Bodily Bicentennial Professorship in Analytics - Faculty & Research
Bodily Bicentennial Professorship in Analytics
Expanding the Impact of Analytics
To succeed and thrive in the complex, connected world in which we live, today’s business minds and solution seekers are increasingly turning to analytics, data science and artificial intelligence applications for answers. Much of analytics has developed over four decades; it is not new. What is new is the immense amount and granularity of data, the pervasiveness and speed of computing power and the mobility of both. The ability of analysts and managers to harness these tools is ramping up and scalable. We now see probabilistic forecasting and modeling used everywhere, an overnight sensation from decades of development.
Today, decision makers rely on rapidly transforming analytics, the proliferation of data and advances in computing power to provide answers to a wide range of sophisticated issues. Darden aims to advance the field through its own faculty research and by launching the Bodily Bicentennial Professorship in Analytics.
This position was created to honor the contributions of Sam Bodily, the John Tyler Professor Emeritus of Business Administration to the field of decision analysis.
Nominations
Darden is now accepting nominations for this chairholder. This visiting position will allow a leader in the field of analytics to step away from their normal activities and collaborate and share insights with the Darden and broader University of Virginia community. Full details of the assignment and how to apply are contained in the position announcement.
Analytics at Darden and UVA
The research environment associated with analytics at Darden and UVA is robust. Darden analytics faculty and the new School of Data Science provide opportunities for joint work. The new Collaboratory for Applied Data Science in Business has recently launched between the two schools to foster team efforts on real-world challenges.
Have an Impact
The Bodily Professor in Analytics will have an opportunity along with others to build a library of published solutions for the betterment of the world. Darden is committed to amplifying the findings and output produced during this appointment to enhance business practices.
2024-25 Bodily Bicentennial Professor
Keith McCormick
Keith McCormick currently serves as the 2025-2026 Bodily Centennial Professor of Analytics at Darden. Keith is a highly accomplished professional consultant, mentor, and trainer, having served as keynote and moderator at international conferences focused on analytic practitioners and leadership alike. Keith has built predictive analytics models for more than three decades, utilizing popular industry advanced analytics solutions such as IBM SPSS Statistics, IBM SPSS Modeler, KNIME Analytics Platform, and other popular machine learning tools. He’s authored seven books on the effective use of predictive analytics software and techniques. He has guided organizations to establish highly effective analytical practices across industries, including the public sector, media, marketing, healthcare, retail, finance, manufacturing, and higher education. His LinkedIn Learning courses and frequent conference workshops have reached 100s of thousands of individuals trying to learn statistics, machine learning, and data science.
Topics of interest during his year at Darden include enterprise adoption of low-code tools, the risks and potential of vibe coding, data science education, and AI Ethics.
Previous Bodily Bicentennial Professors
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2024-25: Thomas H. Davenport
Tom Davenport was the third Bodily Centennial Professor of Analytics at the Darden Business School, University of Virginia. He is also the President’s Distinguished Professor of Information Technology and Management at Babson College; an MIT lecturer and Fellow of the MIT Initiative on the Digital Economy; and Senior Advisor to Deloitte’s Chief Data and Analytics Officer Program. He pioneered the concept of “competing on analytics” with his best-selling 2006 Harvard Business Review article (and his 2007 book by the same name). He has published 23 books and over 300 articles for Harvard Business Review, MIT Sloan Management Review, and many other publications. He writes columns for Forbes, MIT Sloan Management Review, and the Wall Street Journal. His most recent book (with Nitin Mittal) is All In on AI: How Smart Companies Win Big with Artificial Intelligence.Davenport has been named one of the world’s “Top 25 Consultants” by Consulting magazine, one of the top 3 business/technology analysts in the world by Optimize magazine, one of the 100 most influential people in the IT industry by Ziff-Davis magazines, and one of the world’s top fifty business school professors by Fortune magazine. He’s also been a LinkedIn Top Voice for both the education and tech sectors.
MIT Sloan Management Review Discussion: AI Hype vs. Reality: 2025
Grewal, D., Satornino, C., Davenport, T., and Guha, A., "How Generative AI Is Shaping the Future of Marketing," Journal of the Academy of Marketing Science, Dec. 2024, https://link.springer.com/article/10.1007/s11747-024-01064-3.
Grewal, D., Satornino, C., Davenport, T., and Guha, A., "How Should Gen AI Fit Into Your Marketing Strategy?" Harvard Business Review, March 24, 2025, https://hbr.org/2025/03/how-should-gen-ai-fit-into-your-marketing-strategy.
Davenport, T. and Bean, R. "TurboTax Meets Turbo Innovation: AI at Intuit," MIT Sloan Management Review, April 1, 2025, https://sloanreview.mit.edu/article/turbotax-meets-turbo-innovation-ai-at-intuit.
Hoque, F., Davenport, T., and Nelson, E. "Why AI Demands a New Breed of Leaders," MIT Sloan Management Review, April 9, 2025, https://sloanreview.mit.edu/article/why-ai-demands-a-new-breed-of-leaders/.
Bornet, P., Wirtz, J., Davenport, T. et al, Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work, and Life (Irreplaceable Publishing, March 2025).
"Why Companies Should Consolidate Tech Roles in the C-Suite" (Harvard Business Review, 13 Sept 2024).Davenport, T., Barkin, I. All Hands on Tech: The AI-Powered Citizen Revolution, with Ian Barkin, Wiley, 2024.
Davenport, T., Redman, T., “How to Marry Process Management and AI,” Harvard Business Review, Jan-Feb. 2025.
Davenport, T., Bean, R. (2025) “Five Trends in Data Science and AI for 2025,” MIT Sloan Management Review.
Davenport, T., High, P. (2024) “How Gen AI and Analytical AI Differ--and When to Use Each,” Harvard Business Review.
Davenport, T. Bean, R. “How Gen AI Helps USAA Innovate,” MIT Sloan Management Review.
Davenport, T. and Westerman, G. (2024) “Case Study: How Aggressively Should a Bank Pursue AI?”, Harvard Business Review.
Davenport, T., Sterne, J. and Thompson, M. (2024) GenAI Can Help Companies with Customer Feedback, Harvard Business Review.
Davenport, T., Tiwari, P. (2024) “Is Your Company's Data Ready for Generative AI?”, Harvard Business Review.
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2023-24: Dean Abbott
Dean Abbott is President of Abbott Analytics and and served as the Bodily Bicentennial Professor in Analytics during the 2023-24 academic year. He is an internationally recognized thought leader and innovator in data science and predictive analytics with more than three decades of experience solving problems in customer analytics, fraud detection, risk modeling, text mining and survey analysis. He is frequently included in lists of the top pioneering and influential data scientists in the world. Abbott is the author of Applied Predictive Analytics (Wiley, 2014, 2nd Edition forthcoming) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a popular keynote speaker and bootcamp/workshop instructor at conferences worldwide and serves on advisory boards for the UC/Irvine Predictive Analytics and UC/San Diego Data Science Certificate programs. Abbott holds a bachelors degree in computational mathematics from Rensselaer Polytechnic Institute and a masters degree in applied mathematics from the University of Virginia.
Bodily Bicentennial Professor Final Presentation
"12 Ideas That Will Transform Your Predictive Models"
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2022-23: Eric Siegel
Darden's inaugural Bodily Bicentennial Professor in Analytics, Eric Siegel, is a leading consultant and former Columbia University professor who focuses on machine learning. He is the founder of the Machine Learning Week conference series, executive editor of The Machine Learning Times and author of the bestselling book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.
To right the misconceptions that sabotage machine learning and write the strategic playbook to launch it effectively, Siegel spent his one-year Darden appointment developing guidance and curricula to help future graduates run machine learning projects that successfully deploy.
Bodily Bicentennial Professor Final Presentation
"Machine Learning Is Notoriously Difficult to Deploy – But Here's How"
(view the slide deck and coverage in The Darden Report)
Additional Contributions
Lectures: Several guest appearances at UVA courses and student clubs, including the School of Data Science courses "Business Analytics for Data Scientists" and "Big Data Ethics," and the Darden Tech Club.
Curriculum supplement: Developed and "field tested" course materials to expand introductory data science courses so that they cover the business-side execution of machine learning projects – the known-how needed to ensure deployment is achieved. This supplement fulfills a critical unmet learner need. For a detailed writeup, see this article.
Research: Interviewing industry leaders at companies like UPS and FICO as well as leading professors about machine learning deployment and helping run an expanded industry survey focused on the topic. For the survey results, see this article.
Book: The AI Playbook: Mastering the Rare Art of Machine Learning Deployment by Eric Siegel (February 2024, MIT Press)
"Where FICO Gets Its Data for Screening Two-Thirds of All Card Transactions" (The European Business Review)
"Getting Machine Learning Projects from Idea to Execution" (Harvard Business Review)
"What Leaders Should Know About Measuring AI Project Value" (MIT Sloan Review)
"Survey: Machine Learning Projects Still Routinely Fail to Deploy" (KDNuggets.com)
"How to Sell a Machine Learning Project" (Builtin.com)
"The Data Disconnect: A Key Challenge for Machine Learning Deployment" (Inside Big Data)
"Machine Learning: Prediction, Decision and Action" (Darden Ideas to Action)"The AI Hype Cycle Is Distracting Companies" (Harvard Business Review)
"To Deploy Machine Learning, You Must Manage Operational Change - Here Is How UPS Got It Right" (Harvard Data Science Review)
"How Machine Learning Can Improve the Customer Experience" (Harvard Business Review)
"Predictions: Seeing the Future" (podcast interview: Trailblazers with Walter Isaacson)
"To Avoid Wasting Money on Artificial Intelligence, Business Leaders Need More AI Acumen" (Analytics Magazine, coauthored with Darden's Michael Albert)
Podcasts. Subsequent to his year at Darden, Siegel appeared on two UVA podcasts to discuss his work:
UVA Data Points (02/06/2024): "The AI Playbook | A Conversation with Eric Siegel"The Stakeholder Podcast (1/30/2024): "Eric Siegel"
