales office of IBM and on the faculty of the University of Chicago Graduate School of Business.

Dr. Fisher’s research during his 35-year career has focused on supply chain management, with a varying emphasis that has included private truck fleet scheduling, supply chain management for hard to predict fashion products and a scientific approach to retailing. Dr. Fisher has been a consultant to many Fortune 500 companies, including Advance Auto Parts, Air Products and Chemicals, Albert Heijn, Bertelsmann Music Group, Bulgari, Campbell Soup, Dupont, Experticity, Exxon, Frito Lay, General Motors, IBM, Jo-Ann Fabric and Craft Stores, Kronos, Lutron, Motorola, Nike, Nokia, Scott Paper, Spencer Gifts and Spiegel, Inc., to name a few.

Radhika Kulkarni Data Science Symposium 2020 Keynote Speaker

Radhika Kulkarni, PhD: VP (Retired), Advanced Analytics R&D, SAS Institute, Inc.

"Building Analytics Teams for Success: A Perspective from Two Sides"

Abstract: You have chosen a career in Data Science, Analytics and Operations Research: Do you wonder if algorithmic innovation is enough to succeed? As you advance in your career and assume leadership positions in Analytics, what are the lessons you need to build and grow a successful team? In this talk, you can hear some of the experiences from both perspectives: Lessons learned as a young professional and also as a leader of a large Analytics R&D organization.

Radhika Kulkarni retired as VP, Advanced Analytics R&D at SAS Institute Inc. where she was responsible for the world’s leading Analytics Software products portfolio. She holds a Ph.D. in Operations Research from Cornell University. Under her leadership, OR gained recognition as a key contributor to scalability and performance of algorithms in statistics, machine learning, forecasting, data mining, econometrics, etc. She serves on many academic advisory boards. Kulkarni is an INFORMS Fellow and WORMS Award winner.

Jude Schramm, Keynote Speaker. Data Science Symposium 2020

Jude Schramm, Keynote Speaker, Data Science Symposium 2020.

Jude A Schramm: Exec VP/CIO/Head:Information Technology, Fifth Third Bancorp

"Adopting Data and Analytics into the Fiber of a Company"

Abstract: Data science and analytics technologies, skills, and jobs are rapidly growing. The proliferation of enterprise data offices, advanced technologies in data science and analytics, and a generation of digital first workers are enabling a new way of working led by data driven decisions. What are some key areas of focus and interest companies should consider as they continue the journey?

Jude Schramm serves as Chief Information Officer. He leads teams that provide innovative solutions in support of the Bank’s strategy, including information technology, Agile software development, infrastructure and cloud solutions, information security and enterprise data management.

Before joining the Bank, Jude served as Chief Information Officer for GE Aviation, where he was responsible for leading IT strategy and digital transformation. In previous roles there, he led IT organizations for the services, digital industrial and commercial divisions. He also led digital and enterprise data transformation for the GE IT Corp. He began his career at GE in 2001 as a developer and had roles of increasing responsibilities over his 17 year career. Jude began his career as a senior consultant with Ernst & Young LLP and also worked as a project manager with Whittman-Hart.

Matt Brems: Managing Partner, Distinguished Faculty at General Assembly, Betavector,

"Good, Fast, Cheap: Doing Data Science with Missing Data"

Abstract: If you've never heard of the "good, fast, cheap" dilemma, it goes something like this: You can have something good and fast, but it won't be cheap. You can have something good and cheap, but it won't be fast. You can have something fast and cheap, but it won't be good. In short, you can pick two of the three but you can't have all three. If you've done a data science problem before, I can all but guarantee that you've run into missing data. How do we handle it? Well, we can avoid, ignore, or try to account for missing data. The problem is, none of these strategies are good, fast, *and* cheap. We'll walk through practical tips for working with missing data and recommendations for integrating it with your workflow that allow you to make better, more informed decisions when doing data science with missing data.

  • Matt Brems is currently Managing Partner and Principal Data Scientist at BetaVector. His full-time professional data work spans finance, education, consumer-packaged goods, and politics and he earned General Assembly's 2019 "Distinguished Faculty Member of the Year" award. Matt earned his Master's degree in statistics from Ohio State. Matt is passionate about responsibly putting the power of machine learning into the hands of as many people as possible and mentoring folx in data and tech careers. Matt also volunteers with Statistics Without Borders.


Pavan Chundi: Senior Analyst, Cincinnati Children's Hospital

"Improving Patient Family Experience: A Machine Learning Approach"

Abstract:  Effective communication has always been a great intervention to improve patient family experience. Being able to accurately predict clinic visit length (including wait time) and making this part of the communication can improve overall experience. Explore this opportunity on how we make use of machine learning model to predict visit lengths by incorporating a range of variables like date, time, schedule, patient flow and others.

  • Pavan K Chundi is a Senior Analyst at the James M Anderson Center for Health System Excellence, Cincinnati Children’s Hospital Medical Center. He graduated from University of Cincinnati with a Master’s degree in Business Analytics and holds a Master’s degree in Biomedical Engineering from University of Surrey, UK. His areas of specialization are Healthcare Analytics, Healthcare Outcomes and Improvement, Data Visualization and Business Intelligence. He has been instrumental in the development of the analytical framework and interactive dashboards that have helped clinical divisions to provide patient centered care. His expertise on time series modeling is evident from his recent publication in JAMA Pediatrics.

James Lee, PhD: Associate Vice Provost for Digital Scholarship and Associate Dean of Libraries,
Lindsay Nickels, PhD:  Program Coordinator, Digital Scholarship Center, University of Cincinnati

"Sentiment Analysis 2.0"

Abstract: In this talk, we will present our "Sentiment Analysis 2.0" project, which combines deep learning with linguistics expertise to define human behavior and meaning encoded in text of different forms - social media, articles, electronic health records - in n-dimensions determined by the language actually being used. We have developed our methods as a way to avoid assumptions or overly-narrow rules of positive or negative sentiment that we could be applied to the data. This approach allows the full complexity of the language data to be revealed.

  • James Lee, PhD is the Associate Vice Provost for Digital Scholarship and Associate Dean of Libraries at the University of Cincinnati, where he also serves as the Director of the Digital Scholarship Center and is an Associate Professor of Digital Humanities. His research and teaching are in the areas of digital humanities, machine learning and text mining techniques on historical archives, social network analysis and data visualization. He works largely in early modern literature and culture. More recently, his research has branched out into fascinating collaborations applying digital humanities methods with partners in biomedical informatics, corpus linguistics, and law.
    He received his PhD at the University of California, Berkeley. His research has been supported by the Andrew W. Mellon Foundation and the National Endowment for the Humanities. He is a PI of the Catalyst Model for Transdisciplinary Teams in Digital Scholarship project, supported by the Andrew W. Mellon Foundation.
  • Lindsay Nickels, PhD is the Program Coordinator for the Digital Scholarship Center at the University of Cincinnati and works with transdisciplinary research teams to develop and execute innovative methodologies on large unstructured text datasets. Her research is situated in critical discourse studies and corpus approaches to discourse analysis.

Dan Shah SEI, Senior Consultant,  Rob Dodd 84.51, Digital Customer Insights, Reid McCreary 84.51, Digital Customer Insights

"Understanding and Improving Kroger Customer Experience During COVID"

Abstract: To say COVID-19 impacted the way customers shop and the supply chains that deliver food to shelves is an understatement. Kroger Pickup and Home Delivery saw an unprecedented increase in demand which required improved data visibility and insight to customer behavior. Rob, Reid and Dan will talk about how 84.51’s Customer Insights and Kroger’s Digital Business Intelligence responded to this dynamic – specifically, through adopting a new approach to measuring causality and by modeling customer behavior to understand what’s important.

  • Dan Shah is a Senior Consultant at Systems Evolution Consulting (SEI) where he helps companies convert data into insights. Before joining SEI, he worked at Procter & Gamble as a data scientist. He's an alum of UC’s MS Business Analytics Program.
  • Rob Dodd partners with Kroger and 84.51° Product Management, Data Science, and Market Research teams to deliver actionable customer insights to improve Kroger’s digital customer experience and lower the cost to serve. He formerly was a data scientist with 84.51° and Asset Manager with Ergo Investment Partners. He earned a M.S. in Predictive Analytics from Northwestern University and a B.S. in Computer Information Systems and Operations Management from Indiana University.
  • Reid McCreary is a consultant with 84.51°, with a focus on customer strategies and activations within Kroger’s ecommerce fulfillment space. Reid has 10 years of data analytics experience with 84.51° and dunnhumbyUSA. He earned a M.S. in Enterprise Integration and a B.S. in Management Information Systems, both from the University of Alabama.

Yangsu Chen: Amazon Web Services, Data Scientist

"Leveraging Forecasting Power of Classic Time Series Models and Deep Learning"

Abstract: Time series forecasting has always been an essential topic with many applications in the industry. Businesses can look backward to find trends and patterns in the historical data, but even more important is the ability to make accurate forecasts of business demands in the future. Combining historical patterns and future trends can provide a holistic story for business to make forward-looking strategies and actionable insights. In this talk, I will summarize several industry-standard time series forecasting techniques from classic models (e.g. Seasonal Naïve, ARIMA)), non-linear model (e.g. Prophet), to deep learning models (e.g. LSTM) and provide an overview of practical use cases.  

  • Yangsu Chen is a data scientist at Amazon Web Services (AWS). Before joining AWS, he was a data scientist at and a national leading non-profit organization. His work ranges from building machine learning models, time series/deep learning forecasting, market segmentation, causal experimental design, and inferential statistics. He holds his PhD from University of Nevada Las Vegas and MS from Purdue University. Before joining Amazon, he served as an adjunct professor at the University of Nevada Las Vegas.


"Future Impacts of Data Science"

  • Jason Pontin: Moderator
  • Jude Schramm: Fifth Third Bank, Executive Vice President, Chief Information Officer
  • Craig Brabec:  McDonald's, VP/Chief Data Analytics Officer.
    Bio: As McDonald’s Chief Data Officer, Craig is helping to define and infuse data across the global enterprise.  He is creating the roadmap to identify the team, technology, process and culture change required for enabling enterprise data transformation, establishing best-in-class data strategy and governance and evangelizing these changes throughout McDonald’s.
    Most recently, Craig was the Director, Global Data Insights & Analytics within Ford Motor Company.  In this role, Craig provided the executive office, product development, manufacturing, global supply chain, finance, human resources and business units with data insights to enable better decision making for the enterprise.  Craig has more than 25 years of experience working in corporate strategy and data analytics as well as manufacturing, construction, IT, supply chain and management consulting.   He has a proven track record of driving value creation, growth and business performance.  Prior to Ford, Craig was the first Senior Vice President, Data Analytics at McKesson Corporation, leading analytics for the Fortune 5 company worldwide.
  • Carlos Amesquita: CEA Advisory, Founder & President, Former CIO, The Hershey Company
    Bio: Carlos' areas of expertise are IT and Shared Services Leadership and Strategy, Strategic Partnership Models, and Digital Transformation Strategies that weave Consumer Engagement and Marketing, with Supply Chain, Digital Commerce, and Retail Execution via a strong Analytics backbone. He is a business driven and results-oriented IT and Shared Services executive with extensive experience at the intersection of business and technology in Fortune 500 companies. . As Hershey's CIO, Carlos led one of the broadest digital programs in the industry, including a comprehensive organization transformation required to deliver and sustain its digitization plan. Before joining Hershey, Carlos spent 28 years at Procter & Gamble, in a broad and diverse set of roles across several countries. He was CIO and Shared Services Leader for North America in 2011, Global Household Care CIO in 2009, and Global Food & Beverage CIO in 2000. He was P&G Latin America CIO in the late 1990's. Carlos also led P&G's IT Innovation from 2005 to 2009.

Jaime Windeler: Associate Professor of Information Systems, Lindner College of Business

"Data Science Teams: Fundamentals and Future of Virtual Collaboration"

Video Not Available

Abstract: COVID-19 has pushed many data science teams to completely remote work. Some teams are getting a crash course in grappling with longstanding challenges of virtual teamwork: isolation, relationship management, and diffusion of responsibility. Other teams have been collaborating virtually for many years. These teams have figured out how to be productive and engaged but face new challenges now that everyone else is now virtual. To address this spectrum of virtual team experiences, I will share best practices and discuss the future of virtual teamwork.

  • Jaime Windeler is an Associate Professor of Information Systems at the University of Cincinnati. Her research is published in premier IS journals and focuses on the management of distributed collaboration, as well as the attraction, motivation, and retention of IT professionals. She collaborates with several F500 companies on enhancing virtual team leadership and their IT workforce diversity and inclusion.

Ryan Kaplan: Director Data and Analytics, Kamal Raad: Lead Data Engineer, Marketing Analytics,  Fifth Third Bank

"Data DevOps in the Financial Sector?"

Video Not Available

Abstract: Data DevOps in the Financial Sector - Is that even possible?  Join Ryan Kaplan and Kamal Raad as they walk through Fifth Third Bank's journey of Data DevOps in the Enterprise Data Office (EDO) to drive customer outcomes.

  • Ryan Kaplan is a Director of Data & Analytics in the Enterprise Data Office (EDO) at Fifth Third Bank. He leads software engineers within the EDO, is responsible for delivering platforms like Kafka, and supports cloud data movement. Ryan is a proud UC alumni, having earned a Master’s degree of Science in Information Technology.
  • Kamal Raad is a Lindner alum and Data Engineer at Fifth Third Bank in the Marketing Analytics space.  His agile team is focused on providing a 360 degree view of the bank's customers, as well as supporting Marketing campaigns and customer relationship outcomes. They collaborate with the Marketing, Sales, and Retail organizations of the bank.


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Virtual Analytics Summit Webinar 3: "Visualizing Unexpected Events" was held on June 29

This event featured 4 Tableau Zen Masters;

  • Steve Wexler,  Tableau Zen Master, Data Revelations
  • Chantilly Juggernauth, Tableau Zen Master, Lovelytics
  • Jeffrey Shaffer, Tableau Zen Master, Unifund and University of Cincinnati
  • plus one other

Session 1: “Why Trust and Integrity in Data Visualization is Critical”
Steve Wexler, Tableau Zen Master

Abstract: Government has asked all of us to sacrifice for the greater good. How long will you continue to do this? In less than a year’s time you may be asked to take a vaccine. Will you take it? These are big asks and big decisions, and we crave trusted, reliable information to make these decisions. In this session we’ll look at how some governments and organizations are engendering confidence and trust, and which have done the opposite. We’ll also discuss critical thinking around data and what you must do, always, to make sure your stakeholders trust what you have to tell them.

Bio:  Steve Wexler is the founder of Data Revelations and co-author of The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios Steve has worked with ADP, Gallup, Johnson & Johnson, Deloitte, ExxonMobil, Convergys, Consumer Reports, The Economist, ConEd, D&B, Marist, Cornell University, Stanford University, Tradeweb, Tiffany, McKinsey & Company, and many other organizations to help them understand and visualize their data. Steve is a five-time Tableau Zen Master, Iron Viz Champion, and on the advisory board to the Data Visualization Society.

Session 2: "COVID-19: Visualizations for Workforce Planning".
Chantilly Jaggernauth, Vice President Data Visualization and Training, Lovelytics

Abstract:  Organizations across the United States are continuing to grasp the full impact of the COVID-19 pandemic. Employers small and large are asking: is our workforce at risk, how can we protect our employees, and what are safety measures that need to be in place in order to return to work? To help answer these questions, Chantilly Jaggernauth and the Lovelytics Data Visualization team developed several COVID-19 Workforce Analytics visualizations to provide organizations with a baseline in analyzing their workforce data. During this session, Chantilly will walk through these visualizations and discuss how they can assist in the development of strategies around employee safety for organizations.

Bio: Chantilly Jaggernauth's mission is to empower corporations and individuals through the use of data visualizations and data analytics. She is a two year Tableau Zen Master who specializes in data visualization, data analytics, design, and training. Currently, she is the Vice President of Data Visualization and Training at Lovelytics based in Arlington, VA. Prior to joining Lovelytics, Chantilly worked for Johnson and Johnson and Comcast. In addition to her day job, Chantilly is the founder and CEO of the non-profit organization Millennials and Data (#MAD). Through #MAD, she works to bridge the data literacy and analytical skills gap by training, mentoring, and preparing millennials to enter a data- driven global environment.

Session 3: "Turning Your Skill Into a Social Force"
 Tableau Zen Master

(We do not have permission to share this video)

Abstract:During this uncertain time, many of us are asking ourselves: "what can we do for the world?" In this session, we will share how you can leverage your visualization skill along with design thinking to make a positive impact on society. We will dive into the journey of Viz for Social Good as an example, a social nonprofit that empowers mission-driven organizations to harness the power of data visualization for social change.  


"Visualizing Unexpected Events" Panel Discussion

The three event speakers, Steve Wexler,  Chantilly Jaggernauth and one other Tableau Zen Master, were joined for the panel discussion by moderator Jeffrey Shaffer .

Bio: Jeffrey Shaffer, Tableau Zen Master, is an expert in applying data visualization to create insights and competitive advantage. Mr. Shaffer is an Adjunct Professor at the University of Cincinnati in the Carl H. Lindner College of Business where he teaches Data Visualization in the graduate course series for Data Analytics. He is a regular speaker at conferences, symposiums, universities and corporate training programs on the topic of data visualization, he writes for the data visualization blog at Data + Science and he was a finalist in the 2011 Tableau Interactive Visualization Competition. Mr. Shaffer also teaches data visualization at the KPMG Advisory University. Mr. Shaffer is Vice President of Information Technology and Analytics at Unifund.

This year due to the pandemic the Analytics Summit 2020 was delivered as a virtual event over three sessions on June 1, 15, and 29.  Videos of the speaker presentations (that we have permission to share) are available below.

Virtual Analytics Summit Webinar 2: "Decision Making Under Covid-19: Planning and Recovery"

Session 1: "Covid-19 Scratch Models to Support Local Decisions"
Edward H. Kaplan
, William N. and Marie A. Beach Professor of Operations Research, Professor of Public Health, Professor of Engineering, Yale School of Management, Yale University.

Abstract: I was appointed to Yale University’s COVID-19 advisory committee to provide analyses supporting university decisions during the early weeks of the SARS-CoV-2 outbreak. This work expanded in response to requests from the Yale New Haven Hospital and the State of Connecticut for help. Much of this work relied on scratch modeling, that is, models created from scratch in real time. Applications to date include determining crowd-size restrictions on events, hospital surge planning, university shutdown and restart timing decisions, designing viral testing programs, and environmental monitoring by testing sludge from the local wastewater treatment plant. I will describe the problems faced, types of models developed, and advice offered during real-time response to the COVID-19 crisis at the local level.

Session 2: "How To Prepare For Ramping Up? Riding The Covid Wave in the Next Six Months"
(We do not have permission to publish this video)
Jan C. Fransoo, Professor of Operations Management and Logistics, Kuehne Logistics University
Abstract: Extending our successful dynamic models that we deployed 11 years ago during the credit crisis, we model the production and market lockdowns caused by the Covid-19 crisis. We estimate the supply chain dynamics that we may see unfold over the next few months. Our results show that inventory dynamics may be very large, caused by dramatic drops in demand. Regardless of how the market recovery will evolve, we demonstrate the criticality of monitoring cumulative supply chain inventory and market demand. For companies upstream in the supply chain, the impact of the inventory evolution is much stronger than the exact details of the market recovery.
Panel Discussion: "Interpreting Predictive Models Related to Covid-19"
Three experts discuss the challenges related to interpreting predictive models subject to extreme uncertainty. All analytical models are subject to the limitations of existing data and underlying assumptions. Models related to COVID-19 are especially challenging to interpret due to the lack of historical data and the inherent uncertainty of human behavior during these unprecedented times. Learn from experts on how best to communicate model results and insights to decision makers when models are subject to high degrees of uncertainty.


Stephan Chase, Founder, Chase Intel
BIO:  Stephan has over three decades of experience in applied predictive modeling, consumer research, business intelligence, and other forms of analytics. His insights have been used to craft corporate strategy and to create well over a billion dollars incremental revenue. He serves on the executive Board of NC State’s Institute for Advanced Analytics and is an emeritus member of the INFORMS Roundtable and the executive board of the Advertising Research Foundation.

Jan C Fransoo, Professor of Operations Management and Logistics, Kuehne Logistics University
BIO: Jan C. Fransoo is Professor of Operations Management & Logistics at Kuehne Logistics University in Hamburg, Germany. Professor Fransoo’s research studies operations, logistics, and supply chain management decision making in the retail, chemical, food, pharmaceutical and transport industries. His current research focuses in particular on retail distribution and channel management in developing markets, on intermodal container transport, and on sustainability and social responsibility in supply chains. . Fransoo holds a Master of Science degree in Industrial Engineering and a Doctor of Philosophy degree in Operations Management and Logistics, both from Eindhoven University of Technology.

Edward H Kaplan, William N. and Marie A. Beach Professor of Operations Research, Professor of Public Health, Professor of Engineering, Yale School of Management, Yale University
BIO: Edward H. Kaplan is the William N. and Marie A. Beach Professor of Operations Research, Public Health, and Engineering at Yale University’s School of Management. An expert in operations research, mathematical modeling and statistics, Kaplan was elected to the National Academy of Engineering and the Institute of Medicine (now the National Academy of Medicine). His research in HIV prevention and counterterrorism has been recognized with the Edelman Award, Lanchester Prize, Centers for Disease Control’s Charles C. Shepard Science Award, INFORMS President’s Award, three Koopman Prizes, and numerous other awards.

This year due to the pandemic the Analytics Summit 2020 was delivered as a virtual event over three sessions on June 1, 15, and 29.  Videos of the speaker presentations are available below.

Virtual Analytics Summit Webinar 1: "Analytics Leadership in Uncertain Times" Presented on June 1, 2020

This webinar included two keynote speakers and a panel discussion.

Session 1: "When a Data Geek Speaks"
Alex Gutman, Lead Data Scientist, 84.51

Abstract: Within many companies, there’s a communication barrier between decision makers and data scientists. As a result, business professionals, managers, and executives often find themselves making decisions based on data and analytic methods they do not fully understand. This talk addresses this communication barrier and aims to help business professionals become better consumers of analytics. By becoming more informed on the technical aspects and challenges your data scientists face, you’ll be able to ask smarter questions, form better opinions, and make better decisions about the analytics you encounter in the workplace.

Session 2: "intelligent Disruption of the Global Food Chain"
Jarrod Anderson, Emerging Technology Lead, ADM

Abstract: This talk explores disruption as a convergence of technologies that are coming together to unlock new possibilities within the global food and agriculture system. Technological disruption implies systems change, rather than simple product substitution. As with any industry transformation, feedback loops hold back the new in favor of the old. Once certain tipping points have been reached, however, such loops begin to favor the new over the old. The use of data science and artificial intelligence in the support of these changes are key in helping to feed the world.

Panel Discussion - June 1, 2020

Four seasoned leaders of analytics in the CPG, Retail, and Food industries discussed how they empowered their organizations to solve real-time problems related to the COVID-19 pandemic.  Learn how agility counts when faced with significant disruption and how inspirational leadership matters.  The panelists will address such topics as: How did the pandemic change how your organization's work is done on a day-to-day basis? Has your leadership style changed as a result of this?  What lessons have you learned thus far and how will this affect how your organization works in the future?

Mike Cramer: Director, Operations Advanced Analytics, McDonald's Corporation
Bio: Mike has over 35 years of experience in engineering & applied sciences across a diverse portfolio of industries, eventually gravitating to food related  industries.  Mike’s experience has crossed over many functions, including supply chain, manufacturing, operations, insights, innovation and franchising.  Mike joined McDonald’s Innovation and Global Solutions Group 15 years ago, charged with creating McDonald’s first ever Operations Research department focused on creating the Restaurant of the Future.  Moving on from there, Mike has lead teams to apply advanced sciences in the US business with supports over 14,000 restaurants serving over 16 million customers each day.

J. David Dittmann: Director, Data & Analytics, The Procter & Gamble Company
Bio: With more than 20 years of experience, David Dittmann holds worldwide responsibility for Business Analytics Services, Product Supply Data Science, and the Data & Analytics IT Development & Operations organization including Data Engineering.  David’s organizations have been recognized with numerous industry awards and he is a frequent industry speaker who is passionate about using data & analytics to make unconventional connections across all aspects of business.  In 2018, he was recognized as an “Analytics Visionary” by Consumer Goods Technology. David holds a Bachelor of Science in Industrial & Systems Engineering and a Master of Science in Operations Research & Engineering Management both from The Ohio State University.

Alex Gutman: Lead Data Scientist, 84.51
Bio: Alex Gutman, PhD, is a Lead Data Scientist at 84.51°, Accredited Professional Statistician®, Adjunct Professor at the Air Force Institute of Technology, and Fulbright Specialist with expertise in statistical & machine learning. He enjoys teaching a wide variety of data science topics to both technical and non-technical audiences.

Jarrod Anderson: Emerging Technology Lead, ADM
Bio: Jarrod Anderson joined ADM in August of 2019 in the newly created role of Emerging Technology Lead moving his family from Seattle, Washington to Erlanger, Kentucky. He is responsible for building a data science team and developing artificial intelligence solutions to address ADM’s most complex challenges. Before joining ADM, Jarrod worked at Wells Fargo as VP of Artificial Intelligence and has held multiple technology and innovation roles at IBM Watson working on Artificial Intelligence, IoT and Blockchain technology.


The Data Science Symposium 2019 was held at the new Lindner College of Business on October 10 & 11, 2019.  The event featured 3 keynote speakers and 16 technology talks on current data cience methods and tools.

Keynote Speakers included

  • Kevin Werbach: Professor of Legal Studies and Business Ethics Wharton School University of Pennsylvania:  "Big Data, Big Responsibilities"
  • Terry McFadden: Principal, Datascente: "40 years of Data & Analytics Evolution  - Distilled Knowledge for 2020 and Beyond"
  • Udo Sglavo: Division Head & Vice President of Analytics, SAS;  "SAS Ex Machina Doctrina"

Keynote Speakers

Zeynep Tufekci:  Techno-sociologist and an internationally recognized authority on the social and moral implications of how we use big data and algorithms to make decisions.

Anne Robinson: Chief Strategy Officer, Kinaxis: "Analytics in Action - from Concept to Value"

Todd Wickerham: Special Agent in Charge, Cincinnati Field Office, Federal Bureau of Investigation: "Securing Big Data: The FBI's Perspective"


Confirmed two-day training sessions and instructors include: 

  • Machine Learning with R featuring Brad Boehmke and Brandon Greenwell
  • Intermediate and Advanced Tableau a new Tableau training class with Jeffrey Shaffer
  • Big Data: Hadoop and Spark with Andrew Harrison and Jay Shan
  • Advanced Power BI, with Derek Sasthav and Geoff Marsh, that will take experienced Power BI users to the next level.
  • Analytics for Leaders with Glenn Wegryn (1/2 day session April 2 1200-5:00PM)

Track Sessions

The five track sessions and presenting companies will include

  1. Financial/Risk Management Analytics: FICO, Synchrony/Fidelity, American Modern Insurance Group
  2. Marketing Analytics: 84.51, PNC Bank, Infotrust
  3. Operational Analytics: WakeForest University, Evalueserve, National Weather Center
  4. Analytics Management and Leadership; Cincinnati Children's, Boeing, Domo
  5. Analytics Tools: SAS, KNIME, ICC

The Data Science Symposium will showcase presentations from thought-leaders in data science. Each presenter will discuss technical use cases. The event will also include opportunities for networking with other leading analytics professionals and graduate students in the Business Analytics and Information Systems programs. Attendees will receive continental breakfast, box lunch, and free parking.

Keynote speakers

John Bossert, Senior Data Scientist at Google, will address "Two Problems in Demand Planning for Compute Resources at Google."

Michael L Thompson, Research Fellow from P&G, will follow with "Bayesian Sense Making in Data Science."

Joe Blue, Director of Global Data Science at MAPR, will finish the keynotes with "Zen and the Art of Model Maintenance."Replace with your text

The 2018 Analytics Summit consisted of inspiring keynote speakers, four two-day and one-half day training sessions, and five all-day track sessions.

Keynote speakers included Cameron Davies, Senior Vice President Analytics and Strategy, NBC Universal; Bill Franks, Chief Analytics Officer, International Institute for Analytics; and Craig Brabec, Director, Global Insights and Analytics, Ford Motor Company.

Training sessions had the following topics and presenters:

  • Data Mining: John Elder, data mining expert and author
  • Tableau Training: Jeff Shaffer, Tableau Zen Master
  • Machine Learning with R: Brad Boehmke and Brandon Greenwell, R book authors
  • Big Data with Hadoop and Spark: Andrew Harrison and Jay Shan, professors and big data researchers
  • Analytics for Leaders: Glenn Wegryn, experienced analytics organization leader, Executive Director of UC Center for Business Analytics

Finally, the al-day track sessions covered Data Visualization, Sports Analytics, Advanced Analytics, Big Data/Analytics Case Studies, and Analytics Management and Leadership. Top speakers from companies such as the Cincinnati Reds, Elder Research, DHL, Cincinnati Children’s Hospital, Verizon, P&G, Amazon, University of Cincinnati, Amend Consulting, Unifund, and more.

Keynote speakers

Machine Learning Day featured keynote addresses from Mohammad Taghi Saffar, Machine Learning Engineer, Google; Doug Meiser, General Manager of R&D Operations Research, Kroger; and Jeff Dandridge, VP Product Marketing, FICO.

Keynote speakers

The 2017 Data Science Symposium featured keynote addresses from Joe Blue, Director of Data Science, MapR; Mark Wolff, PhD, Advisory Industry Consultant and Chief Health Analytics Strategist, Health and Life Sciences Global Practice, SAS Institute; and Joe Porter, Chief Analytics Officer, Flywheel Digital.

Keynote speakers

Brian Christian, co-author, Algorithms to Live By: The Computer Science of Human Decisions; Neil Hornsby, Pro Football Focus; and Stephan Chase, Chase Intel.

Keynote speakers

Jordan Goldmeier: Data Science Manager,; Eric Duell, Vice President, Analytics and Intelligence, The E.W. Scripps Company; Daniel Gerard, Operational Director of the UC Institute of Crime Science in the School of Criminal Justice and Murat Ozer, Research Director, UC Institute of Crime Science.

Keynote speakers

Andrew Harrison, Assistant Professor Operations Business Analytics and Information Systems, Lindner College of Business
Big Data Integration and Fraud Detection

Abstract: Fraud costs consumers and firms billions of dollars annually, and the problem is getting worse. The “Internet of Things” has expanded vulnerabilities and social networks provide a wealth of personal data that fraudsters covet. Big data solutions offer promising new avenues to fight fraud, but major hurdles persist: constraints upon completeness, accuracy, timing, and security make it difficult to get the information needed to detect fraudulent transactions as they occur. During this presentation, Andrew will discuss big data integration strategies that offer solutions to overcome these problems, and will provide examples of how firms are currently using big data integration practices to fight fraud.

Bio: Andrew Harrison is an Assistant Professor of Information Systems in the Lindner School of Business at the University of Cincinnati. His research interests include consumer fraud, deception, security systems, privacy, media capabilities, and virtual worlds.

Lawrence J. Weber, Director, Analytics Platform Services, IBM
The Shifting Software Market: Top Three Trends in Big Data and Analytics

Abstract: While the software market has been progressing over the past 60 years, there have been some major shifts in how both practitioners and end consumers interact with the technology. Software has evolved from a hardware dependent afterthought to an instant, on-demand service.

In this talk, we will outline and discuss top technology trends that we are seeing emerging from the software market (such as open source and cloud technologies) and illustrate how these advances may affect the way that you (and your organization) consume software, build new products and tap into deeper analytical insights.

Bio: Having spent over 20 years in technology, building new business and bringing products to market, Larry understands the benefit of business analytics and tapping into new data sources for competitive advantage. On his current mission, he is getting back to his roots, getting hands on and is redefining the way that developers interact with enterprise software and engage with IBM on the digital front.

Prior to this role, Larry ran product marketing and strategy for IBM’s big data portfolio, including Hadoop and Streaming technologies and spent considerable time with IBM’s data warehousing business launching IBM’s first family of data warehouse appliances.

Larry holds an MBA with concentrations in product management and entrepreneurship from Kenan-Flagler Business School (UNC) and a Masters of Computer Science from North Carolina State University.

Derek S. Kane, Enterprise Systems Engineer, Cloudera, Inc.
The Road Less Traveled: Data Science with Big Data

Abstract: Walk down the road with us as we go from data immaturity to the eventual destination: The Road Less Traveled - Data Science with Big Data

Derek will discuss how big data can impact your organization, how to find use cases that can make a significant impact, and how you can take your staff down the road to real expertise with Big Data and Data Science.

Bio: Derek Kane has spent the last 20 years building solutions with data. Before joining Cloudera, he spent ten years with a large financial services company where he was a Lead Architect. As a part of the Innovation team, Derek led the creation of Big Data solutions for an organization that managed $2 trillion in assets. He has also built out multiple Centers of Excellence covering Business Intelligence and Data Visualization. He is a patent holder for an application that manages Total Cost of Ownership of technology solutions. Derek has worked at Cloudera as a Systems Engineer since 2015 and is based in Columbus, Ohio. Derek holds a BS in Business and Economics from Lehigh University.

Keynote speakers

Thornton May, Author, Educator, and Futurist, Executive Director, IT Leadership Academy
Big Data, Machine Intelligence and the Future of Work

Abstract: The managing director at a White-Shoe strategic consultancy frequently counsels Global 20 enterprises, “You need a strategy for strategy.” A guest panelist on a Sunday morning political talk show likes to remind viewers, “There is a lot of politics inside politics.”

As a futurist charged with keeping an eye out for early signals of high impact trends I can safely say that most organizations need to start paying attention to the data about data – specifically how data and analytics surfaces a new division of labor in the modern workplace. In addition to deciding which human does what, executives have to determine which tasks are best conducted by advanced analytics in smart machines/algorithms.

Bio: Thornton May began his career as an anthropologist, studying tribal behavior in the modern Japanese corporation. Fascinated with the Japanese ability to observe, orient, decide and act (i.e., move data) faster than competitors, he returned to the U.S. and earned his masters of science with a concentration in cognitive science at Carnegie Mellon University. He apprenticed with über-futurist Alvin Toffler, assisting in creating the national digital strategies for Singapore, Korea and Mexico. In each national plan, high-speed data analysis figured prominently.

In his most recent book, The New Know: Innovation Powered by Analytics he analyzes what organizations know; how they come to know; and how they act upon that information—or lack thereof. May delivered the inaugural keynote at the first ever Data Science Summit. He designed and delivered the first Big Data webinar in Russia in association with the Skolkovo School of Management.

His writings, reviewed as having “Jeffersonian acoustic power,” have appeared in The Harvard Business Review, TheWall Street Journal, The Financial Times, Computerworld, India Today and the South China Morning Post.

Stuart Aitken, Chief Executive Officer, 84.51°
The Data Revolution

Abstract: How can the information you collect be beneficial to your customer and your business? We’ll explore the basic principles of data analysis and how to view information through the customer’s lens. Stuart will share how data builds brand loyalty and can create customers for life. We’ll take a look at the right way and the wrong way to reward new and existing customers for the behavior you seek. It’s not all about cost.

Data is useful to every size and type of business. Hear us share the best practices to collecting, connecting and using data.

Bio: With an extensive background in technology and marketing, Stuart Aitken is a firm believer in the power of the customer and the subjective concept of loyalty. Previously Aitken served as CEO of dunnhumbyUSA, Executive Vice President and Chief Marketing Officer for arts-and-crafts retailer Michael’s Stores. For nearly a decade, he managed loyalty marketing, data analytics, innovation, and category management at North American grocery retailer Safeway.

As dunnhumbyUSA CEO Aitken led the company’s growth as a leader in personalization, helping clients such as The Kroger Co., Macy’s, Coca-Cola, General Mills, and Procter & Gamble find success by rewarding and retaining their best customers.

Aitken holds a bachelor’s and a master’s degree in Information Management and also worked as a software industry consultant and as a technology professor.

Industry-focused track sessions

Retail and Consumer Analytics: Track Chair Dan Whitacre, Senior Director of Enterprise Data Strategy, Kroger
Health Care Analytics: Track Chair: Denise White, Director QI Analytics, Cincinnati Children's Hospital Medical Center
Supply Chain Analytics: Track Chair: Diana McHenry, Strategic Account Manager, Supply Chain Solutions, Llamasoft
Finance and Insurance Analytics: Track Chair: Steve Slezak, Director Carl H Lindner III Center for Insurance and Risk Management, Associate Professor, University of Cincinnati
Bonus Analytics Track: Track Chair: Glenn Wegryn, Executive Director, UC Center for Business Analytics

Keynote speakers

McKay Curtis, Sr. Principal, Decision Science Team, Walt Disney Company
Applying Analytics: It's More than Magic

Abstract: Providing great analytics is not enough by itself to ensure it is applied by your client. Having an engaged client throughout the development process can ensure that analytics tools make their way into the daily lives of end users. In this talk, some best practices to achieve this are discussed. This has proven to be very fruitful for the Disney Decision Science team and two examples are described to illustrate the power of client engagement to ensure successful adoption of analytics tools.

Bio: McKay Curtis is Senior Principal on the Decision Science Team at the Walt Disney Company. His current focus is to improve business practices for partners at Disney through the integration of predictive and prescriptive analytics into daily work processes. Prior to joining the Walt Disney Company five years ago, McKay worked as a postdoctoral research associate at the University of Washington developing statistical methods for the analysis data from Alzheimer’s patients. McKay earned a Ph.D. in Statistics from North Carolina State University where he focused on Bayesian methods in variable selection and shape-restricted regression.

Jorge Silva, Senior Research Statistician, Developer, Enterprise Miner, R&D, SAS
A Roadmap to Predictive Analytics: Best-in-Class and Emerging Techniques

Abstract: Analytics are ubiquitous in the business world, and picking the right method, algorithm or technology for the problem at hand can be a challenge. In this presentation we will review some of the best-in-class supervised and unsupervised methods available for a variety of applications, including market segmentation and rare event prediction. In addition, we will cover emerging techniques devised for highly challenging tasks, such as product recommendation and pattern recognition in images and video. Thanks to recent advances in machine learning–for instance, collaborative filtering, deep learning and ensembles–these problems are now tractable at scale using commodity hardware.

Bio: Jorge received his PhD in Electrical and Computer Engineering from IST Lisbon in 2007. He continued to be involved in academics as a senior research scientist at Duke University, where he applied statistical models to large-scale problems, e.g., unsupervised learning, analysis of multi-modal data, recommender systems and social networks. Since 2012 he is a Senior Research Statistician Developer at SAS, where he develops high-performance distributed machine learning algorithms for Enterprise Miner. He holds multiple US patents and has authored numerous articles in scholarly journals.

Dr. Dave Schrader, Teradata (retired)
Sports Analytics–What’s New? What’s Hot?

Abstract: This survey talk describes the current state of data analytics for 5 major professional sports – baseball, basketball, football, hockey, and soccer, as well as analytics used by trainers and strength coaches. Topics include:

  • Sport is Big Business – how much money is involved?
  • The field of Sports Analytics is hot – what’s table stakes? What’s cutting-edge?
  • How do analytics from traditional marketing apply to sports business operations?
  • How can video and sensor technologies provide opportunities for improving team operations?
  • What are the latest research results for individual and team play dynamics?
  • What can business people learn from sports analytics, and vice-versa?

Bio: Dr. Dave Schrader spent 32 years in engineering, advanced development, and marketing for high-tech companies, including 24 years at Teradata. His areas of expertise include parallel database systems, marketing and operations analytics, as well as Big Data. He recently retired but stayed on the Teradata University Network Board of Advisors, where he stays busy giving talks for faculty and students on business analytics and best practices. Since retiring, he has focused on sports analytics, attending conferences and debriefing experts to create teaching decks and reading assignments to help more students get interested in both the business and operations side of sports analytics, as well as statistics and computer science. Dr. Dave holds a Ph.D. in Computer Science from Purdue University and is a popular speaker world-wide.

Lunch sports analytics panel

Chris Calo, Senior Business Analyst, Cincinnati Reds
Geoff Smith, Analytics Advisor to the Cincinnati Bengals
Brandon Sosna, Director, Strategic Relations and Associate Director of Marketing, UC Bearcats
Moderated by Dave Schrader

Tutorials and solutions in predictive analytics

George Habek, Analytical Training Consultant, Global Academic Program, SAS

Demonstration of SAS Forecast Server using an applied example within the Health and Life Sciences industry.

George obtained his B.S. degree in Mathematics & Statistics from Loyola University Chicago and his M.S. degree in Applied Statistics (With Distinction) from DePaul University Chicago. He has more than 18 years of programming and statistical modeling with SAS® and over seven years of statistical modeling experience in database marketing. He also has expertise in statistical analysis, data mining, predictive modeling, text mining, forecasting, clustering, and survey analysis. His in-depth knowledge of SAS® tools includes BASE, STAT, ETS, Enterprise Guide, SAS Studio, Enterprise Miner, Text Miner, Forecast Studio, JMP, Visual Analytics and Visual Statistics.

Damon Ragusa, ThinkVine CEO

This session will focus on key challenges faced by marketers and their partners in marketing analytics. We’ll cover marketers’ context and our methodological approaches to attribution and optimization.

An accomplished entrepreneur and marketing technologist, Damon founded ThinkVine in 2008. Seeing an opportunity to innovate how companies evaluate the performance of their marketing in an ever increasingly complex environment, Damon led the development of what would become ThinkVine's flagship product. In early 2009, ThinkVine launched its marketing planning & optimization software and services to the marketplace. ThinkVine was subsequently selected as a leader in the marketing mix modeling space by Forrester Research, an independent research firm. Damon's responsibilities cover the overall leadership of and responsibility for the company's performance, driving ThinkVine's thought leadership platform and contributing to its long-term product vision.

A popular speaker known for his domain expertise and thought leadership, Damon is frequently asked to present at such conferences as ad:tech, American Marketing Association (AMA), Advertising Research Foundation and the Institute for International Research. Damon has held partner and senior level positions at management consulting, marketing science and software development firms. He holds degrees in Quantitative Studies and Psychology and has conducted advanced studies in both Business Administration and Computer Science.

Zahir Balaporia, CAP Solutions Partner, FICO

Integrating and Deploying Predictive Analytics for Speed, Scale and Stability: From scoring and classification tools, to the powerful capability of integrating predictive analytics with optimization. All of this in a platform that allows decision makers to interact with the models, visualize results and compare scenarios, while reducing development and deployment time. A win-win-win for decision makers, IT and analytics teams. Zahir Balaporia, Solutions Partner, FICO.

Zahir develops customer focused solutions within FICO’s Decision Management Suite. With over 20 years of business and IT operations experience, he brings thought leadership to the development of advanced analytics solutions across analytical domains and industry verticals. He also specializes in change management associated with deploying process disruptive technologies. Before coming to FICO, Zahir was Director of Advanced Planning and Decision Sciences at Schneider, a leading provider of truckload, logistics and intermodal services. His team specialized in the application of advanced analytical techniques for operational, tactical and strategic decision support across the enterprise.

Zahir is a Certified Analytics Professional through INFORMS. He is actively involved with INFORMS serving as President of the Analytics Section, and has served on the advisory council for the Business Analytics Conference for the last nine years. He is acknowledged in the books Competing on Analytics by Davenport and Harris, and The New Know by Thornton May. Zahir has a BS in Computer Engineering, an MS in Industrial Engineering, and is completing an MS in System Dynamics.

Keynote speakers

Sarah Denman, Vice President, Insights, and Jillian Payne, Director, Analytical Development Program, 84.51o
An Organization's Journey to Build Analytic Expertise

Abstract: Sarah developed the analytic training program a few years ago at dunnhumby and has a good handle on what is required to build analytic chops in an organization. She will describe how their organization got started developing a large scale analytics training program for new hires before handing it over to Jillian, who will talk about her role in expanding the program beyond just new hires to the entire analytical community at the company and beyond.

Bios: Sarah Denman has a passion for both analytics and teaching. She has spent over 7 years analyzing transactional data for dunnhumbyUSA and 84.51°, and prior to that she spent 5 years teaching mathematics and statistics at Miami University. During her time with dunnhumbyUSA/84.51°, she has had a variety of experiences, including the opportunity to develop the first analyst new graduate training program. In her current role, she leads a diverse team of insights analysts who focus on pricing strategy for both retailer and CPG partners. Sarah holds a Bachelor of Arts in Sociology and a Masters of Science in Statistics from Miami University. In her spare time, Sarah loves spending time with her husband and four children. On weekends, she can usually be found at a soccer field cheering on one of her kids. She also enjoys traveling and attempting DIY home improvement projects.

Jillian Payne graduated from Miami University in 2009 with a degree in Marketing and Decision Sciences. Upon graduation, Jillian joined 84.51° (previously dunnhumbyUSA) as an Analyst working across various parts of the business from helping Kroger get Assortment right for their best customers to answering custom analytics questions for our CPG partners. After spending four years in Analysis, she “off-roaded” for 2 years in a more commercially-focused Solutions role helping our clients understand the best solution to answer their business questions and helping the organization innovate the next solution we need to offer for our clients. Recently, Jillian has returned to Analysis where she is leading the Analyst Development Program for new hires and beyond.

Andy Kriebel: Head Coach at The Information Lab's Data School
Good to Great–Tips for Helping to Become Great with Data

Abstract: Data is everywhere. But unless you have the skills to make sense of the data, then it’s merely a pile of numbers that take up space on your hard drive. To truly become great with data takes commitment, focus, passion, and specialized set of skills.

In this presentation, Andy Kriebel will review the tips that helped him learn about data visualisation, how he applied that to his work and life, and how you can get to the next level. Andy will then talk about how this passion led to the creation of the first “Data School” for learning Tableau and Alteryx, what they’re doing at the Data School, how these people will become the next generation of great data analysts, and what you can learn from their experience.

Bio: Andy, a three-time Tableau Zen Master working hard to make it four, stumbled upon Tableau in 2007 when he was desperate for help to quickly create dashboards using SSAS cubes. Since then, it’s been Andy’s personal mission to help as many people as possible “see and understand” their data with Tableau, which is the focus of his role as Head Coach at The Information Lab’s Data School.

In August 2009 he launched, which provides examples of data visualization best practices, methods for improving existing work, and tips and tricks with Tableau Software. He writes two weekly series: Makeover Monday and Tableau Tip Tuesday. He also recently launched, a site created to highlight data visualisation best practices, and is ½ of the website

Away from Tableau, Andy enjoys spending time with his wife and four children being tourists in their own town. You might find Andy running the streets of London, playing football, or cheering on his beloved Arsenal in a local pub. One of Andy’s goals is to become to low handicap golfer at The Information Lab.

Jeff Goldman, Associate Director Enterprise Data Science at Procter and Gamble
Developing Exceptional Analytic Talent

Abstract: Analytic and Data Science Organizations drive critical competitive advantage for corporations. To leverage this potential, a company needs to build an organization that combines detailed technical and business expertise, and that has executive sponsorship that pulls them into the most critical problems of the enterprise. This presentation will look at the growth of analytics at P&G and strategies to start-up, train, operationalize, and grow analytic organizations.

Bio:Jeffrey Goldman is Associate Director of Enterprise Data Science, leading P&G’s Big Data Analytics and serving as analyst to P&G's leadership.  In recognition of his sustained analytic contribution to P&G, he was inducted into P&G’s CIO Circle.  Before his current role, Jeff led Business Analytics for Global Markets and the Western European Analytics Organization and founded and led the Market Analytics group for China and Product Supply Analytics for Asia.

Jeff was born in Cincinnati and holds a BA in Economics and a Masters in Operations Research from Cornell University. He lives in Cincinnati with his wife and son.

Rex Daisey, Data Scientist at E.W. Scripps
Beyond Technical Skills - Build Your Domain Knowledge

Abstract: This talk stresses the importance of understanding the business environment in order to have a foundation to get great actionable insights from Analytics. While it is true that true analytic talent is a requirement the success of an analyst and an analytic team requires far more domain knowledge.

The presentation will help attendees:

  • Learn the business – understand and map the competitive environment; use financial reports to get key metrics and hit the ground running.
  • Manage expectations and keep your learning agenda goals focused using 'The First 90 Days' approach by Michael Watkins.
  • Learn industry trends by watching interviews and reading popular blog posts.

Bio: Rex Daisey brings over 15 years of data analytics and business intelligence experience. He is a practitioner drawing on experience leading and mentoring analytics teams in several industries: publishing, higher education, pharmaceuticals, financial services and broadcasting. Through this regular changing of environments Rex has developed and refined several techniques to quickly learn and add value.

In his spare time Rex enjoys giving back through skills based volunteering for non-profit organizations, spending time with his wife and six year old son, and following baseball. Rex holds a Master of Business Administration (MBA) from Xavier University, an undergraduate degree from Purdue University and a Professional Certificate in Risk Management from Stanford University.

Keynote speakers

Dr. John Elder
The Peril of Vast Search (and How Target Shuffling Can Save Science)

Abstract: It’s always possible to get lucky (or unlucky). When you mine data and find something, is it real, or chance? The central question in statistics is "How likely could this result have occurred by chance?" Ancient geniuses devised formulas to answer this question for special-case scenarios. Yet, their calculus only applies to quaint, handmade analyses where a few hypotheses are considered. But modern, predictive analytic algorithms are hypothesis-generating machines, capable of testing millions of "ideas." The best result stumbled upon in its vast search has a much greater chance of being spurious. Such overfit is particularly dangerous, as it leads one to rely on a model molded to the data noise as well as signal, which usually is worse on new data than no model at all. The good news is an antidote exists! John Elder will explain the simple breakthrough solution that's rarely employed, but being rediscovered in leading fields. He will illustrate how to use the resampling method he calls "target shuffling" in multiple learning scenarios, showing how it calibrates results so they are reliable. Bottom line: Honest data science is needed to save experimental science!

Bio: Twenty years ago, John Elder founded Elder Research, America’s largest and most experienced analytics consultancy. With offices in Charlottesville, Baltimore, and Washington, DC, they’ve solved hundreds of challenges for commercial and government clients by extracting actionable knowledge from all types of data.  Dr. Elder co-authored 3 books -- on practical data mining, ensembles, and text mining -- two of which won “book of the year” awards.  John has created data mining tools, was a discoverer of ensemble methods, chairs international conferences, and is a popular workshop and keynote speaker.  Dr. Elder earned Engineering degrees from Rice and UVA, where he’s an Adjunct Professor. He was named by President Bush to serve 5 years on a panel to guide technology for national security.

Stephen Few

Abstract: There is no shortcut to enlightenment. Better decisions can only come from better understanding. Information technology does not hold the key to better decisions, we do. Technologies can augment our thinking, but cannot replace it.

The computer has ushered in a new “data age.” The “information age” is yet to come. For this to happen, we must use better technologies more intelligently. Most data is noise. With more data comes more noise but not necessarily more signals. More important than gathering more data, we must learn to distinguish signals from noise. The longer we wait, the harder this will become. While there’s still a chance, we must turn up the signals and turn down the noise. In this presentation, Stephen Few will introduce what’s needed to do this.

Bio: Stephen Few has over 20 years of experience as an innovator, consultant, and educator in the fields of business intelligence (a.k.a. data warehousing and decision support) and information design. He focuses on the effective analysis and presentation of quantitative business information. Stephen is recognized as a world leader in the field of data visualization.

Track speakers

Glenn Wegryn
Built to Last: What's Your Analytics Strategy?

Abstract: So you've sold-in Analytics to your organization, bought the software, attended the conferences, (think you) understand Big Data and have delivered a modest, but insightful analysis.  Great start!  Now get ready to roll up your sleeves to figure out what your Act II will be, and more importantly how to sustain the impact and ultimately gain the competitive advantage analytics offers.  This session, led by a seasoned practitioner, will discuss three keys to achieving long term success in analytics: Strategy, People and Relevance.

Bio: A dynamic and engaging speaker, Glenn Wegryn has been an evangelist for analytics for over 30 years.  Notably, he re-built the Advanced Business Analytics practice at P&G into a world-class, award-winning organization. Now retired from P&G, he actively consults and coaches on analytics and supply chain strategy and design. Glenn is a regular invited speaker at major conferences.  He holds a BS in Quantitative Analysis from Indiana University Kelley School of Business and is a Certified Analytic Professional by The Institute for Operations Research and Management Science (INFORMS) and currently serves as President of the Analytics Section of INFORMS.

Doug Meiser
Growing an Analytics Team

Abstract:  Analytics talent is in short supply. Learn about the way that Kroger’s Operations Team successfully constructed a mathematically diverse team to create a sustainable competitive advantage.

Bio:  Mr. Meiser is proud to be the founding member of the Operations Research Team at The Kroger Company. The Operations Research team has delivered world-class solutions in innovation, queuing, inventory, facility layout, manufacturing analysis, and many other disruptive solutions. In 2013, Doug was honored as a Franz Edelman Laureate for the Operations Research Team’s work in inventory; the medal is given to men and women who distinguish themselves with their significant contribution to applied analytics. He was honored in 2014 for the company’s rank at the number three spot in the Information Week Elite 100 for the Kroger QueVision system. Doug obtained his B.S. in Mathematics and Physics and his MBA from Northern Kentucky University. Doug enjoys coaching the micro-soccer team for his kids.

Laura Harris
Evolutionary Analytics Enablement

Abstract: Enabling a self-service model may be one of the most gratifying movements that a data executive can make. At American Modern Insurance Group, the demand for ad hoc reporting had well outpaced the team's capacity, leaving true skill sets underutilized. With this realization, Laura Harris proposed and executed a strategic vision to limit her team's reporting resources in the short term in order to enable the business long term. In this session, Harris uncovers the keys behind balancing immediate frustrations while staying the course and delivering on a greater promise – self-service in the hands of the business customer to enable insight driven operational and strategic decision making.

Bio: Laura H. Harris, CIC is Vice President of Business Intelligence & Analytics at American Modern Insurance Group. With American Modern Insurance Group for 21 years, Laura has held a variety of positions in Product Development, Underwriting, Operations and now Business Intelligence. Laura is a co-developer of the company’s five year Enterprise Data Warehouse and Business Intelligence Strategy and leads the team responsible for supporting 1,300 internal analytics business users as well as 700+ external partner users. She is a graduate of the University of Cincinnati, holds the designation of Certified Insurance Counselor and is currently pursuing her designation as a Chartered Property and Casualty Underwriter. She is a resident of Ft. Thomas, Kentucky with her husband, and is the mother of a senior in high school and first-year medical school student.

Kelly Martin
Designing Dashboards to Delight

Abstract: For far too long, business dashboards seem to have been designed to purposely abuse and confuse their users. The recent explosion of ‘beautiful’ web data visualizations has the pendulum swinging widely in the other direction… beautifully designed, but not necessarily informative or useful for business. Our job as dashboard builders is to create a cohesive and accurate information message that can stand alone in a room without us there to interpret. In this session we’ll explore how to apply meaningful design to dashboards in a way that effectively communicates the data, highlights the insights and also provides enough beauty to draw the user in.

Bio: Kelly has been working as a senior data analyst since 2000 and has an education in demography; the study of population patterns and behaviour. (MA 2001). She has worked in health care (public health, cardiology), child protection services, and telecommunications and is skilled in social research methods, statistics, SQL and Tableau. Kelly has been Tableau Zen Master for two consecutive years, 2013 and 2014. Kelly’s visualization was featured in the Keynote at the last Tableau conference and was also mentioned in GeekWire. She authors, “at play in the world of data visualization”, focusing on designing Tableau dashboards.

Jeffrey A. Shaffer
Last Call at the Bar [Chart]

Abstract: What happens when a data visualization expert walks into a bar? We've heard many times that bar charts are great visualization tools, but this chart type has some limitations. This session will focus on variations of the bar chart and line chart and alternative chart types that can be used to visualize data, while still taking advantage of the strengths of the visual system. We will discuss the pros and cons of these various alternatives and show real-world examples from a number of data visualization designers.

Bio: Mr. Shaffer is Vice President of Information Technology and Analytics at Unifund and has been instrumental in the creation and development of the complex systems, analytics and business intelligence platform at the compny. Mr. Shaffer holds a bachelor of music and a master of music degree from the University of Cincinnati and an MBA from Xavier University where he was the winner of the 2006 Graduate Student Scholarly Project in Research. Jeff is also Adjunct Assistant Professor at the University of Cincinnati in the Carl H. Lindner College of Business teaching a graduate-level course in Data Visualization. He is a regular speaker at conferences, symposiums, universities and corporate training programs on the topics of data visualization and data mining, and also teaches data visualization at the KPMG Advisory University.

Ryan Sleeper
Data-Driven Storytelling: Tips from a Tableau Iron Viz Champion

Abstract: How do you get the most out of your descriptive dashboards when you’re not always there to actually describe the stories in your data to stakeholders? Former Tableau Iron Viz Champion, Ryan Sleeper, is here to share fifteen actionable tips on balancing design, data visualization best practices, and functional requirements to get the most out of your company’s descriptive analytics. Ryan believes that without some consideration to the intangible aspects of data visualization, your descriptive analytics practice is destined to fail. This session is for anyone who wants to improve their storytelling to maximize the effectiveness, adoption, and business impact of their dashboards.

Bio: Ryan Sleeper is Director of Data Visualization at Evolytics, a full-service digital analytics consultancy out of Kansas City, where he has worked with data-driven brands including TurboTax, Mint, Roku, Sephora, Dr Pepper, and the Atlanta Hawks, among many others. Outside of his day job, Ryan enjoys creating unique sports data visualizations that have led to several notable Tableau recognitions including 2013 Elite 8 Champion, two 2013 Top 25 Tableau Public visualizations, 2014 Elite 8 Sports Viz Finalist, 2014 Top 5 Tableau Public visualization, and 2013 Tableau Iron Viz Champion. His work has garnered attention from popular websites including The Guardian, ESPN, and Grantland. He is a lifelong Kansas City Chiefs and Kansas City Royals fan.

Ronald Dravenstott
Geisinger Health Systems Uses Predictive Modeling to Mitigate No-shows

Abstract: No-shows, patient appointments that are scheduled but not completed, cost Geisinger Health System (GHS) over $20M annually. GHS has created and implemented a No-Show Predictive Model (NPM), an Artificial Neural Network-based model that identifies patients likely to no-show and enables proactive targeted interventions. The NPM and targeted intervention have been integrated with the Electronic Health Record and tested through a randomized controlled trial which showed a 24.9% relative reduction in the no-show rate. Subsequent to the randomized controlled trial, GHS has expanded the NPM to 40+ clinics. The impacts of the NPM are: 1) former no-showing patients receive care, 2) patient access to care is improved, and 3) clinics operate more efficiently. The NPM targeted interventions are projected to prevent over 5,000 no-shows annually.

Bio: Ron Dravenstott MS, Senior Modeler-Operations Research, Geisinger Health System, has been an Operations Research Practitioner at Geisinger Health System (GHS) since 2011. He received his Master of Science (2012) and Bachelor of Science (2009) in Industrial and Systems Engineering from Ohio University. In addition to his work on no-shows to outpatient appointments, while at GHS Ron has improved predictions for surgical case durations, implemented a short-term inpatient bed demand forecasting tool, and developed an Emergency Department discrete-event simulation model. Prior to joining GHS, Ron was a research assistant at Ohio University developing manufacturing cost estimation software for General Electric Aircraft Engines, Electric Power & Water Systems.

Erick D. Wikum
Tales from the Trenches of Predictive Maintenance

Abstract: The ultimate goal of predictive maintenance is to identify and address impending failures before they occur. Proliferation of low cost sensors producing reams of data provides the basis for significant progress towards that goal. And yet, significant challenges exist to harness sensor and other data to predict and diagnose failures. This presentation examines several such challenges related to interpreting data and moving from detection to action in the context of real world case studies.

Bio: Erick D. Wikum is a Principal Scientist within the TCS Innovation Lab in Cincinnati, OH. He focuses on applied supply chain research, interacting with leading universities, other TCS labs and corporate partners. Dr. Wikum has over 20 years of experience in applying Operations Research and analytics techniques to help people and organizations make better, data-driven decisions. His primary application area has been freight transportation, with expertise in airlift, rail, truckload trucking, truck-rail intermodal, third-party logistics, freight brokerage and pipeline transport.

Denise White
Predictive Analytics: What are the possibilities in health care?

Abstract: Over the past decade, the influx of electronic medical records in health care has opened up new horizons for deployment of analytics in the healthcare industry, especially in the area of predictive analytics. Improved data access and technology allows predictive modeling to answer many questions and permits proactive response that was not previously possible. Utilizing predictive analytics in both a static and real-time environment, we can answer many questions. What is the probability that a patient will be readmitted? When might an employee experience an on-the-job injury? What number of specialized nurses will we need in 2 days? How many patients are expected to be admitted/discharged on a particular day? When will we need to build additional ICU capacity? We will discuss the current methods and tools that we are using at Cincinnati Children’s Hospital to integrate predictive modeling into daily activities and explore the future potential in the industry.

Bio: Denise White is an Assistant Professor/Director of Quality & Transformation Analytics in the James M. Anderson Center for Health Systems Excellence at Cincinnati Children’s Hospital Medical Center. In her current position, she manages the analytic team supporting quality and transformation analytics across the hospital. The team provides expertise in statistical process control (SPC), performance measurement and reporting, and advanced analytics along with providing coaching and training in quality improvement analytics. Dr. White is a graduate from the University of Cincinnati’s College of Business where she received her PhD in Operations Management with a focus on Healthcare Operations. She holds a B.S degree in Mathematics and Computer Science along with an MBA. Dr. White’s research interests lie in the area of capacity management, hospital flow, scheduling, and advanced analytics.

Chris Stromblad
StratBAM: Geisinger Health System’s Strategic Bed Analysis Model

Abstract: How do executives best utilize their most expensive resources and deliver value in a highly variable environment? At Geisinger our high level decision makers are faced with this question when deciding how many beds are needed to ensure the right care at the right time for our patients. Studies have shown that elongated emergency room wait times until inpatient admission (>6 hours) are associated with an increased risk of mortality. In addition, the initial cost of an inpatient high acuity bed can be as high as $1 million, emphasizing the need for an analytic approach to support all bed capacity decisions. This presentation will detail how our team:

  • Analyzed patient flow data (>70,000 inpatients) from our electronic health record
  • Understood the detailed patient placement processes and the market forecast methods
  • Developed, validated, and applied StratBAM
  • Transformed a decision making process to be strategic, objective, data driven, and robust

Bio: Christopher Thomas Strömblad is a Senior Operations Research Modeler at Geisinger Health System’s Division of Clinical Innovation and a research associate at the Geisinger Center for Healthcare Systems Re-Engineering. At Geisinger, Chris has optimized outpatient clinic and physician scheduling with the objective of improving access to care and seeing more patients using Mixed-Integer Programming. Chris has also provided strategic decision support to multi-million dollar inpatient bed capacity challenges at times of hospital expansion and renovation.

Prior to Geisinger Chris worked at Accenture Copenhagen as part of a team of consultants and developed an IT-Vision for Save The Children Denmark.

Chris serves as a Councilor for the INFORMS Health Applications Society (HAS) and as Chair for the INFORMS HAS Practitioner Engagement Committee. Chris has a Master of Science Dual Degree in Industrial Engineering and Operations Research from The Pennsylvania State University and a Bachelor of Science in Engineering Mathematics from The Technical University of Denmark.

Zahir Balaporia
Real Time Dispatch Optimization

Abstract: Optimization is at the core of Schneider Intermodal’s driver dispatch process. At peak volumes the optimization matches thousands of hours of capacity with thousands of shipments, creating a very large and complex optimization problem to solve in real time. The data changes continuously based on updates from drivers, updates from railroads, updates from container sensors, changes to freight availability, and plans that are running ahead or behind schedule. This talk will cover:

  • An introduction to the technology framework, problem partitioning, and parallelization used to solve the optimization problem.
  • The change management program used for training frontline and upstream users.
  • The use of Hadoop to store optimization log files and the potential to use the data to feedback into the optimization process.
  • Successes and continuing challenges in deploying a semi autonomous real time dispatch optimization system.

Bio: Zahir Balaporia is Director, Process and Technology at Schneider, a premier provider of transportation, logistics and related services. He is responsible for implementation of business optimization technologies and related processes within the company’s Intermodal division. Prior to moving into the Intermodal line of business, he led the corporate Decision Engineering Team, which specializes in the application of advanced analytics for operational, tactical and strategic decision support. A Certified Analytics Professional with more than 20 years of experience, he is acknowledged in the books Competing on Analytics by Davenport and Harris, and The New Know by Thornton May. Zahir has an MS in Industrial Engineering from Purdue University and a BS in Computer Engineering from Clarkson University. He is pursuing an MS in System Dynamics from Worcester Polytechnic Institute.

Kevin Norwood

Bio: Research fellow at Procter & Gamble.

Keynote speakers

Andy Kriebel: Data Visualization Guru, Facebook
From Insights to Actions - Using Big Data to Drive Market Changing Decisions

Abstract: In 2008 during the keynote for the first Tableau Customer Conference, Stephen Few said “Our problem is not a lack of data, it’s our inability to make sense of what we have.” This simple statement resonated with Andy and he took it to heart in all of his future projects. When he began a new role at Coca-Cola in 2010, he wanted to use data visualization to “show” some of Coca-Cola’s biggest customers their data. In this session, you will learn how Andy approaches projects to go from data to insights to actions using rapid-fire analytical techniques, some of which led to multi-million dollar wins!

Bio: Andy Kriebel is a data visualization guru and Tableau expert at Facebook. He is also the creator of, a popular data visualization blog and a Tableau Zen Master. Andy’s foray into data visualization began with building project management dashboards for teams in Vietnam in 2005. His passion exploded when he began using Tableau in 2007. Since then, his drive has led to a life-changing opportunity at Facebook. In August 2009 he launched, which provides examples of data visualization best practices, methods for improving existing work, and tips and tricks with Tableau Software.

Jude Schramm: Chief Information Officer, Digital: GE Aviation
The Industrial Internet: How GE is Optimizing Assets and Operations with Big Data and Analytics

Abstract: Our vision for the Industrial Internet is simple. It’s a connected network of intelligent machines – both brilliant GE machines and others – working the way they are intended to work: on schedule, reliably, efficiently, safely and securely – all with no unplanned downtime. Learn how GE is transforming the way we work by increasing the connected capability of our brilliant machines.

Bio: Jude Schramm is the Chief Information Officer, Digital for GE Aviation. Named to this role in August 2014, he is responsible for defining one digital strategy across and leading IT strategy and support for Aviation’s digital products and internal web services. Jude joined General Electric’s Aviation division in 2001 as a project manager in the Aviation Services Fleet Management IT division. He became a certified black belt in 2004, and in 2007 was appointed IT manager of the Commercial Engines Operations division. In 2008 Jude became a certified Lean leader for GE Infrastructure, where he was responsible for cross-business synergy programs between GE Aviation and GE Energy.

Steven Pino, National Vice President of Business Analytics Services, North America, SAP
Reimagining Sports and Business with Big Data

Abstract: Hear how SAP helped the German national soccer team get a leg up in winning the 2014 World Cup and find out what this and other use cases can do for you. Get inspired as we discuss how Big Data is an opportunity to change how you work, play, and live by tracking new signals within digital noise. Imagine new ways of conducting business by hearing industry use cases to show examples of what you can achieve.

Bio: As the leader of SAP’s Business Analytics services practice, his team is focused on ensuring customer success, outcome based solutions and driving partner enablement. Mr. Pino has over 25 years’ experience working for industry leaders such as ADP, Cambridge Technology Partners, Business Objects and SAP. SAP customers represent 98% of the top 100 most valued brands in the world, and most recently made news during the 2014 World Cup when it’s Sports Analytics solutions helped the German national soccer team use Big Data and analytics for competitive advantage to take top honors.

Steven brings a broad understanding of the application of business analytics to multiple industries and diverse stakeholders, supporting their efforts to continuously generate data-driven intelligence from connected things, people and devices – through Big Data, predictive analytics, enterprise mobility and cloud computing - to optimize business processes and automate operations for competitive advantage. Mr. Pino and his team of consultants are passionate about the incredible opportunity customers have to utilize today’s technology and software to simplify everything so they are enabled to run better.

He attended the University of Cincinnati and graduated with BBAs in Information Systems and Business Management. He began his professional career as a Management Consultant for Ernst & Young LLP, where he worked as a staff and senior consultant in the Pharmaceutical practice.

Jeff Ficke: Senior Vice President, Payments Strategy & Innovation, Fifth Third Bancorp
Real-Time Cash Management in Financial Services

Abstract: Data analytics is having a dramatic impact on consumer and corporate cash management. Combined with the real innovation and product adoptions of Omni-channel market such as mobile payments, chip base cards and advancements in online banking, the industry is advancing well beyond remote check deposit and electronic money transfers. Hear about how Fifth Third Payments Organization is using data analytic solutions to fundamentally change the customer experience, accelerate receivables, more effectively disburse money & mitigate fraud for both consumers and business customers.

Bio: Mr. Ficke serves as Senior Vice President of Payments Strategy & Innovation Director for Fifth Third Bancorp. In this position, he oversees the strategic direction & evolution of Payments Strategy and Business Development for Fifth Third’s Payments & Commerce Solutions division. The Payment & Commerce Solutions group represents close to $1 billion dollars in annual revenue to Fifth Third Bancorp. Mr. Ficke was previously the Director of Treasury Management from 2010 through 2013 where he lead a $450 million dollar line of business. Before that, he was Director of Central Operations, responsible for leading more than 2,500 employees handling Fifth Third Bank’s back office functions and Call Center services to nearly six million customers.

Mr. Ficke brings 20-plus years of payments processing experience to his position. Prior to joining Fifth Third Bank, he was co-founder and executive vice president of GovConnect, where he led the company’s transformation from a startup business to a national leader in payment processing solutions for clients including many local, state and federal agencies. GovConnect was sold to First Data Corporation in 2002.

Mr. Ficke received his bachelor’s degree in Mechanical Engineering and master’s in Mechanical Engineering from The Ohio State University. Mr. Ficke is a past president of the Gorman Heritage Farm Foundation. He has previously served as a board member of both the Epilepsy Foundation of Greater Cincinnati and the Cincinnati-Hamilton County Community Action Agency.