Tom Davenport

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Pioneer of the Concept of “Competing on Analytics;” Leading Expert on Using Artificial Technologies in Business; Professor of Information Technology and Management, Babson College; Co-founder of the International Institute for Analytics; Fellow of the MIT Initiative for the Digital Economy; Senior Advisor, Deloitte Analytics

Biography

Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, co-founder of the International Institute for Analytics, fellow of the MIT Initiative for the Digital Economy, and a senior advisor to Deloitte Analytics.

One of HBR’s most frequently published authors, Davenport 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 HBR 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, and then on artificial intelligence. Davenport’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. In his latest book, “The AI Advantage: How to Put the Artificial Intelligence Revolution to Work,” he provides a guide to using artificial technologies in business.

HBR editors highlighted Davenport’s latest ideas in the “10 Must Reads 2017: The Definitive Management Ideas of the Year” and again in the 2019 issue. One of his articles is also in the new “10 Must Reads on AI, Analytics, and the New Machine Age.” Davenport was also named one of ten “Top Voices” by LinkedIn–in 2016 for education and in 2018 for technology. He has also 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 50 business school professors by Fortune magazine. He has written or edited 20 books and over 250 print or digital articles for Harvard Business Review (HBR), Sloan Management Review, the Financial Times, and many other prestigious publications.

Davenport earned his doctorate 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.

Tom Davenport is available to advise your organization via virtual and in-person consulting meetings, interactive workshops and customized keynotes through the exclusive representation of Stern Speakers, a division of Stern Strategy Group®.

Videos

Media

Tom Davenport's Writings

The Pursuit of AI-Driven Wealth Management

July 7, 2021

How to Design an AI Marketing Strategy

July 1, 2021

Why Companies are Struggling to Implement AI at Scale (Audio)

June 25, 2021

Your Data Supply Chains Are Probably a Mess. Here’s How to Fix Them.

June 24, 2021

When Low-Code/No-Code Development Works — and When It Doesn’t

June 22, 2021

Improving The Healthcare Revenue Cycle With AI And RPA

June 14, 2021

The Future Of Work Now: Ethical AI At Salesforce

May 27, 2021

When Data Science Met Epidemiology

May 21, 2021

Embracing AI When Your Industry Is in Flux

May 5, 2021

The Future Of Work Now: Intelligent Mortgage Processing At Radius Financial Group

May 4, 2021

The Shift to Collaborative Analytics

April 30, 2021

The Future Of Work Now: Product Managers At Shopee

April 20, 2021

MIT Sloan Management Review logo

Experiments and Data for Post-COVID-19 Work Arrangements

March 23, 2021

AI Can Help Companies Tap New Sources of Data for Analytics

March 19, 2021

MIT Sloan Management Review logo

How HR Leaders Are Preparing for the AI-Enabled Workforce

March 17, 2021

The Future Of Work Now: AI-Assisted Clothing Stylists At Stitch Fix

March 12, 2021

4 Ways to Democratize Data Science in Your Organization

March 8, 2021

MIT Sloan Management Review logo

Execs Bullish on AI but Wary of Data Leadership

March 5, 2021

The Future Of Work Now: Good Doctor Technology For Intelligent Telemedicine In Southeast Asia

March 2, 2021

Deployment as a Critical Business Data Science Discipline

February 10, 2021

The Future Of Work Now: AI-Driven Policing In Wilmington, NC

February 3, 2021

Pushing The Frontiers Of Manufacturing AI At Seagate

January 27, 2021

An RPA Robot For Every Employee At Dentsu?

January 21, 2021

The Future Of Work Now: Pharmacists And The Robotic Pharmacy At Stanford Health Care

January 18, 2021

Data Exhaust Turbocharges Mastercard

January 13, 2021

MIT Sloan Management Review logo

How Large Companies Can Grow Their Data and Analytics Talent

November 18, 2020

MIT Sloan Management Review logo

To Fight Pandemics, We Need Better Data

August 25, 2020

Machine Learning and Organizational Change at Southern California Edison

July 30, 2020

The Future of Work Now: Natalie Munroe and the Transformation of Legal Service Delivery

July 28, 2020

Data Science Quarantined

July 15, 2020

Is AI Getting Faster?

July 14, 2020

Establishing a New Chief Data and Analytics Role at Commerzbank

July 7, 2020

Process Mining: From Analytics to Action

June 30, 2020

The Future of Work Now: The Computer-Assisted Translator and Lilt

June 29, 2020

Webinar: Creating a Data-Driven Culture

June 27, 2020

AI/ML Innovation in a Post-Pandemic World

June 23, 2020

The Recession's Impact on Analytics and Data Science

June 16, 2020

BizOps--Aligning Business and IT in Automated Decision-making

June 15, 2020

Digital Transformation Comes Down to Talent in 4 Key Areas

May 21, 2020

Your Organization Needs a Proprietary Data Strategy

May 4, 2020

How to Make Better Decisions About Coronavirus

April 8, 2020

Return on Artificial Intelligence: the Challenge and the Opportunity

March 27, 2020

The Houston Astros and the Ethical Use of Data and Analytics

March 4, 2020

An Emerging Consensus Among Chief Data Officers

February 26, 2020

Are You Asking Too Much of Your Chief Data Officer?

February 7, 2020

What Separates Analytical Leaders from Laggards

February 3, 2020

Creating a Data-Driven Culture (Audio)

January 27, 2020

The Future of Work Now - Medical Coding with AI

January 3, 2020

Analytics 3.0 And Beyond: From Ad Hoc Insights To Automated Decisions (Video)

Don't Fear the Future

Winter 2019

Learning From the Canadian Model of AI

November 19, 2019

AI at JP Morgan Chase - Breadth, Depth and Change

November 12, 2019

Physics Envy and the Second Class Status of Translators

October 30, 2019

Building a Culture That Embraces Data and AI

October 28, 2019

Digital Transformation Should Start With Customers

October 8, 2019

Wall Street Journal logo

Data Not Leading to Insights? Culture May Be to Blame

September 29, 2019

Wall Street Journal logo

The State of AI in the Enterprise

September 13, 2019

Collaborate Smarter, Not Harder

September 10, 2019

If You Want to See the Benefits of AI, Forget Moonshots and Think Boring

September 4, 2019

Self-Driving Companies are Coming

August 29, 2019

How to Tame "Automation Sprawl"

July 19, 2019

When to Stop Deliberating and Just Make a Decision

July 9, 2019

What Does an AI Ethicist Do?

June 24, 2019

Enterprise AI: Think Big, Start Small

May 1, 2019

Wall Street Journal logo

Early Adopters Bullish on Business Value of Cognitive

January 23, 2018

Wall Street Journal logo

How to Outflank the Competition with Analytics

December 14, 2017

Application of AI for Knowledge Management

Competing on Analytics

January 2006

A-Z Name

Davenport, Tom

Biography

Tom Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College, co-founder of the International Institute for Analytics, fellow of the MIT Initiative for the Digital Economy, and a senior advisor to Deloitte Analytics.

One of HBR’s most frequently published authors, Davenport 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 HBR 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, and then on artificial intelligence. Davenport’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. In his latest book, “The AI Advantage: How to Put the Artificial Intelligence Revolution to Work,” he provides a guide to using artificial technologies in business.

HBR editors highlighted Davenport’s latest ideas in the “10 Must Reads 2017: The Definitive Management Ideas of the Year” and again in the 2019 issue. One of his articles is also in the new “10 Must Reads on AI, Analytics, and the New Machine Age.” Davenport was also named one of ten “Top Voices” by LinkedIn–in 2016 for education and in 2018 for technology. He has also 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 50 business school professors by Fortune magazine. He has written or edited 20 books and over 250 print or digital articles for Harvard Business Review (HBR), Sloan Management Review, the Financial Times, and many other prestigious publications.

Davenport earned his doctorate 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.

Tom Davenport is available to advise your organization via virtual and in-person consulting meetings, interactive workshops and customized keynotes through the exclusive representation of Stern Speakers, a division of Stern Strategy Group®.

Speech Topics

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 describes the attributes of each era, the drivers of change, and the valuable lessons that each era provides. He provides 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, also known as artificial intelligence, offer the possibility of new and potentially 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 describes 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 more likely to be successful. He also discusses the strategies and steps companies can take to incorporate cognitive capabilities into their businesses. Examples of successful early adopters make tangible the potential of this important new factor in competitive success.

Making Different — and Better — Decisions

In this talk, Tom Davenport describes the results from his most recent research study on the new landscape of decision-making. He argues that recent decision failures mean that organizations need to systematically examine their approaches to making key decisions. He defines how organizations improve decisions through:

    • Different opinions and dissent in the decision process
    • Different alternatives, such as the wisdom of crowds
    • Findings from neuroscience and behavioral economics
    • Different blends of analytics and intuition
    • Different relationships between analysts and decision-makers

He draws upon interviews with more than 50 companies about how they have actually improved particular decision processes.

Competing on Analytics

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 Davenport describes his recent research on firms that compete on the basis of their analytical prowess and provides guidelines for adopting similar approaches.

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