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.
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Current Bodily Professor: Thomas H. Davenport
Tom Davenport is the third Bodily Centennial Professor of Analytics at the Darden Business School, University of Virginia; 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.
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Past Bodily Professors
2022 - 2023: Eric SiegelDarden'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.
When it comes to machine learning projects, there’s a great opportunity to improve. Currently, the overall track record of this highly visible technology is compromised: the realized value doesn’t match the excitement... yet. And that misalignment spells opportunity.
Machine learning’s popularity exploded because of its great potential business value and sheer scientific clout — learning from data to predict impresses the best of us. The praise is not all empty hype, but surveys show a stark reality: most machine learning projects fail to deploy. The number-crunching part is solid, but using it to improve operations turns out to be a greater change-management challenge than most foresee.
Those who proactively address this dilemma by adopting a collaborative, end-to-end management practice will be ahead of the curve. They will empower their organizations to overcome impediments so that the fruits of their data scientists’ labor come to fruition.
To right the misconceptions that sabotage machine learning and write the strategic playbook to launch it effectively, Eric spent his one-year Darden appointment developing guidance and curricula to help future graduates run machine learning projects that successfully deploy.
2023 - 2024: Dean Abbott
Dean Abbott is President of Abbott Analytics and is the former Bodily Bicentennial Professor in Analytics at UVA Darden School of Business. 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, survey analysis and is frequently included in lists of the top pioneering and influential data scientists in the world. Mr. 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. Mr. Abbott holds a bachelors degree in computational mathematics from Rensselaer Polytechnic Institute and a masters degree in applied mathematics from the University of Virginia.
Tom Davenport is the third Bodily Centennial Professor of Analytics at the Darden Business School, University of Virginia; 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.
2022 - 2023: 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.
When it comes to machine learning projects, there’s a great opportunity to improve. Currently, the overall track record of this highly visible technology is compromised: the realized value doesn’t match the excitement... yet. And that misalignment spells opportunity.
Machine learning’s popularity exploded because of its great potential business value and sheer scientific clout — learning from data to predict impresses the best of us. The praise is not all empty hype, but surveys show a stark reality: most machine learning projects fail to deploy. The number-crunching part is solid, but using it to improve operations turns out to be a greater change-management challenge than most foresee.
Those who proactively address this dilemma by adopting a collaborative, end-to-end management practice will be ahead of the curve. They will empower their organizations to overcome impediments so that the fruits of their data scientists’ labor come to fruition.
To right the misconceptions that sabotage machine learning and write the strategic playbook to launch it effectively, Eric spent his one-year Darden appointment developing guidance and curricula to help future graduates run machine learning projects that successfully deploy.
2023 - 2024: Dean Abbott
Dean Abbott is President of Abbott Analytics and is the former Bodily Bicentennial Professor in Analytics at UVA Darden School of Business. 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, survey analysis and is frequently included in lists of the top pioneering and influential data scientists in the world. Mr. 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. Mr. Abbott holds a bachelors degree in computational mathematics from Rensselaer Polytechnic Institute and a masters degree in applied mathematics from the University of Virginia.
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.
