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Visiting Professor at Saïd Business School, University of Oxford
Cambridge, Massachusetts, United States
Tom Davenport is a world-renowned thought leader and author, is the President’s Distinguished Professor of Information Technology and Management at Babson College, a Fellow of the MIT Center for Digital Business, and an independent senior advisor to Deloitte Analytics.
An author and co-author of 20 books and more than 200 articles, he helps organizations to transform their management practices in digital business domains such as artificial intelligence, analytics, information and knowledge management, process management, and enterprise systems.
He's been named:
A "Top Ten Voice in Tech" on LinkedIn in 2018
The #1 voice on LinkedIn among the "Top Ten Voices in Education 2016"
One of the top 50 business school professors in the world in 2012 by Fortune magazine
One of the 100 most influential people in the technology industry in 2007 by Ziff-Davis
The third most important business/technology analyst in the world in 2005 by Optimize magazine
One of the top 25 consultants in the world in 2003
For more information: http://www.tomdavenport.com/
Available For: Authoring, Consulting, Speaking Travels From: Cambridge, Massachusetts, United States
Points based upon Thinkers360 patent-pending algorithm.
The Business Value of MLOps
October 12, 2021
Machine learning has been used by companies for several decades now, but over the last few years it has become a critical business resource for many organisations. The capabilities to train models with data, to generate accurate predictions about important business outcomes, and to analyze both structured and unstructured data have made machine learning the most important component of artificial intelligence.
How AI Is Helping Companies Redesign Processes
March 02, 2023
In the 1990s, business process reengineering was all the rage: Companies used budding technologies such as enterprise resource planning (ERP) systems and the internet to enact radical changes to broad, end-to-end business processes. Buoyed by reengineering’s academic and consulting proponents, companies anticipated transformative changes to broad processes like order-to-cash and conception to commercialization of new products.
8 Strategies for Chief Data Officers to Create — and Demonstrate — Value
January 31, 2023
The chief data officer (CDO) role was only established in 2002, but it has grown enormously since then. In one recent survey of large companies, 83% reported having a CDO. This isn’t surprising: Data and approaches to understanding it (analytics and AI) are incredibly important in contemporary organizations. What is eyebrow-raising, however, is that the CDO job is terribly ill-defined. Sixty-two percent of CDOs surveyed in the research we describe below reported that the CDO role is poorly understood, and incumbents of the job have often met with diffuse expectations and short tenures. There is a clear need for CDOs to focus on adding visible value to their organizations.
If you ask someone to name a company that’s putting artificial intelligence at the center of its business, you’ll probably hear a predictable list of technology powerhouses: Alphabet (Google), Meta (Facebook), Amazon, Microsoft, Tencent, and Alibaba. But at legacy organizations in other industries many leaders feel that it’s beyond the capabilities of their companies to transform themselves using AI. Because this technology is relatively new, however, no company was powered by AI a decade ago, so all those that have been successful had to accomplish the same fundamental tasks: They put people in charge of creating the AI; they rounded up the required data, talent, and monetary investments; and they moved as aggressively as possible to build capabilities.
Transforming The Internet With Project Liberty
November 18, 2022
Like almost all the reflective tech watchers I know, I am worried about what social media is doing to our society. Algorithm-driven polarization, misinformation, hate speech, etc.—all have been exacerbated by our existing social media landscape. So I am of course interested in any attempts to address these issues.
Why Your Company Needs Data-Product Managers
October 13, 2022
There’s a familiar problem with companies’ efforts to build AI and analytics applications: They hire or engage with data scientists to build models, but the models are rarely deployed into production. A recent survey of data scientists found that the majority saw 20% or fewer of their models go into production deployment.
How Truist CDO Tracy Daniels Adds Value To Her Organization
October 06, 2022
Over the past couple of months I’ve been embedding myself in the world of Chief Data Officers. I’m working with Amazon Web Services and the MIT CDO/Information Quality Symposium on a report about the role, which is based on both a large survey and 25 interviews. The report will be out early next month, but I thought I’d give a preview of it by focusing on one CDO I interviewed. Tracy Daniels of Truist—the name for the combination of SunTrust and BB&T banks—was the first CDO I spoke with. I thought it might be useful to compare her perspective to some of the other things I learned about contemporary CDOs.
Is Data Scientist Still the Sexiest Job of the 21st Century?
July 15, 2022
Ten years ago we published the article “Data Scientist: Sexiest Job of the 21st Century.” Most casual readers probably remember only the “sexiest” modifier — a comment on their demand in the marketplace. The role was relatively new at the time, but as more companies attempted to make sense of big data, they realized they needed people who could combine programming, analytics, and experimentation skills. At the time, that demand was largely restricted to the San Francisco Bay Area and a few other coastal cities. Startups and tech firms in those areas seemed to want all the data scientists they could hire. We felt that the need would expand as mainstream companies embraced both business analytics and new forms and volumes of data.
New Mindsets For Digital Transformation
April 12, 2022
I recently participated in a Red Hat online customer event that changed my thinking about how digital transformation takes place, and how digital capabilities can transform customer events. It was an intentionally intimate affair—two discussion leaders, one facilitator, and about ten customer executives. The format was an interesting one too—first a “fireside chat” with me, George Westerman of MIT, and Mike Walker, the facilitator, who runs Red Hat’s Open Innovation Labs. Then we moved into a “Lean Coffee” session, in which participants suggest topics, talk about them for five minutes, and vote whether to continue the same topic for another five minutes or move to another. It’s a lively format that never gets boring. And the graphic facilitator Tricia Walker annotated the proceedings .
Tags: Digital Transformation, Management, Leadership
Was Your Information Swimming Naked During The Pandemic?
April 07, 2022
The highly successful investor Warren Buffet is fond of saying, “Only when the tide goes out do you discover who’s been swimming naked.” The Covid pandemic is the most recent example of a major low tide event for unprepared organizations. We see its effects in tangled supply chains, confusing work arrangements, transportation systems in disarray, and now unresponsive information environments. This latter issue is an important one—so much so that I plan to devote several posts to it.
Your CEO Needs To Really Get AI
March 07, 2022
For a forthcoming book with Nitin Mittal of Deloitte, I’ve been researching companies that are “All In on AI,” as the book will be titled. These are companies who have made substantial and long-term bets on the notion that AI will revolutionize the way they do business. In several of the companies, the CEOs have been heavily engaged in the AI-driven transformation process. One of them is Piyush Gupta, the CEO of Singapore-based DBS Bank, whom I have written about elsewhere as an AI leader
Digital Workers Are Toiling Away At A Bank Near You
March 01, 2022
In the early days of automation and AI, vendors rarely mentioned the possibility of smart machines replacing human beings. Jobs were not going to be automated out of existence; instead they were going to be augmented, with machines doing the boring tasks and humans freed to do more creative and interesting work. Virtually every vendor of AI and automation systems adopted this mantra. And it was mostly correct; AI and robotic process automation (RPA) generally automated tasks, not entire jobs, so at most any human job loss was on the margins.
Platform Agnosticism, Fabrics And Faster Data Access: Unwrapping A Solution
February 15, 2022
In a short series of articles/posts (first one here) I’ve described a situation in which analytical insights have been slower to arrive than what is needed by business decision-makers. In the second article I suggested that a knee-jerk preference for the cloud when premise-based solutions seem to provide faster time to insight was part of the problem. For this third and final post on the matter, I promised an overall solution.
Is The Cloud Slower For Analytical Insights?
January 21, 2022
In my last post I described a big problem related to data in the pandemic. According to an IBM global survey of information executives, the Covid pandemic, like previous business crises, put pressure on IT organizations to deliver business information quickly. Reliable real-time data and analytics for decision-making became more critical. But many IT organizations couldn’t deliver; survey respondents said that the information and insights needed by the business often weren’t available. They mentioned issues of timeliness, integration, and a shortage of IT services as reasons. The IT executives agreed that real-time analytics for decision-making are particularly critical during business crises, but many can’t provide them in real time. Instead, their systems and reports are more focused on transaction data, which tends to be provided more quickly than analytics.
Why Do Chief Data Officers Have Such Short Tenures?
September 23, 2021
The Chief Data Officer is arguably one of the most important roles at a company. It’s also a position that has become notoriously hard to stay in. The average tenure of CDOs is just two to two-and-a-half years. There are a few reasons for this. The role is relatively new, so companies are still trying to decide what they want from the person in this position. Many companies expect the impossible from their CDO. Finally, CDOs often have trouble selling their actual accomplishments to a business audience — they just don’t speak the language. But, it doesn’t have to be this way. One successful CDO imparted two pieces of advice: 1) Start with a clear connection to business strategy with tangible examples of how data analytics can drive business outcomes (topline, bottom line, cash, stewardship), and 2) lead with 1-2 forward thinking business partners to demonstrate what is possible. Those partners become the change agents across the organization.
Artificial Intelligence and Work: Two Perspectives
September 02, 2021
One of the most important issues in contemporary societies is the impact of intelligent technologies on human work. For an empirical perspective on the issue, we recently completed 30 case studies of people collaborating with AI-enabled smart machines. 1 Twenty-four were from North America, mostly in the US. Six were from Southeast Asia, mostly in Singapore. We compare some of our observations to one of the broadest academic examinations of the issue. In particular, we focus on our case study observations with regard to key findings from the MIT Task Force on the Work of the Future report.
The Pursuit of AI-Driven Wealth Management
MIT Sloan Management Review
July 07, 2021
Understanding the application of AI to business requires an understanding of context — strategy, customers, company culture, and so forth. One application worthy of study across organizations is wealth management. A number of banks and investment firms are trying to use AI to improve that management — either to eliminate human wealth advisers altogether or, much more commonly, to augment their efforts. Our survey research suggests that while many organizations have challenges with production deployments of AI, wealth management is a clear exception.
Your Data Supply Chains Are Probably a Mess. Here’s How to Fix Them.
June 24, 2021
Data management has bedeviled large companies for decades. Almost all firms spend a lot on it but find the results unsatisfactory. While the issue does not appear to be growing worse, resolving it is increasingly urgent as managers and companies strive to become more data driven, leverage advanced analytics and artificial intelligence, and compete with data. In this article we’ll explore a powerful approach to data management through the lens of “data products” and “data supply chains.”
When Low-Code/No-Code Development Works — and When It Doesn’t
June 22, 2021
It used to be that when companies needed new information systems, they either had to hire a developer or use off-the-shelf software. Now, however, there’s a third option: Low-code/no-code applications allow organizations to build custom systems without hiring teams of developers or compromising on just close enough software for administrative tools; workflow or case management systems (a modern take on traditional business process management tools); virtual assistants or chatbot tools; and function-specific tools in the marketing space. To make proper use of them, however, managers need to know how they work and what they’re good for: small business transactions, small-scale automation, analytics, and website developing are all good use cases. There are also management challenges to watch out for: the proliferation of applications built by “citizen developers” can create a shadow IT problem, where only one user knows how the system works. Department managers should be encouraged to facilitate LC/NC development, and be educated about how the technology works, what tools the organization supports, and the desired relationship between citizen developers and the IT organization.
Improving The Healthcare Revenue Cycle With AI And RPA
June 14, 2021
Imagine that you’re the CEO of a large healthcare provider, and you’re thinking about what to do with AI. You’ve heard about some of the fascinating results out of various research labs about how AI can equal or exceed human physicians in diagnosing cancer, retinal diseases, and even Covid-19. You salivate a bit at the dollars you might bring in from funding organizations and rich donors who want to be associated with these sexy developments.
The Future Of Work Now: Ethical AI At Salesforce
May 27, 2021
In September 2016, Salesforce founder and CEO Marc Benioff informed employees, customers, and investors that Salesforce would be an AI-driven company. Earlier that year, Microsoft released its Tay research chatbot project through a Twitter Account. Microsoft shut down Tay after only 16 hours because it started to mimic the deliberately offensive behavior of other Twitter users, and Microsoft had not given the bot an understanding of such inappropriate behavior.
When Data Science Met Epidemiology
May 21, 2021
During the COVID-19 pandemic, many data science and business analytics practitioners have been pulled—mostly willingly—into the field of epidemiology. Large businesses with data science teams wanted to learn as much as possible about the likely course of the infection in the places where they do business. Some may also have had some epidemiologists or medical officers in the organization, but they didn’t necessarily have enough analytical talent in their groups to run the numbers on the virus’ prevalence and growth.
Deployment as a Critical Business Data Science Discipline
May 14, 2021
In this article, we focus on a key problem in industry: getting data science models deployed into production within organizations. The tasks and skills involved in deployment are often not considered as a key component of data science initiatives, but they are critical to data science success. We describe evidence of the deployment problem, the components of deployment, and how some campus-based business analytics degree programs attempt to inculcate deployment skills.
Embracing AI When Your Industry Is in Flux
MIT Sloan Management Review
May 05, 2021
One of the great challenges we have seen businesses face in recent years is how they approach data and analytics (and now artificial intelligence) when their industries are undergoing major transformation. It’s hard enough to create a data-driven culture, compete on analytics, develop data-driven products and services, and so forth under normal business conditions, as we noted in our March column about the newest NewVantage Partners survey on big data and AI. But doing it while your business and industry are transforming — the old line of changing out a jet engine while the plane is flying through turbulence at 35,000 feet — is really tough.
How HR Leaders Are Preparing for the AI-Enabled Workforce
May 01, 2021
The promise — and threat — of AI is real. But the impact on jobs has not yet arrived in most organizations. As recently as 2017, headlines such as “Bosses Believe Your Work Skills Will Soon Be Useless” (from the The Washington Post) were common. Oxford University researchers argued in 2013 that 47% of U.S. jobs were at risk of loss to automation. MIT launched its institute-wide task force on the future of work in 2018. Leaders around the world began to consider how their organizations would be different when thousands of their employees’ jobs are automated away.
AI Can Help Companies Tap New Sources of Data for Analytics
March 19, 2021
Over the past several years, technology has rapidly changed what enterprise analytics can do. Analytical approaches that incorporate predictive models have begun to displace merely descriptive approaches. Descriptive analytics, which continue to be valuable for many users, have evolved as well, making greater use of visual analytics and moving toward a self-service model in which nontechnical users can often develop their own analyses. In general, analytics are quickly becoming both easier to use and more powerful.
4 Ways to Democratize Data Science in Your Organization
March 08, 2021
Many organizations have begun their data science journeys by starting “centers of excellence,” hiring the best data scientists they can and focusing their efforts where there is lots of data. In some respects, this makes good sense — after all, they don’t want to be late to the artificial intelligence or machine learning party. Plus, data scientists want to show off their latest tools.
What is a minimum viable AI product?
January 25, 2021
One of the key attributes of the lean startup approach popularized by Steve Blank and Eric Ries is the development and refinement of a minimum viable product (MVP) that engages customer and investor attention without large product development expenditures. Initially defined by technologist Frank Robinson, an MVP may not meet all customer needs, but it offers enough capabilities for highly interested customers to get started. It’s a paradigm that has become well established in technology product development.
Getting Serious About Data and Data Science
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October 05, 2020
Share This! To implement successful data programs, companies need to shift goals, muster resources, and align people. Data science, including analytics, big data, […]
The post Getting Serious About Data and Data Science appeared first on Tom Davenport.
Digitizing And Automating Unsung Heroics: The Case Of Pathology
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June 29, 2020
Share This! We are all very familiar with and thankful for the sacrifices of front-line healthcare professionals in the COVID-19 pandemic. We’re less […]
The post Digitizing And Automating Unsung Heroics: The Case Of Pathology appeared first on Tom Davenport.
Digital Transformation Comes Down to Talent in 4 Key Areas
May 21, 2020
Over the years we’ve participated in, advised on, or studied hundreds of digital transformations. In doing so, we’ve gained a perspective on just how difficult true digital transformation really is and what it takes to succeed. Digital transformation is not for the faint of heart — the unfortunate reality is that, to date, many such efforts, like transformation programs in general, have failed.
Beyond Unicorns: Educating, Classifying, and Certifying Business Data Scientists
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May 20, 2020
Share This! There is increasing recognition that the data scientist ‘unicorn’—one who can master all the necessary skills of data science required […]
The post Beyond Unicorns: Educating, Classifying, and Certifying Business Data Scientists appeared first on Tom Davenp
Your Organization Needs a Proprietary Data Strategy
May 04, 2020
What’s the most overlooked piece of your company’s data strategy? If you’re like many companies, it’s probably proprietary data — data that is unique to a company and can be used to create a sustainable competitive advantage. This is not to mean trade secrets and intellectual property (which is often proprietary but seldom really data), but rather, data where the company is the only organization that has it, or it has added enough value to make it a unique business asset. Proprietary data can be big or small, structured or unstructured, raw or refined. What’s important is that it is not easily replicated by another entity. That’s what makes it a powerful means of achieving offensive value from data management.
Winter Is Coming—For The Economy And AI
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March 31, 2020
Share This! Economic winter has been a long time coming; the US has had the longest-running bull market in the country’s history. Markets, […]
The post Winter Is Coming—For The Economy And AI appeared first on Tom Davenport.
How CEOs Can Lead a Data-Driven Culture
March 23, 2020
While businesses across the world are trying to make more effective use of data, analytics, and AI, a key impediment is holding many of them back: The lack of a culture that truly values data/analytics capability and the superior decision making that can flow from it. Yet as we’ll describe, it’s possible to create a data-driven culture and accrue the competitive benefits that result.
The Houston Astros And The Ethical Use Of Data And Analytics
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March 07, 2020
Share This! I’ve been thinking a lot about the Houston Astros. They won the 2017 World Series with an impressive performance, and were […]
The post The Houston Astros And The Ethical Use Of Data And Analytics appeared first on Tom Davenport.
Are You Asking Too Much of Your Chief Data Officer?
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February 10, 2020
Share This! Since the first chief data officer was appointed at Capital One in 2002, the role has been plagued by confusion […]
The post Are You Asking Too Much of Your Chief Data Officer? appeared first on Tom Davenport.
Are You Asking Too Much of Your Chief Data Officer?
February 07, 2020
Since the first chief data officer was appointed at Capital One in 2002, the role has been plagued by confusion about its purpose. Although surveys of large organizations by Randy’s firm NewVantage Partners show an overall increase in the prevalence of the role — climbing from 12% in 2012 to 68% in 2018, and falling somewhat in 2019 — CDOs’ responsibilities have remained unclear. In the most recent survey, only 28% of respondents agreed that the role was “successful and established.”
Building a Culture That Embraces Data and AI
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October 29, 2019
Share This! Many organizations aspire to have cultures that embrace data, analytics and AI, and other new technologies, but few make specific attempts to create […]
The post Building a Culture That Embraces Data and AI appeared first on Tom Davenport.
How to Tame “Automation Sprawl”
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July 24, 2019
Share This! One of the generally unheralded trends in enterprise IT is the proliferation of automation tools. Dozens of vendors offer systems to […]
The post How to Tame “Automation Sprawl” appeared first on Tom Davenport.
When to Stop Deliberating and Just Make a Decision
July 09, 2019
You’ve come up with ideas, narrowed down your options, and looked at the available data. You’ve asked all the right questions to guide your choice. And yet, for some reason, you just can’t pull the trigger on a decision. What’s the hold up?
What Process Mining Is, and Why Companies Should Do It
April 23, 2019
There have long been a few fundamental challenges associated with business process management, at least for as long as the two of us have been involved with the field (forty years or so, for better or worse). Two of the most troublesome problems, in our view, are at least partially responsible for the fact that process management and improvement is, among many companies, a back-burner issue at the moment. But a relatively new and innovative technology, process mining, has the capability to solve both of the problems and to revitalize process management in firms where it has lain fallow for years.
Is HR the Most Analytics-Driven Function?
April 18, 2019
I have argued over the past decade that the Human Resources (HR) function has the potential to become one of the leaders in analytics. The key word, I thought, was potential. Not anymore. A recent global survey on which I collaborated with Oracle suggests that HR is right up there with the most analytical functions in business — and even a bit ahead of a quantitatively-oriented function like Finance. Many HR departments are making use of advanced analytical methods like predictive and prescriptive models, and even artificial intelligence.
Companies Are Failing in Their Efforts to Become Data-Driven
February 05, 2019
Becoming “data-driven” has been a commonly professed objective for many firms over the past decade or so. Whether their larger goal is to achieve digital transformation, “compete on analytics,” or become “AI-first,” embracing and successfully managing data in all its forms is an essential prerequisite. Consistent with these goals, companies have attempted to treat data as an important asset, evolve their cultures in a more data-oriented direction, and adjust their strategies to emphasize data and analytics.
How to Set Up an AI Center of Excellence
January 16, 2019
Artificial intelligence is one of the most powerful technologies for reshaping business in decades. It has the ability to optimize many processes throughout organizations and is already the engine behind some of the world’s most valuable platform businesses. In our view AI will become a permanent aspect of the business landscape and AI capabilities need to be sustainable over time in order to develop and support potential new business models and capabilities.
Using AI to Improve Electronic Health Records
December 13, 2018
Electronic health record systems for large, integrated healthcare delivery networks today are often viewed as monolithic, inflexible, difficult to use and costly to configure. They are almost always obtained from commercial vendors and require considerable time, money, and consulting assistance to implement, support and optimize.
How B2B Software Vendors Can Help Their Customers Benchmark
August 10, 2018
Knowing which organizations perform the best on any particular dimension used to require subjective surveys or painstaking research. Today, the data to answer those questions exists — it’s captured by the software-as-a-service firms whose services companies use to run their businesses. Mainstream software companies are beginning to hold “data mirrors” up to their customers, allowing scoring and benchmarking of their customers’ strategies. We’ve already seen that it’s possible to use external data to evaluate firms on what business models they are employing, and what those business models mean for their valuations. Those analyses rely on publicly available data sources, but software providers have accumulated growing amounts of private data on almost every aspect of their customers’ technology, operations, people, and strategies. It’s time that these data accumulators begin to share insights back to the creators of all this data, and several firms are beginning to do so.
Artificial Intelligence for the Real World
February 01, 2018
In 2013, the MD Anderson Cancer Center launched a “moon shot” project: diagnose and recommend treatment plans for certain forms of cancer using IBM’s Watson cognitive system. But in 2017, the project was put on hold after costs topped $62 million—and the system had yet to be used on patients. At the same time, the cancer center’s IT group was experimenting with using cognitive technologies to do much less ambitious jobs, such as making hotel and restaurant recommendations for patients’ families, determining which patients needed help paying bills, and addressing staff IT problems.
All-in On AI: How Smart Companies Win Big with Artificial Intelligence
Harvard Business Review Press
December 06, 2022
Written by bestselling author Tom Davenport and Deloitte's Nitin Mittal, All-In on AI looks at artificial intelligence at its most extreme—from established companies like Anthem, Ping An, Airbus, and Capital One. The book also features lessons from startups and tech firms, but the focus is on how existing firms can transform themselves.
Working with AI: Real Stories of Human-Machine Collaboration (Management on the Cutting Edge) Hardcover – September 27, 2022
The MIT Press
September 08, 2022
This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers.
The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge)
The MIT Press
October 16, 2018
In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM’s Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don’t go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient.
Competing on Analytics: The New Science of Winning; With a New Introduction (Updated, with a New Introduction: The New Science of Winning)
Harvard Business Review Press
September 01, 2017
This landmark work, the first to introduce business leaders to analytics, reveals how analytics are rewriting the rules of competition. Updated with fresh content, Competing on Analytics provides the road map for becoming an analytical competitor, showing readers how to create new strategies for their organizations based on sophisticated analytics. Introducing a five-stage model of analytical competition, Davenport and Harris describe the typical behaviors, capabilities, and challenges of each stage. They explain how to assess your company’s capabilities and guide it toward the highest level of competition. With equal emphasis on two key resources, human and technological, this book reveals how even the most highly analytical companies can up their game.
Tags: Analytics, Digital Transformation, Leadership
Only Humans Need Apply: Winners and Losers in the Age of Smart Machines
May 24, 2016
An invigorating, thought-provoking, and positive look at the rise of automation that explores how professionals across industries can find sustainable careers in the near future.
Nearly half of all working Americans could risk losing their jobs because of technology. It’s not only blue-collar jobs at stake. Millions of educated knowledge workers—writers, paralegals, assistants, medical technicians—are threatened by accelerating advances in artificial intelligence.
Big Data at Work: Dispelling the Myths, Uncovering the Opportunities Illustrated Edición
Harvard Business Review Press
February 25, 2014
When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind.
Keeping Up with the Quants: Your Guide to Understanding and Using Analytics
Harvard Business Review Press
June 11, 2013
Welcome to the age of data. No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)—your world is awash with data.
Judgment Calls: Twelve Stories of Big Decisions and the Teams That Got Them Right
Harvard Business Review Press
April 03, 2012
Despite the dizzying amount of data at our disposal today—and an increasing reliance on analytics to make the majority of our decisions—many of our most critical choices still come down to human judgment. This fact is fundamental to organizations whose leaders must often make crucial decisions: to do this they need the best available insights.
Analytics at Work Smarter Decisions. Better Results.
Harvard Business Review Press
February 08, 2010
One of the top fifteen must reads for 2010! – CIO Insight
A “how-to” guide for developing an analytical capability in your company, and putting it to work. As a follow-up to the bestseller Competing on Analytics, Tom Davenport and his co-authors provide practical frameworks and tools for all organizations wanting to become more analytical and to make better data-based decisions.
Competing on Analytics: The New Science of Winning
Harvard Business Review Press
March 06, 2007
You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool.
In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling.
Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics.
Thinking for a Living: How to Get Better Performances And Results from Knowledge Workers
Harvard Business Review Press
September 13, 2005
Knowledge workers create the innovations and strategies that keep their firms competitive and the economy healthy. Yet, companies continue to manage this new breed of employee with techniques designed for the Industrial Age. As this critical sector of the workforce continues to increase in size and importance, that's a mistake that could cost companies their future. Thomas Davenport argues that knowledge workers are vastly different from other types of workers in their motivations, attitudes, and need for autonomy--and, so, they require different management techniques to improve their performance and productivity.
Based on extensive research involving over 100 companies and more than 600 knowledge workers, Thinking for a Living provides rich insights into how knowledge workers think, how they accomplish tasks, and what motivates them to excel. Davenport identifies four major categories of knowledge workers and presents a unique framework for matching specific types of workers with the management strategies that yield the greatest performance.
Written by the field's premier thought leader, Thinking for a Living reveals how to maximize the brain power that fuels organizational success. Thomas Davenport holds the President's Chair in Information Technology and Management at Babson College. He is director of research for Babson Executive Education; an Accenture Fellow; and author, co-author, or editor of nine books, including Working Knowledge: How Organizations Manage What They Know (HBS Press, 1997).
What's the Big Idea? Creating and Capitalizing on the Best New Management Thinking
Harvard Business Review Press
April 01, 2003
The secrets of successful idea practitioners change management. Reengineering. Knowledge management. Major new management ideas are thrown at today's companies with increasing frequency - and each comes with evangelizing gurus and eager-to-assist implementation consultants. Only a handful of these ideas will be a good fit for your organization. Choose the right idea at the right time and your company can become more efficient, more effective, and more innovative. Choose the wrong one - or jump on the right bandwagon too late - and your company could fall hopelessly behind. Thomas H. Davenport and Laurence Prusak say that some managers have found ways to improve their odds of success in the risky but essential game of idea management. In "What's the Big Idea?, they introduce a largely unsung class of managers they call - idea practitioners - individuals who do the real work of importing and implementing new ideas into businesses. While gurus reap most of the credit when big ideas take flight, Davenport and Prusak's research reveals that idea practitioners actually play the most important role: they turn the right ideas into action. Drawing from decades of consulting, academic, and business experience and from their novel study of more than 100 of these critical change leaders, "What's the Big Idea?" offers tools and frameworks for: assessing the merits of the top business gurus; scanning and tracking emerging ideas in the marketplace; distinguishing promising ideas from rhetoric; refining ideas to suit your organization's particular needs; packaging and selling the idea internally; and ensuring successful implementation. Davenport and Prusak prove that there are no faddish management ideas - only faddish ways of adopting them. Encouraging managers to embrace the power of ideas while avoiding the hype that often accompanies them, this pragmatic guide shows how passion and reason combine to build innovative companies.
The Attention Economy: Understanding the New Currency of Business
Harvard Business Review Press
September 01, 2002
In today's information-flooded world, the scarcest resource is not ideas or even talent: it's attention. In this groundbreaking book, Thomas Davenport and John Beck argue that unless companies learn to effectively capture, manage, and keep it--both internally and out in the marketplace--they'll fall hopelessly behind.
In The Attention Economy, the authors also outline four perspectives on managing attention in all areas of business:
1) measuring attention
2) understanding the psychobiology of attention
3) using attention technologies to structure and protect attention
4) adapting lessons from traditional attention industries like advertising
Drawing from exclusive global research, the authors show how a few pioneering organizations are turning attention management into a potent competitive advantage and recommend what attention-deprived companies should do to avoid losing employees, customers, and market share. A landmark work on the twenty-first century's new critical competency, this book is for every manager who wants to learn how to earn and spend the new currency of business.
Tags: Customer Experience, Management, Future of Work
Knowledge Management Case Book: Siemens Best Practises
June 10, 2002
This book provides a perspective on knowledge management at Siemens - an internationally recognised benchmark - by presenting the reader with the best of the corporation's practical applications and experiences. Tom Davenport and Gilbert Probst bring together instructive case studies from different areas that reflect the rich insights gained from years of experience in practising knowledge management.
Most of the cases have been updated for the second edition. New cases have been added.
The Knowledge Management Case Book provides a comprehensive account of how organisational knowledge assets can be managed effectively. Specific emphasis is given to the development of generic lessons that can be learned from Siemens' experience. The book also offers a roadmap to building a "mature knowledge enterprise", thereby enhancing our understanding of the steps that need to be taken in order to sustain competitive dominance in the knowledge economy.
Presenting applications from very different areas, this practice-orientated book is really outstanding in the broad field of KM literature.
Harvard Business Review Press
May 01, 2000
This influential book establishes the enduring vocabulary and concepts in the burgeoning field of knowledge management. It serves as the hands-on resource of choice for companies that recognize knowledge as the only sustainable source of competitive advantage going forward.
Drawing from their work with more than thirty knowledge-rich firms, Davenport and Prusak--experienced consultants with a track record of success--examine how all types of companies can effectively understand, analyze, measure, and manage their intellectual assets, turning corporate wisdom into market value. They categorize knowledge work into four sequential activities--accessing, generating, embedding, and transferring--and look at the key skills, techniques, and processes of each. While they present a practical approach to cataloging and storing knowledge so that employees can easily leverage it throughout the firm, the authors caution readers on the limits of communications and information technology in managing intellectual capital.
Mission Critical: Realizing the Promise of Enterprise Systems
Harvard Business Review Press
February 01, 2000
This is a no-nonsense guide to the benefits and pitfalls of enterprise-wide information systems. How many organizations would doubt the promise of an integrated enterprise system (ES)? Not many, judging by a $15 billion industry. The combination of an ES as a platform for organizational information and Internet technology for gaining access to it adds up to the ideal solution for company-wide data sharing in real time. Not surprisingly, small and large companies worldwide are either considering an ES, in the process of implementing one, or living with the results. Yet, says Tom Davenport, unless managers view ES adoption and implementation as a business decision rather than a technology decision, they may be risking disappointment Mission Critical presents an authoritative and no-nonsense view of the ES opportunities and challenges. Suggesting ESs are not the right choice for every company, the author provides a set of guidelines to help managers evaluate the benefits and risks for their organizations. To be successful, argues Davenport, an organization must make simultaneous changes in its information systems, its business processes, and its business strategy. Such changes are described in detail with extensive examples from real organizations. Bolstering his contention that ESs should be viewed as business vs. technology projects, Davenport spells out the specific business change objectives that should be formulated in advance of ES adoption and monitored throughout its implementation. The first strategic guide to the ES decision, Mission Critical will be indispensable to general managers and information technology specialists at all stages of the implementation process.
Tags: Emerging Technology, Management, Business Strategy
Mastering Information Management
January 01, 2000
Davenport and Marchand edited this book of short pieces by many leading authorities on information management. Part of the Financial Times’ “Mastering” series, it contains highly readable and usable lessons on this most important topic.
Tags: Emerging Technology, Management, Business Strategy
Information Ecology: Mastering the Information and Knowledge Environment
Oxford University Press
June 26, 1997
According to virtually every business writer, we are in the midst of a new "information age," one that will revolutionize how workers work, how companies compete, perhaps even how thinkers think. And it is certainly true that Information Technology has become a giant industry. In America, more
that 50% of all capital spending goes into IT, accounting for more than a third of the growth of the entire American economy in the last four years. Over the last decade, IT spending in the U.S. is estimated at 3 trillion dollars. And yet, by almost all accounts, IT hasn't worked all that well. Why
is it that so many of the companies that have invested in these costly new technologies never saw the returns they had hoped for? And why do workers, even CEOs, find it so hard to adjust to new IT systems?
In Information Ecology, Thomas Davenport proposes a revolutionary new way to look at information management, one that takes into account the total information environment within an organization. Arguing that the information that comes from computer systems may be considerably less valuable to
managers than information that flows in from a variety of other sources, the author describes an approach that encompasses the company's entire information environment, the management of which he calls information ecology. Only when organizations are able to combine and integrate these diverse
sources of information, and to take them to a higher level where information becomes knowledge, will they realize the full power of their information ecology. Thus, the author puts people, not technology, at the center of the information world. Information and knowledge are human creations, he
points out, and we will never excel at managing them until we give people a primary role. Citing examples drawn from his own extensive research and consulting including such major firms as A.T. & T., American Express, Ford, General Electric, Hallmark, Hoffman La Roche, IBM, Polaroid, Pacific Bell,
and Toshiba Davenport illuminates the critical components of information ecology, and at every step along the way, he provides a quick assessment survey for managers to see how their organization measures up. He discusses the importance of developing an overall strategy for information use; explores
the infighting, jealousy over resources, and political battles that can frustrate information sharing; underscores the importance of looking at how people really use information (how they search for it, modify it, share it, hoard it, and even ignore it) and the kinds of information they want;
describes the ideal information staff, who not only store and retrive information, but also prune, provide context, enhance style, and choose the right presentation medium (in an age of work overload, vital information must be presented compellingly so the appropriate people recognize and use it);
examines how information management should be done on a day to day basis; and presents several alternatives to the machine engineering approach to structuring and modeling information. Davenport makes explicit what many managers already know in their gut: that useful information flow depends
on people, not equipment. In Information Ecology he paves the way for all managers to build a more competitive, creative, practical information environment for their companies.
Process Innovation: Reengineering Work Through Information Technology
Harvard Business Review Press
October 01, 1992
The business environment of the 1990s demands significant changes in the way we do business. Simply formulating strategy is no longer sufficient; we must also design the processes to implement it effectively. The key to change is process innovation, a revolutionary new approach that fuses information technology and human resource management to improve business performance. The cornerstone to process innovation's dramatic results is information technology--a largely untapped resource, but a crucial "enabler" of process innovation. In turn, only a challenge like process innovation affords maximum use of information technology's potential. Davenport provides numerous examples of firms that have succeeded or failed in combining business change and technology initiatives. He also highlights the roles of new organizational structures and human resource programs in developing process innovation. Process innovation is quickly becoming the byword for industries ready to pull their companies out of modest growth patterns and compete effectively in the world marketplace.
Analytics Hall of Fame
March 22, 2019
This leader has transformed the practice of analytics or another Analytics Hall of Fame discipline by founding, or transforming, a successful global company or large division within a global company. This leader’s reputation and ideas are known globally.
This leader is a recognized authority in an Analytics Hall of Fame discipline as evidenced by one or more of the following:
- Serves as a distinguished professor at a college or university
- Achieved a Ph.D. in an Analytics Hall of Fame discipline or related area
- Authored books that have impacted the field
- Published at least twelve (12) journal articles and is a heavily cited authority
- Received at least one (1) honorary doctoral degree
Tags: Management, Future of Work, Business Strategy
The AI Advantage How to Put the AI Revolution to Work
December 10, 2018
Everywhere you look, people are talking about the revolutionary power of AI to transform their industry. But that begs the question - how do you put the AI revolution to work? Join this session with analytics guru and "The AI Advantage" author Tom Davenport to learn how you can get ahead with AI today.
The Cognitive Company: Incremental Present, Transformational Future
June 13, 2017
Cognitive technologies undoubtedly have the potential to transform knowledge-based work. However, in the present, highly ambitious cognitive projects have encountered obstacles and delays, even when substantial resources have been committed to them. It’s important, then, for organizations to proceed incrementally toward the dramatic changes that cognitive technologies and capabilities will eventually enable. Based on a review of over 100 organizations’ attempts to implement some form of cognitive technology, this TED-type talk will describe major areas of cognitive activity likely to be transformed and prescribe steps that most organizations should take today to becoming a “cognitive company.”
Prof. Tom Davenport (@tdav), Distinguished Professor at Babson College, Fellow at MIT Initiative on the Digital Economy
Analytics 3.0 And Beyond: From Ad Hoc Insights To Automated Decisions
May 01, 2014
Many companies are excited about the possibility of competitive advantage from analytics on big data, but many don’t understand how to take full advantage of this resource, or how to integrate it with their existing analytical activities. In this session, Tom Davenport will describe what organizations are attempting to accomplish with big data analytics, and how companies can assemble the necessary capabilities and blend them with those for traditional analytics. Several leading examples of companies—large firms and startup—that are aggressively integrating big and small data will be presented. Professor Davenport will also describe a framework he has developed called “Analytics 3.0,” which involves analytics at speed and scale for the data economy. Finally, he’ll provide a peek into the likely attributes of Analytics 4.0, which will involve automated, interconnected decision-making in many different business domains.
Analytics 3.0: Big Data and Small Data in Big and Small Companies
September 18, 2013
UC Berkeley School of Education Dean's Lecture
Speaker: Thomas H. Davenport
Wednesday, September 18, 2013
Many companies and observers are excited about the possibility of competitive advantage from analytics on "big data," but many don't understand the differences between big and small data analytics. There are also substantial differences in how large, established organizations and startups approach big data. In this presentation, Tom Davenport will describe what organizations are attempting to accomplish with big data. Several leading examples of companies—large firms and startup—that are aggressively pursuing big data will be presented. Davenport will then describe how big data differs from previous approaches to analytics and data management on small data. Finally, he'll address some of the key factors that big and small data analytics have in common, and will describe his ideas on their integration using the "Analytics 3.0" framework he has developed.
Successful Business Analytics by Tom Davenport - Part II
May 22, 2012
http://online-behavior presents Part II of Successful Business Analytics , Thomas Davenport discusses the importance of relationships for Analytics: Analytics people have to work with a whole variety of organizations.
Tom also addresses the organizational culture and business leadership required to make the most of the science of analysis, and shares stories of people who have made this transition and the resulting competitive edge their organizations exploit.
Watch Successful Business Analytics Part I
Watch an interview with Tom Davenport http://www.youtube.com/watch?v=CStxyj...
Successful Business Analytics by Tom Davenport Part I
May 16, 2012
http://online-behavior.com presents Thomas Davenport from the eMetrics Marketing Optimization Summit San Francisco 2011.
Tom Davenport starts by discussing the different type of people involved in this process: Web Analysts, Business Intelligence, Conversion Optimizers, HR Analysts, and others. He also provides examples on which companies and professions are embracing analytics.
Following, we learn about a research he made where company executives were interviewed on how they make decisions and how they improve decision-making on their companies. From the techniques described, the ones that seem to stand out are the use Analytics for planning and learning from error.
AI in the Enterprise: Management and Business Review
October 01, 2020
Artificial intelligence is the most important new technology of the age, but it comes in many varieties, and businesses face a range of challenges in effectively deploying it throughout their organizations. Tom Davenport takes a pragmatic but positive approach to AI’s longterm potential, describing effective approaches
to creating and implementing a strategy for this transformative technology.
Tom Davenport: AI & New Emerging Business Models | Future of Work Pioneers Podcast #10
July 28, 2020
This conversation is part of the Future of Work Pioneers Podcast. Welcome to the Future of Work Pioneers podcast. Today, we are speaking with Tom Davenport, the President's Distinguished Professor of Information Technology and Management at Babson College, co-founder of the International Institute for Analytics, Fellow at the MIT Initiative on the Digital Economy, and Senior Advisor to Deloitte Analytics. He teaches analytics in executive programs at Babson, Harvard Business School Harvard School of Public Health, and MIT Sloan School.
Tom pioneered the concept of competing on analytics in 2007. Having authored some 20 books and 200 articles, his most recent book is The AI Advantage: How to Put the Artificial Intelligence Revolution to Work.
ROI in AI: Achieving Value and Maximizing Return
HARVARD ALUMNI ENTREPRENEURS INVITES
July 13, 2020
There’s no question that artificial intelligence has been a key driver of innovation over the past decade, garnering the interest – and dollars- of business the world over. To date, however, a majority of businesses claim limited success from the implementation of AI. With a recessionary economic context before us, more companies will seek clearer returns for those investments. Tom discusses how he sees this next phase evolving for AI and discusses what is holding it back from delivering stronger gains for firms.
The Future of Artificial Intelligence - with Professor Tom Davenport
June 17, 2020
In this live stream, I will be joined by Thomas H. Davenport, who 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 is also the author of 20 books and many articles in Harvard Business Review and Sloan Management Review.
We will be taking a look at the future of AI, the impact of the global pandemic, as well as the key tips to deliver successful AI projects in the future
026 – Why Tom Davenport Gives a 2 out of 10 Score To the Data Science and Analytics Industry for Value Creation
Designing for Analytics
November 19, 2019
Tom Davenport has literally written the book on analytics. Actually, several of them, to be precise. Over the course of his career, Tom has established himself as the authority on analytics and how their role in the modern organization has evolved in recent years. Tom is a distinguished professor at Babson College, a research fellow at the MIT Initiative on the Digital Economy, and a senior advisor at Deloitte Analytics. The discussion was timely as Tom had just written an article about a financial services company that had trained its employees on human-centered design so that they could ensure any use of AI would be customer-driven and valuable.
AI & the Future of Work
November 05, 2019
In this episode of The ConversAItion, Jim speaks with a renowned expert on digital business, Tom Davenport, about everything from the fears of job displacement to employability in an AI-driven world. A prolific author, senior advisor to Deloitte Analytics and the President's Distinguished Professor of Information Technology and Management at Babson College.
The Artificial Intelligence Revolution (w/ Tom Davenport)
August 08, 2019
Tom Davenport is a 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 has written or edited twenty books including The AI Advantage and over 250 print or digital articles for Harvard Business Review (HBR), Sloan Management Review, the Financial Times, and many other publications. He earned his Ph.D. from Harvard University and has taught at the Harvard Business School and the University of Chicago.
Putting the artificial intelligence revolution to work
January 16, 2019
The first author we had the pleasure to speak with in the #HighOnData series is Tom Davenport, a widely known and accomplished professional in the analytics field. Davenport is the co-founder of the International Institute for Analytics, a Fellow of the MIT Initiative on the Digital Economy, and a Senior Advisor to Deloitte Analytics, as well as a visiting professor at Harvard and MIT. Tom shared some of his thoughts behind his recent work The AI Advantage: How to Put the Artificial Intelligence Revolution to Work, discussing how companies can use artificial intelligence in a practical manner to advance their business and gain a competitive advantage.
Putting Artificial Intelligence to Work
January 07, 2019
Our guest this week is Thomas H. Davenport. He’s a world-renowned thought leader and author, and is the president’s distinguished professor of information technology and management at Babson College, a fellow of the MIT Center for Digital Business, and an independent senior advisor to Deloitte Analytics.
Tom Davenport is author and co-author of 15 books and more than 100 articles. He helps organizations to revitalize their management practices in areas such as analytics, information and knowledge management, process management, and enterprise systems. His most recent book is “The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge).”
Tom Davenport - The AI Advantage
November 26, 2018
Humans of Data Science (HoDS) project - showing the human-side of data science!
Watch the video to learn more about Tom’s most recent book “The AI Advantage”. Tom is a world-renowned thought leader and author (with over 20+ books and 100+ articles published). He helps organizations to revitalize their management practices in areas such as analytics, information and knowledge management, process management, and enterprise systems.
Link to the AI Advantage: https://mitpress.mit.edu/books/ai-adv...
Episode 12: Being an AI-Driven Leader
AI at Work
September 06, 2018
Hosts Rob May and Brooke Torres interview Tom Davenport, President’s Distinguished Professor of Information Technology and Management at Babson Collegea, Fellow of the MIT Center for Digital Business, and an independent senior advisor to Deloitte Analytics. Tune in to learn what it means to be an AI-driven leader.
Cómo las pymes pueden sacar partido al 'big data' | Tom Davenport
August 17, 2017
Nos pide que le llamemos simplemente Tom con la misma llaneza que explica su punto de vista cercano y accesible sobre el temido 'big data'. Es un término que no le gusta "porque solo indica que hay una gran cantidad de datos", y él prefiere centrarse en cómo sacar partido a esa montaña de información que recoge, voluntaria e involuntariamente, todo tipo de empresas.
De hecho, su afán principal en esta entrevista (y, en general, en sus conferencias divulgativas) es dar a conocer que el tamaño de las empresas ya no es una barrera para acceder a las ventajas del 'big data'. Davenport invita a los empresarios de pymes y autónomos a comprobar lo barato que es ya contratar "un pequeño paquete de potencia de cálculo en la nube" para recopilar y tratar los datos que se recogen, por ejemplo, en las webs de estas empresas. Del mismo modo que es muy accesible el hacer un análisis profundo de esos datos y que nos ayude a tomar decisiones.
Tom Davenport on mitigating AI’s impact on jobs and business
February 09, 2017
This week, I sit down with Tom Davenport. Davenport is a professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a fellow at the MIT Center for Digital Business, and a senior advisor for Deloitte Analytics. He also pioneered the concept of “competing on analytics.” We talk about how his ideas have evolved since writing the seminal work on that topic, Competing on Analytics: The New Science of Winning; his new book Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, which looks at how AI is impacting businesses; and we talk more broadly about how AI is impacting society and what we need to do to keep ourselves on a utopian path.
The Rise of Automation’s Effect on the U.S. Job Market
December 02, 2016
Martin Ford, author of “The Rise of the Robots,” and Tom Davenport, author of “Only Humans Need Apply,” discuss the increase of machines in the workplace and its impact on jobs in the United States. They speak with Bloomberg's Emily Chang on "Bloomberg Technology." (Source: Bloomberg)
Tom Davenport On Avoiding Obsolescence in an Automated Age
September 05, 2016
Smart machines are coming, so what are we doing about it?
Instead of cowering in fear, what if we took a proactive approach? What if there were a playbook we could use to anticipate and thrive in an increasingly automated world?
In his book, Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, Thomas Davenport, offers ways to accomplish that goal. His book is a guide for employees and students who want to know what they can do to work successfully with smart machines.
How collaborative robots (or "Cobots") might soon be your workmates. We visit the Innorobo exhibition in Paris to see the latest models. And Tom Davenport, co-author of new book "Only Humans Need Apply" on how jobs will change in a robotic future. Plus, Twitter CEO Jack Dorsey on how he plans to make his company regain its popularity.
Will Machines Take Your Job?
Smart People Podcast
May 17, 2016
This week we speak with Tom Davenport as we discuss these issues and his new book, Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. You will hear how Tom actually reframes the conversation about automation, arguing that the future of increased productivity and business success isn’t either human or machine. It’s both. The key is augmentation, utilizing technology to help humans work better, smarter, and faster. Instead of viewing these machines as competitive interlopers, we can see them as partners and collaborators in creative problem solving as we move into the next era. The choice is ours.
a16z Podcast: Automation, Jobs, & the Future of Work (and Income)
May 03, 2016
There's no question automation is taking over more and more aspects of work and some jobs altogether. But we're now entering a "third era" of automation, one which went from taking over dangerous work to dull work and now decision-making work, too.
So what will it take to deal with a world -- and a workplace -- where machines could be thought of as colleagues? The key lies in distinguishing between automation vs. augmentation, argue the guests on this episode of the a16z Podcast, IT management professor Thomas Davenport and Harvard Business editor Julia Kirby, who authored the new book Only Humans Need Apply: Winners and Losers in the Age of Smart Machines.
But the argument isn't as simple as saying humans will just do the creative, emotionally intelligent work and that machines will do the rest. The future of work is complex and closely tied to the need for structure, identity, and meaning. Which is also why linking the discussion of things like "universal basic income" to the topic of automation isn't just unnecessary, but depressing and even damaging (or so argue the guests on this episode).
“Beyond Big Data: From Analytics to Cognition” – An Interview with Thomas Davenport
The Marketing Journal
January 15, 2016
Thomas H. Davenport is a Distinguished Professor at Babson College, a Research Fellow at the MIT Center for Digital Business, Director of Research at the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics.
Tom Davenport's Guide to Big Data
March 03, 2014
Big Data at Work: Dispelling the Myths, Uncovering the Opportunities, is a new book from Tom Davenport, a veteran observer of the data analysis scene. It’s a required reading for managers that need a straightforward, hype-free introduction to big data, a clear and clarifying “signal” in the incredible noise around the confusing and mislabeled term. If Viktor Mayer-Schönberger’s and Kenneth Cukier’s book was last year’s definitive text on the subject for general audiences, Big Data at Work is the 2014 definitive guide to starting and managing the big data journey in small and large organizations.
Teaching business poets and quants to make nice
June 26, 2013
FORTUNE — Let’s say you’ve got a crucial strategic decision to make, and a team of analysts has painstakingly built a complex mathematical model that’s supposed to show you which way to go. The trouble is, even after the data scientists have laid out the details of their statistical algorithm in what they think are simple terms, it’s Greek to you.
Why the Airline Industry Needs Another Data Revolution
The New York Times
June 26, 2013
Over the years, airline travel has been a prime testbed for advanced computing and data tools. In the late 1950s and 1960s, American Airlines and I.B.M. teamed up to develop the Sabre computerized reservations system, perhaps the most impressive private-sector computer system of its day.
In Conversation with Tom Davenport, Harvard Business Professor
January 03, 2013
Tom Davenport (Professor, Harvard University) spoke at Trend Spotting: CMA Ontario's Winter Conference in Toronto, December 12-13, 2012.
In this exclusive interview, he answers questions on overcoming managerial reluctance in the face of digital change, how to integrate analytics into business, how to capitalize on mined data, and much more!
The three '..tives' of business analytics; predictive, prescriptive and descriptive
November 16, 2012
There are major changes afoot in the world of analytics as the familiar concept of business analytics yields to the less familiar world of predictive analytics. As it turns out, predictive analytics holds the key to unlocking the business value of Big Data, as the foremost analytics authority, Harvard Business School visiting professor Tom Davenport, reveals.
Are You Ready to Reengineer Your Decision Making?
October 01, 2010
There has been enormous progress in embedding the use of analytics at lower levels of companies. But according to Thomas H. Davenport, professor at Babson College and one of the best-known thinkers about analytics and business intelligence, the upper levels of companies haven’t kept up.
Tom Davenport and Andy McAfee, June 2008
The Story for Information
September 02, 2010
On June 18, 2007, at the Enterprise 2.0 Conference in Boston, Andrew McAfee, who coined the term in 2006, debated the merits of Enterprise 2.0 with Tom Davenport. Jason Rubin and Gil Press revisited the debate with them a year later at Tom’s office in Babson College.
How to Integrate AI into your Organization
January 01, 2019
No, artificial intelligence is not going to work miracles (it won’t find the cure for
cancer, rationalize stock market speculation or make car accidents go away).
However, it might allow you to optimize your processes, better understand
your clients, improve your products, and expand your skills. Here are a few
suggestions for how to concretely utilize the potential of AI.
Based on The AI Advantage by Thomas H.Davenport
(The MIT Press, 2018)
How to unleash data science to become a model-driven business
Domino Data Lab
August 11, 2021
Hosted by Domino Data Lab and distinguished speaker, author, and advisor, Tom Davenport - one of Harvard Business Review’s most frequently published authors - this live panel discussion will explore why many of the world’s most sophisticated companies struggle to deliver data science at scale.
Join us to hear first-hand from experts studying the challenges impacting the best efforts to become model-driven, leaders at enterprises successfully overcoming them with enterprise MLOps, and learn proven methods to put models at the heart of your business.
Tom Davenport, Babson College | MIT CDOIQ 2019
July 31, 2019
Tom Davenport joins theCUBE hosts Dave Vellante (@dvellante) and Paul Gillin (@pgillin) live from MIT CDOIQ 2019
Are humans and machines on a collision course? A futurist examines our uneasy dance with automation
The next time a McDonald’s Corp. customer is asked if they want fries with their order, the questioner may not be a real person.
The fast-food giant has been testing voice-recognition software at one of its locations in Chicago. And those fries may soon be robot-cooked as well. McDonald’s is piloting the use of robots to toss menu items into deep fat fryers and serve them up.
2014 Big Data, Analytics, and Insights
June 05, 2014
Big Data, Analytics, and Insights
Prof. Tom Davenport, MIT Center for Digital Business moderator
Barry Morris, NuoDB
Darrell Fernandes, Fidelity Investments
Don Taylor, Benefitfocus
Puneet Batra, LevelTrigger
Many organizations are excited about the possibility of developing a competitive advantage from the use of advanced analytics on "big data". In this session a panel of experts who will address their concept of big data and what their organizations are attempting to accomplish with it. They will also discuss the role of the data scientist in extracting value from that big data using advanced analytics tools and techniques. Examples will be presented from firms that are aggressively pursuing big data initiatives for predicting or optimizing future outcomes. The panelists will describe how using big data sets for analytics and data management differs from previous approaches utilizing small data sets. Finally, the panel will address key factors that big and small data analytics have in common.
The Business Value of Digital Workflows | Workflow Quarterly
March 29, 2019
New data reported by IT expert Tom Davenport reveals how changing the employee, client and IT experience with technology makes work better. Learn more in The Business Value Issue of Workflow Quarterly: https://workflow.servicenow.com/Quart...
QUT Real World Futures | Disruptive Influences Conference: Professor Tom Davenport
November 04, 2016
Learn more about QUT's Real World Futures program: http://bit.ly/2agCrAT
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 on 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 co-authored Only Humans Need Apply, Winners and Losers in the Age of Smart Machines.
10 Observations on Big Data in Late 2015 - Tom Davenport
November 18, 2015
Business analytics has become an invaluable tool in every industry. This issue of Babson Insight looks at the evolving uses of big data in the business world along with how your organization can learn to make the most out of big data.
Teradata's Bill Franks & Babson College's Thomas H. Davenport: Becoming Data Driven
August 06, 2015
Becoming Data-Driven 101: Planning for Success:
In an era where the term Big Data has become ubiquitous, and many organizations are still struggling to ensure they have the right strategy in place, a few have managed to transform their business by simply making data and analytics strategic assets.
Attend this session to hear from Thomas Davenport, President’s Distinguished Professor in Management and Information Technology at Babson College and Bill Franks, Chief Analytics Officer for Teradata as they discuss the meaning of “being data driven”, the benefits of becoming a data-driven business and the planning for success in this ever-changing data driven business environment.
Tom Davenport | HP Big Data Conference 2014
August 13, 2014
Tom Davenport, Author and Big Data Visionary, at HP Big Data Conference 2014 with John Furrier and Dave Vellante
With a background in sociology, Tom Davenport, a Distinguished Professor in Management and Information Technology at Babson College and author of 19 books on management practices and analytics, thinks about technology in terms of what it means for humans. At the Hewlett-Packard (HP) Vertica Big Data Conference this week, he joined theCUBE’s John Furrier and Dave Vellante and talked about Big Data and social behavior. He offered some interesting examples and insights as to how Big Data affects social behaviors today, and how analytics could be used in the future.
Fuel and navigate organizational change
October 12, 2021
A thought-provoking conversation with Tom Davenport on how to fuel and navigate organizational change
Integrating digital technology into all areas of a business is an ongoing process of changing the way you do business. It requires foundational investments in skills, projects, infrastructure, and often, new or rebuilt IT systems.
Overcoming cultural challenges was important to IT leaders prior to 2021, but in the wake of global disruption, organizations are now forced to rethink their traditional strategies in order to adapt and survive.
An open approach to leadership means building an organization that can thrive, even during the most turbulent times. Leaders must weave values, principles, and norms into the fabric of their organizations to ensure people remain aligned, unified, engaged, and empowered. But with the future rapidly changing, how are IT executives supposed to plan for the unknown?
Join Tom Davenport, world-renowned thought leader and author at the forefront of digital innovation, to discuss his perspectives and best practices on how to build a culture that can be a powerful force for innovation. Speaking alongside Tom is Michael Walker, Red Hat’s Global Head of Open Innovation Labs and Transformation Services.
Tags: Digital Transformation, Innovation, Leadership
How to Lead a Data-Driven Culture
June 24, 2020
Businesses say they want to make more effective use of data, analytics, and AI, but many are not making progress. A survey of U.S. executives found that 63% do not believe their companies are analytics driven. Other research found that in 2019 only 31% of large U.S. firms said they were data-driven compared to 37% in 2017; some companies are clearly regressing.
At a time when making analytical decisions is so important, why are companies struggling?
Join Tom Davenport — one of the world’s foremost experts on analytics — for an interactive HBR webinar on how senior executives can create a data-driven culture in their organizations.
The Data & Analytics Essentials Sprint
February 08, 2022
Principles of Data and Analytics
Professor Tom Davenport and PayPal’s Head of Global Analytics Jon Francis teach you the essentials of turning data into useful, actionable insights for your team and organization.
February 21 - March 8, 2022
2-week sprint plus Section4 Membership — $995
KDD 2020 - Tom Davenport - Beyond Data Science Unicorns
September 16, 2020
Tom Davenport's speech titled "Beyond Unicorns: Educating, Classifying, and Certifying Business Data Scientists?" at KDD 2020 Conference. This speech was part of the IADSS' 2nd Workshop on Data Science Standards – What do you need to know as a Data Scientist? Training Data Scientists of the Future.