Research

How artificial intelligence explains analytics

By Kris Hammond, May 19, 2016

No one would ever work with a person that just spits out answers and then walks away. Why would we expect people to work with intelligent machines that do any less?

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Corporate recruiters have a very important and difficult job. They predict who will be a top performer in certain roles, and protect against non-performers getting inside the business ecosystem.

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We’re all generating a lot of data about ourselves and how we live day to day. There are personal fitness devices, preferences and opinions expressed on social media, details on when we’ve come and gone from the house from our security systems, and more. It isn’t just data that companies are collecting from us, but data that we are directly generating ourselves. What should we be willing to do with it and at what price?

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The Logical Step Past Analytics Is Cognitive

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.

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Ideally, guidelines for taking action on Internet of Things (IoT) events should be in response to the type of situation — and type of data — being acted upon. In our experience, in-plant situations fall into one of the following scenarios:

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Humans tend to rely on available information while completing complex tasks. But what happens when information is presented by human and automated sources? And what happens if those information sources conflict?

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Much of the business world still operates using a “gut-based” approach rather than the “data-driven” approach to problem solving. But why, in this day and age, is this still the case? Let me offer three reasons.

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Approach Big Data Analytics Like A Lego Kit

By Bill Franks, Apr 14, 2016

When it comes to Lego’s pre-packaged building kits, there is one aspect that ties closely to the needs of big data analytics. Namely, Lego provides consumers kits that use a combination of both custom pieces and standard pieces to create awesome models which children (and some adults!) can’t wait to get their hands on.

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Business Analytics: An Overrated Sham

By Gary Cokins, Apr 01, 2016

Gary Cokins offers his hot take on business analytics and big data, with an unexpected twist at the end.

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Analytics Journal: Privacy and the Customer Contract

By Daniel Magestro, Mar 22, 2016

The capture and usage of customer data are front of mind for European analytics leaders in many industries. The “customer contract” goes beyond privacy laws that govern the use of customer data to include the implied expectation that their data will be used to their benefit.

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