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TOM DAVENPORT

President's Distinguished Professor of IT and Management, Babson College, Digital Fellow, MIT Initiative on the Digital Economy

Co-founder of the International Institute for Analytics, a Fellow of the MIT Initiative for the Digital Economy
He teaches analytics and big data in executive programs at Babson, Harvard Business School, MIT Sloan School, and Boston University
Named one of the top three business/technology analysts in the world, and one of the 100 most influential people in the IT industry
One of the world’s top fifty business school professors by Fortune magazine
Has been at the forefront of the Process Innovation, Knowledge Management, and Analytics and Big Data movements
Tom is thinking, writing, and speaking about what happens to humans and organizations when smart machines make many important decisions?
In his forthcoming book, The AI Advantage: How to Put the Artificial Intelligence Revolution to Work, he provides a guide to using artificial technologies in business
LinkedIn recently named Tom Davenport the #1 "must-know" writer in the education industry

Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a Fellow of the MIT Initiative for the Digital Economy, and a Senior Advisor to Deloitte Analytics. He teaches analytics and big data in executive programs at Babson, Harvard Business School, MIT Sloan School, and Boston University.

He has written or edited twenty books and over 100 articles for Harvard Business Review, Sloan Management Review, the Financial Times, and many other publications. He has been named one of the top three business/technology analysts in the world, one of the 100 most influential people in the IT industry, and one of the world’s top fifty business school professors by Fortune magazine. He earned his Ph.D from Harvard University and has taught at the Harvard Business School, the University of Chicago, the Tuck School of Business, Boston University, and the University of Texas at Austin.

One of HBR’s most frequently published authors, Tom has been at the forefront of the Process Innovation, Knowledge Management, and Analytics and Big Data movements. He pioneered the concept of “competing on analytics” with his 2006 Harvard Business Review article and his 2007 book by the same name. Since then, he has continued to provide cutting-edge insights on how companies can use analytics and big data to their advantage – topics that he explored in his 2014 book, Big Data@Work (Harvard Business Review Press). The updated edition of his bestselling business classic, Competing on Analytics: The New Science of Winning, was released by Harvard Business Review Press in September 2017.

Extending his work on analytics and big data to its logical conclusion, today Tom is thinking, writing, and speaking about what happens to humans and organizations when smart machines make many important decisions? He has explored this question and its ramifications on society and business in a series of publications. Harvard Business Review editors highlighted his latest ideas in the recently released 10 Must Reads 2017: The Definitive Management Ideas of the Year. His What's Your Data Strategy? article was published in the June 2017 issue of HBR, one on Artificial Intelligence for the Real World was highlighted in the January 2018 HBR, and a piece on When Your Jobs Become Commodities was in the January 2018 MIT Sloan Management Review. Tom’s book, co-authored with Julia Kirby, Only Humans Need Apply: Winners and Losers in the Age of Smart Machines offers tangible tools for individuals who need to work with cognitive technologies and in his forth-coming book, The AI Advantage: How to Put the Artificial Intelligence Revolution to Work, he provides a guide to using artificial technologies in business.

LinkedIn recently named Tom Davenport the #1 "must-know" writer in the education indus-try. His posts, which are shared weekly to his over 250,000 followers, explore topics such as the future of cybersecurity, big data usage at the NYPD, the automation of work, and the rise of strategy machines. The posts offer practical and often humorous insight into Tom's research on big data, analytics, and cognitive technologies, explaining how their usage is reshaping business, politics, and society.

Analytics
Business Intelligence
Future of cybersecurity
Big data
The automation of work
The rise of strategy machines

Four Eras of Analytics

There have been four different approaches for applying analytics to business over the last half century. Some organizations still practice Analytics 1.0 (the artisanal era), while others are actively pursuing Analytics 4.0 (the cognitive era). Each era requires different management of both analytics and the underlying data. In this presentation Tom Davenport will describe the attributes of each era, the drivers of change, and the valuable lessons that each era provides. He will provide examples of 3.0 and 4.0 organizations (in healthcare and other industries) and the business, technology, and human issues with which they are wrestling.

The Cognitive Corporation

Cognitive technologies (AKA artificial intelligence) offer the possibility of new and potential-ly disruptive opportunities to many businesses today. A growing number of firms are already achieving significant benefits, and are building ongoing capabilities to develop and use these technologies. In this presentation Tom Davenport will describe the constellation of cognitive technologies and some of the most prominent enterprise use cases for each. He contrasts “moon shot” projects with “low hanging fruit” uses of AI that are much likely to be successful. He’ll also discuss the strategies and steps companies can take to incorpo-rate cognitive capabilities into their businesses. Examples of successful early adopters will make tangible the potential of this important new factor in competitive success.

The Cognitive Company in Financial Services

Cognitive technologies offer the possibility of new and potentially disruptive opportunities to many businesses today, and the financial services industry is among the most aggressive users. A growing number of banking and insurance firms are building ongoing capabilities to develop and use these technologies. In this presentation Tom Davenport will describe the constellation of cognitive technologies and some of the most prominent financial use cases for each. He’ll also discuss the steps financial services firms can take to incorporate cognitive capabilities into their business processes and strategies. Examples of early adopters in the banking and insurance industries will make tangible the potential of this important new factor in competitive success.

Big Data vs. Small Data Analytics

Although many companies and observers are excited about the possibility of competitive advantage from analytics on “big data,” they may not understand fully the differences between big and small data analytics. In this session, Tom describes the concept of big data and what organizations are attempting to accomplish with it, and the role of the data scientist in extracting value from big data. He presents examples of several leading companies, from startup to established, that are aggressively pursuing big data. Throughout the session, Tom sheds light on the implications of big data and how it enables organizations to manage and bring products and services to market.

Competing on Analytics: How Fact-Based Decisions & BI Drive Performance

Companies have long used business intelligence for specific applications, but these initiatives were too narrow to affect corporate performance. Now, leading firms are basing their competitive strategies on the sophisticated analysis of business data. Instead of a single application, they are building broad capabilities for enterprise-level business analytics and intelligence. These strategies are driven by senior executives who insist on fact-based decisions. In this talk, Tom describes his recent research on firms that compete on the basis of their analytical prowess and provides guidelines for adopting similar approaches.