By Thomas H. Davenport, Oct 02, 2014
If a huge, big-iron-focused company like GE can jump headfirst into the data economy, any firm should be able to do it.
By Thomas H. Davenport, Sep 18, 2014
It’s evident that financial services are going to be very interesting users of big data over the next few years. Of course, there will be important regulatory and consumer privacy issues to navigate. It will also be important to figure out just how to make money from these data products.
By Thomas H. Davenport, Sep 04, 2014
The big data underachievers are companies that have had a lot of data for a long time, but haven’t done much with it. They had big data before big data was big, but for various reasons they simply didn’t use it to improve their business.
By Thomas H. Davenport, Aug 21, 2014
What kinds of activities and decisions should a company pursue as it wrestles with its big data strategy? I see two major decisions at first, and then several others that follow from them. I’ll use Monsanto as an example, since it is a company that is clearly moving from being a provider of seeds and herbicides to one that provides data and analytics-based products and services.
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.
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.
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.
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.
By Thomas H. Davenport, Apr 01, 2014
Available to ERS Clients and Professional Members
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.
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.