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Cognitive applications: Home runs versus base hits

by Tom Davenport
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    29 January 2016

    Cognitive applications: Home runs versus base hits

    30 January 2016
    • Tom Davenport United States
    • Tom Davenport United States
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    Some companies are aiming at dramatic results such as finding a cure for cancer using cognitive applications, while others are focusing on more prosaic areas such as billing. What's the correct approach?

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    Some organizations, in building applications of cognitive computing, try to hit a “home run”—a technically demanding and organizationally difficult project of major ambition. These organizations believe that cognitive technology is path-breaking, so they try to accomplish breakthrough objectives with it. Two prominent examples include Memorial Sloan Kettering Center’s and M.D. Anderson Cancer Center’s attempts to address the treatment of oncology with IBM’s Watson. M.D. Anderson actually calls its Watson project a “moon shot.” Curing cancer may be right up there with reaching the moon in the level of ambition. So the term is apt.

    In pharmaceuticals, Johnson & Johnson and Sanofi are pursuing home runs in the form of new drug development. They hope to use Watson to develop drugs much faster and without too much intervention by human scientists. In the veterinary sector, LifeLearn, a Canadian company, is pursuing an ambitious project to use Watson to transform veterinary treatment. Outside of health care, firms like Swiss Re in insurance underwriting and law firms like Dentons and Latham & Watkins are using Watson and other cognitive technologies to transform some of their key business processes. All of these would qualify as attempts to “swing for the fences” in their particular business domains.

    But cognitive technologies don’t have to aim for the fences; they can power more prosaic (and easier-to-reach) destinations. M.D. Anderson Cancer Center is reaching for a home run with its oncology treatment project, but it is also trying to get solid base hits with several other projects. For example, it’s using cognitive technology from Cognitive Scale to power a “care concierge” with specific patient recommendations. The organization is employing the same technology to determine which patient bills are most likely to be at risk of nonpayment, to build a “cognitive help desk” for key enterprise applications, and to develop a wide variety of other applications. Chris Belmont, the organization’s chief information officer, and his team have already identified more than 60 use cases for cognitive applications, and he expects many more.1

    Base hits with cognitive computing are being pursued in several other industries as well. Several retailers are using the technology to do a better job of recommending appropriate products to customers, for example. Companies with extensive supply chains are using cognitive tools to evaluate unstructured data about key suppliers. Firms with complex enterprise systems are using cognitive applications that digest reams of documentation and answer employees’ technical questions in the field.

    So which should you strive for—a home run or a base hit? As in baseball, each approach to cognitive technology has its advantages and disadvantages. Large, ambitious projects are difficult and time-consuming. Memorial Sloan Kettering began to work with IBM Watson to capture and deploy oncology expertise in 2012, and it’s still working on that project in 2016.2 M.D. Anderson raised $50 million in funds to support the expenses of Watson technology and associated organizational changes to train and deploy it effectively.3 We don’t know the exact level of technical risk in these applications—the parties involved are confident that these projects will succeed—but the level of organizational and cultural risk certainly seems high. What if doctors simply decide not to use the cognitive system for diagnosis or treatment recommendations?

    The upside of the big swing for a cognitive home run, of course, is that it gets a lot of attention both inside and outside the organization. If you want to mobilize people inside and outside your organization to get behind a goal, you need a project with a stirring outcome. If you want to be perceived as a world leader in the application of technology, home runs are called for. There are many more people who know the name Babe Ruth (third in career home runs) than those who are familiar with Eddie Collins (third in career singles), who played at about the same time as Ruth.

    Base hits with cognitive technology involve lower rewards and lower risk. Some of the less ambitious projects I have mentioned have been prototyped within a few weeks, and fully developed in a few months. Because many of the functions they employ (recommendations, for example) have been understood and used for a while, the fact that they are often done better by cognitive technologies doesn’t create a lot of organizational resistance. Because they don’t typically involve a huge investment, you probably won’t get fired if they don’t yield the level of ROI you mentioned in your financing proposal.

    Of course, many organizations will want some of both—a portfolio of cognitive projects with various levels of project expense, risk, and reward. The specific mix of base-hit and home-run attempts will vary by an organization’s strategy and situation. Memorial Sloan Kettering and M.D. Anderson, for example, both are already, and plan to continue to be, world-leading organizations in cancer care. It wouldn’t do for other institutions to get all the credit for a cognitive application that helps treat cancer.

    I suspect that most organizations, however, will simply want to use cognitive technologies to solve business problems and provide some degree of value to customers. There are almost 200 countries in the world, for example, and most of them did not feel the need to send rockets to the moon. Cognitive technologies will likely succeed or fail based not on the outcome of a few dramatic home-run swings, but on whether their organizations get on base with reasonable frequency.

    Credits

    Written by: Tom Davenport

    Endnotes
      1. Chris Belmont (of M.D. Anderson), interviews with author, September and October 2015. View in article
      2. Dr. Mark Kris (leader of the Memorial Sloan Kettering Watson project), interviews with author, June and July 2015. View in article
      3. Ariana Eunjung Cha, “Watson’s next feat? Taking on cancer,” Washington Post, June 27, 2015, http://www.washingtonpost.com/sf/national/2015/06/27/watsons-next-feat-taking-on-cancer/. View in article
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    Cognitive technologies , Emerging technologies

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    Tom Davenport

    Tom Davenport

    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 Center for Digital Business. He is an independent senior advisor to Deloitte Analytics, Deloitte Consulting LLP. He collaborates with Deloitte thought leaders on all things related to business analytics, from the potential of cognitive technologies to industry-focused explorations and outcomes. Covering topics from emerging technologies to innovative business applications, Tom's Deloitte University Press series reveals leading-edge thinking on analytics and cognitive technology. Connect with Tom on LinkedIn and Twitter. 

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