Who Owns Your Data Exhaust?

By Thomas H. Davenport, Aug 07, 2014

More than twenty years ago, consultants Stan Davis and Bill Davidson, in the book 2020 Vision, argued that a company’s “information exhaust” (information byproducts gathered in the course of its normal business) could be used to “informationalize” a business (develop products and services based on information) and turbocharge its performance. Their primary examples of this phenomenon were information companies—Quotron, TV Guide, TRW, and the like. They did argue, however, that any company in any industry had the potential to be informationalized by its data exhaust.

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Dueling Schooling on Big Data and Analytics

By Thomas H. Davenport, Jul 22, 2014

There’s been a lot of discussion about the shortage of quantitative analysts and data scientists in this world, and many people wonder where they will all come from. Today I have good news and bad news for you. The good news is that there are a rapidly growing number of educational institutions that are offering courses, concentrations, and degree programs in analytics and big data.

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The Analytics of Things

By Thomas H. Davenport, Jul 07, 2014

The press and blogosphere are full of references to “The Internet of Things” (TIoT) or even “The Internet of Everything.” It’s great to connect inanimate objects to the Internet, of course. But that’s only a first step in terms of doing something useful with all those connected devices. “The Analytics of Things” are just as important, if not more so.

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Is There a Leadership Vacuum for Big Data?

By Thomas H. Davenport, Jun 03, 2014

If big data and analytics are the powerful business resource that I think they are, they need someone to champion and oversee their usage in organizations. The problem is that many organizations don’t really have someone in charge of these capabilities. There is in many companies a leadership vacuum for big data and analytics.

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Analytics in Sports: The New Science of Winning

By Thomas H. Davenport, Apr 01, 2014

Available to ERS Clients only

Many industries today are adopting more analytical approaches to decision-making. However, no other industry has the same types of analytical initiatives underway as the domain of professional sports.

Despite this evidence of impressive activity and growth, the use of analytics in sports is not without its challenges. Foremost among them is the traditional culture of many teams. Relatively few owners, managers, coaches, and players pursued careers in professional sports because of their interest in analytics.

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Google and the Transformation of Marketing

By Thomas H. Davenport, Mar 06, 2014

I spoke last fall at the Google Analytics Summit in Mountain View, and couldn’t help being impressed with the pace of change at both Google and the marketing profession in general. As an aside, it struck me that Google today is much like AT&T in its prime: a near-monopoly (though unlike AT&T, not a regulated monopoly) in search and search advertising, strong product development (AT&T invented Unix and tons of telecom innovations, Google invented or acquired MapReduce, Android, StreetView, driverless cars, Glass, etc.), and a lot of really smart people (AT&T had Bell Labs, Google has them scattered all over). Both companies are quite analytical; almost every decision at Google is data-based, and AT&T pretty much invented database marketing.

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2014 IIA Symposium: We’re Really Hummin’ Now!

By Thomas H. Davenport, Feb 25, 2014

Along with a number of other IIA faculty, I recently participated in the 2014 IIA Analytics Symposium in Orlando. The event was notable for one primary reason: no, not its location in Downtown Orlando, far from the Disney and Universal crowds. That was interesting, but this is more so: analytics have gotten big and strategic in many organizations. At least in the large, sophisticated companies whose representatives attended the Symposium, analytical capabilities have the attention of senior management. Here are a few semi-random examples from the many analytical leaders and practitioners who attended the session:

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For Better and Worse, Big Data Grows Up

By Thomas H. Davenport, Jan 16, 2014

A company to which I’m an advisor just released its second annual survey of big data use in large companies. Most of the companies (75%) participating in the survey were large financial firms, but 20% were in healthcare and life sciences, and 5% in other industries. The results of the study indicate that big data is growing up. This is mostly a positive phenomenon, but there are some warning signs too.

On the positive side, over 90% of the almost 100 executives surveyed have some initiative underway with big data, and about a third of the respondents have a production application in place. This is a big change from last year’s survey, when most participants were experimenting with big data at best. Clearly big companies are moving to make big data a mainstream enterprise business resource.

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Forecasting the Future of Analytics: 2014 Edition

By Thomas H. Davenport, Nov 11, 2013

With 2014 rapidly approaching, we’re calling on you to aid our world-class faculty of analytics experts and help predict what is in store for next year. Each year, IIA gathers its faculty and leadership to look at the evidence and personal experience and provide a perspective on what the future holds in the world of analytics.

Last year, we predicted that data visualization tools would become more prevalent, suggested that personalized customer analytics would transcend product driven analytics, and posed that the lines between data scientists and other analytics professionals would blur.

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Centenarians Get Frisky with Big Data

By Thomas H. Davenport, Oct 28, 2013

While doing some research recently on companies that are incorporating big data into their products and key processes, I noticed that that a disproportionate number seem to be more than a century old. What’s going on with this phenomenon? Here are some examples, ordered by company age.

Procter & Gamble, all of 176 years old, has transformed its decision-making process with its “Business Suite” executive decision rooms and its “Decision Cockpits” pushed out to 50,000 desktops. Both decision environments include real-time social media sentiment analysis on each P&G brand as part of its “Consumer Pulse” dashboard. Former CEO Bob McDonald was a strong advocate for big data and analytics, but his predecessor and successor, A.G. Lafley, is also very supportive. Lafley announced last month that the company spends about 35% of its marketing budget on digital marketing—well above most of its competitors.

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