Tom Davenport

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Pioneering Authority on AI Strategies That Drive Competitive Advantage; Visiting Professor, Oxford Saïd Business School; Fellow, MIT Initiative on the Digital Economy; Senior Advisor, Deloitte AI Practice; Professor of Information Technology and Management, Babson College; Author, “Competing on Analytics” and “The AI Advantage”

Biography

Data is the gold of the 21st century and Tom Davenport – the President’s Distinguished Professor of Information Technology and Management at Babson College with affiliations at MIT and Oxford – is a master at helping companies mine it and leverage it.

Named among the top three business/technology analysts in the world, the 100 most influential people in the IT industry, one of top 25 consultants by Consulting Magazine, and the world’s top 50 business school professors by Fortune magazine, Davenport is the preeminent expert on how organizations can extract value from information and technology. A fellow of the MIT Initiative for the Digital Economy and a senior advisor to Deloitte’s AI practice, he introduced the widely influential concept of “competing on analytics” in his 2006 Harvard Business Review (HBR) article and its related 2007 book (updated in 2017). And in 2016, he was ahead of his time when he wrote about the human + AI future of work in his prescient book “Only Humans Need Apply,” followed in 2018 by “The AI Advantage: How to Put the Artificial Intelligence Revolution to Work,” which was among the first books to provide practical recommendations for using AI in business. He’s written over 300 articles for Harvard Business Review, and many were the first published on the topic.

“AI technologies won’t replace human workers but augment their capabilities with smart machines working alongside smart people,” he predicted at the time. “AI can automate structured and repetitive work, provide extensive analysis of data through machine learning, and engage with customers and employees via chatbots and intelligent agents.”

A prolific researcher and author of 20 books – including five on analytics and AI – Davenport’s work is relevant to any company that is trying to harness data, analytics, and AI for competitive advantage and organizational/cultural transformation. His latest focus is on “the future of work now” with examples of human/AI collaboration, on aggressive, “AI fueled” adopters of that technology, and on AI in health care. He’s currently writing books on all three topics.

“Every company has big data in its future and every company will eventually be in the data business,” says Davenport, whose seminal co-authored 2012 HBR article, “Data Scientist: The Sexiest Job of the 21st Century,” helped usher in a new generation of data scientists. “Companies and organizations around the world have spent trillions on hardware, software, and data science talent in order to advance analytics and AI. Yet a substantial number of firms still lack strong capabilities in these areas. The primary culprit is the absence of a culture that emphasizes data, analytics, and evidence-based decision making. But a few companies are now embarking on initiatives specifically designed to create data-driven cultures.”

Always operating at the forefront of innovation, analytics and big data movements, Davenport is a pragmatic, grounded-in-data consultant, educator and futurist. His invaluable expertise continues to help leaders across sectors use data to respond to what’s happening now and prepare for what’s ahead.

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Tom Davenport has written or edited 20 books and more than 300 articles for publications such as Sloan Management Review, Financial Times and Harvard Business Review. His 2016 book, “Only Humans Need Apply: Winners and Losers in the Age of Smart Machines,” offers guidance to individuals working with cognitive technologies. Harvard Business Review editors highlighted his 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, “Competing on Analytics,” is also in HBR’s 10 Must Reads: The Essentials collection across HBR’s 95-year history. Davenport was named one of ten “Top Voices” by LinkedIn – in 2016 for Education and in 2018 for Technology.

Davenport earned his doctorate from Harvard University and has taught at Harvard Business School, University of Chicago, Tuck School of Business, Boston University and 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 & Advisors, a division of Stern Strategy Group®.

Videos

Media

Tom Davenport's Writings

Toward Better Data Science: Mostly People, But Also Process and Technology

October 12, 2021

Portrait of an AI Leader: Piyush Gupta of DBS Bank

August 31, 2021

The Future of Health Care Is Here. Are You Ready?

August 30, 2021

Why Do Chief Data Officers Have Such Short Tenures?

August 18, 2021

Reality Check: Companies That Don't Go Digital Won't Survive

August 17, 2021

Still Wanted: (Much) Better COVID Data

August 2, 2021

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

Data is the gold of the 21st century and Tom Davenport – the President’s Distinguished Professor of Information Technology and Management at Babson College with affiliations at MIT and Oxford – is a master at helping companies mine it and leverage it.

Named among the top three business/technology analysts in the world, the 100 most influential people in the IT industry, one of top 25 consultants by Consulting Magazine, and the world’s top 50 business school professors by Fortune magazine, Davenport is the preeminent expert on how organizations can extract value from information and technology. A fellow of the MIT Initiative for the Digital Economy and a senior advisor to Deloitte’s AI practice, he introduced the widely influential concept of “competing on analytics” in his 2006 Harvard Business Review (HBR) article and its related 2007 book (updated in 2017). And in 2016, he was ahead of his time when he wrote about the human + AI future of work in his prescient book “Only Humans Need Apply,” followed in 2018 by “The AI Advantage: How to Put the Artificial Intelligence Revolution to Work,” which was among the first books to provide practical recommendations for using AI in business. He’s written over 300 articles for Harvard Business Review, and many were the first published on the topic.

“AI technologies won’t replace human workers but augment their capabilities with smart machines working alongside smart people,” he predicted at the time. “AI can automate structured and repetitive work, provide extensive analysis of data through machine learning, and engage with customers and employees via chatbots and intelligent agents.”

A prolific researcher and author of 20 books – including five on analytics and AI – Davenport’s work is relevant to any company that is trying to harness data, analytics, and AI for competitive advantage and organizational/cultural transformation. His latest focus is on “the future of work now” with examples of human/AI collaboration, on aggressive, “AI fueled” adopters of that technology, and on AI in health care. He’s currently writing books on all three topics.

“Every company has big data in its future and every company will eventually be in the data business,” says Davenport, whose seminal co-authored 2012 HBR article, “Data Scientist: The Sexiest Job of the 21st Century,” helped usher in a new generation of data scientists. “Companies and organizations around the world have spent trillions on hardware, software, and data science talent in order to advance analytics and AI. Yet a substantial number of firms still lack strong capabilities in these areas. The primary culprit is the absence of a culture that emphasizes data, analytics, and evidence-based decision making. But a few companies are now embarking on initiatives specifically designed to create data-driven cultures.”

Always operating at the forefront of innovation, analytics and big data movements, Davenport is a pragmatic, grounded-in-data consultant, educator and futurist. His invaluable expertise continues to help leaders across sectors use data to respond to what’s happening now and prepare for what’s ahead.

###

Tom Davenport has written or edited 20 books and more than 300 articles for publications such as Sloan Management Review, Financial Times and Harvard Business Review. His 2016 book, “Only Humans Need Apply: Winners and Losers in the Age of Smart Machines,” offers guidance to individuals working with cognitive technologies. Harvard Business Review editors highlighted his 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, “Competing on Analytics,” is also in HBR’s 10 Must Reads: The Essentials collection across HBR’s 95-year history. Davenport was named one of ten “Top Voices” by LinkedIn – in 2016 for Education and in 2018 for Technology.

Davenport earned his doctorate from Harvard University and has taught at Harvard Business School, University of Chicago, Tuck School of Business, Boston University and 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 & Advisors, a division of Stern Strategy Group®.

Speech Topics

Designing the Post-COVID Workplace

Longtime Harvard, MIT, and Babson professor Tom Davenport – one of the world’s foremost authorities on analytics, big data and AI strategies that drive competitive advantage – has been an objective advocate for virtual offices since the 1990s when he wrote “Two Cheers for the Virtual Office.” COVID presents a once-in-a-lifetime (we hope) opportunity to redesign work to improve employee satisfaction, productivity, and the environment all at once. In this presentation, he outlines what today’s workers want from their work environments, the various factors that constrain work design, and the importance of segmentation and choice as design elements. He also reveals the outcomes of multiple experiments and data analyses that have been performed by leading firms’ HR analytics groups, and other research that could further guide post-COVID arrangements. “Employers today need workforce policies that are guided by data and enlightened experimentation,” says Davenport, “not opinion and tradition.”

Making Smarter Data-Driven Decisions

According to Tom Davenport – distinguished professor of IT management at Babson College and co-founder of the International Institute for Analytics – the COVID-19 pandemic taught us that America’s data management system is lagging behind those of other countries. Here, he examines how decisions made during the pandemic became more important and more challenging, and that without a cohesive framework, the fractured, sometimes “alternative,” data often led to worse decisions than those made with no data at all. Bad sources and models resulted in cherry-picked facts, emotional decision making and cognitive biases. Now, with systematic methods for identifying these faulty impulses, Davenport teaches organizations how to avoid similar perils by course-correcting away from biased data to find reliable solutions. In this presentation, he discusses the role of statistics and heuristics and how much of our decision making should be offloaded to machines.

The AI-Fueled Organization

Tom Davenport revolutionized the world of analytics with his 2007 book Competing on Analytics. Now he’s describing companies that take the same aggressive approach to artificial intelligence. In this presentation, he discusses the attributes of AI-fueled companies, and details the leadership, strategy, and cultural traits that make companies highly successful with AI. From Kroger in Cincinnati to Ping An in China, he illustrates how AI-driven organizations will power the future of business.

The Promise of Health Care AI

In most industries, data, analytics, and artificial intelligence have taken the guesswork out of business strategy. So why haven’t these tools revolutionized health care? In this presentation, Tom Davenport – distinguished professor of IT management at Babson College and cofounder of the International Institute for Analytics – reviews the potential for more intelligent health care, and the structural barriers preventing a full health care makeover. He describes the silos that prevent data sharing, the slow progress of AI adoption, and the differences in objectives among stakeholders. With optimism about new AI capabilities and information management roles – like Chief Information Officer, Chief Data Officer, and Chief Analytics and AI Officer – and a keen understanding of internal change management issues, he offers health care leaders practical solutions for making more informed decisions through full data integration.

The Future of Work is Now: AI, Skills, and Job Redesign

For years, experts have predicted AI will fundamentally change the future of work. But Tom Davenport – distinguished professor of IT management at Babson College and visiting professor at Oxford’s business school – reveals that many workers are already close colleagues with AI systems in achieving their daily work objectives. Drawing on more than 30 cases, he highlights examples of AI-assisted work, discusses what leads to success, and details how companies can redesign work and upskill workers. As Davenport predicted in his 2016 book “Only Humans Need Apply,” augmentation of human work is both far more likely to succeed and offers far more value than replacement of humans through automation.

Competing on the Three A’s: Getting Up to Speed with Analytics, Automation, and AI

Companies around the world have spent trillions of dollars on talent, software and devices to advance their analytics and AI capabilities, yet a substantial number still lack strong data-driven insights. In this talk, Tom Davenport – distinguished professor of IT management at Babson College and cofounder of the International Institute for Analytics – outlines the issues impeding analytics and AI adoption and cultural change. With statistics showing that only a small percentage of analytics and AI models ever reach production deployment, Davenport teaches leaders how to use data to reach more customers, optimize supply chains, improve HR, build enterprise-level intelligence, and significantly exceed business goals by structuring analytics and AI to achieve greater ROI.

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