By Thomas H. Davenport, May 25, 2016
Perhaps the most important leadership issue is preparing your employees for roles in which they augment smart machines, and vice-versa. There will be new jobs involving implementation and oversight of these technologies—getting them installed, monitoring their daily performance, and improving them over time. Employees with some aptitude need to be groomed for such roles.
By Thomas H. Davenport, May 11, 2016
Many people and companies seem to think of “cognitive computing” as a separate area from analytics. Most large organizations today have significant analytical initiatives underway, but they think of the cognitive space as being an exotic science project. One executive told me, “We have no desire to win Jeopardy,” an allusion of course to the IBM Watson project from 2011. But cognitive computing is not just about Watson, and it’s not an exotic science project.
By Thomas H. Davenport, Feb 18, 2016
You may feel that “business first” is an obvious approach to take with analytics, but I assure you that it is anything but ubiquitous. It means that business objectives drive the business domain to which analytics are applied (what I have usually called “targets”), there are business objectives in place before the analytics are generated, and business considerations constrain the time and expense that are devoted to the analytical exercise. That may sound less fun than analysts running wild in an analytical sandbox, but it is generally the most effective and efficient approach to analytics.
By Thomas H. Davenport, Jan 25, 2016
One common element of these types of jobs is that they are important to their organizations. Big new “Chief” roles aren’t established from scratch without reason.
By Thomas H. Davenport, Dec 31, 2015
If the 3.0 version of analytics and automation involves widespread use of them within organizations, 4.0 is about their application across pervasive, automated networks. Every business and organization in this world will be tied together with ubiquitous communications, apps, sensor networks, and APIs.
By Thomas H. Davenport, Dec 24, 2015
In principle, the ultimate degree of efficiency comes when no human intervention is required. However, uncertainties in the data results in a process that often cannot be fully automated, but can be significantly augmented.
By Thomas H. Davenport, Daniel Magestro, Robert Morison, Dec 22, 2015
Available to Research & Advisory Network Clients and Professional Members
In addition to predictions, we’ve done an extensive review of the pressing themes we see organizations facing today. Our annual Chief Analytics Officer Summit, held in October, provided additional perspective of key priorities for leaders as they navigate the many aspects of elevating analytics capabilities. Therefore, this year we’ve included five priorities to complement our predictions for the year ahead.
By Thomas H. Davenport, Dec 08, 2015
IBM’s Watson is one of the most appealing new technologies of the 21st century, and the most prominent example of the new category of “cognitive computing.” It burst upon the scene with a dramatic Jeopardy! win in 2011, and has now been adopted by a variety of business and health care organizations since then.
By Thomas H. Davenport, Nov 10, 2015
The law is a profession based on rules, procedures, evidence, and precedent. It turns out that intelligent technologies are increasingly able to codify these decision criteria into automated and semi-automated systems.
By Thomas H. Davenport, Oct 13, 2015
While marketing automation will lead to some difficult changes in the nature and work of the function, it offers much potential for value. It can lead to better and more reliable decisions about how best to spend scarce marketing resources, and can lead to closer customer relationships that build brand equity and improve financial outcomes. For those marketers who can embrace the technology and the changes it brings, it will also lead to some exciting careers.