Research

How to Help Humans Work Better With Smart Machines

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.

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Stronger Cybersecurity Starts with Data Management

By Christopher Smith, Evan Levy, Robert Morison, May 25, 2016

Available to Research & Advisory Network Clients Only

A paradigm shift is underway in the cybersecurity industry. Cybersecurity professionals are moving from a focus on attacker prevention to attacker detection. Preventing the “bad guys” from getting in is still important, but cyber adversaries are increasingly able to bypass even the most sophisticated network defenses. Once inside, it is more important than ever to find these attackers fast, before their activities get buried in the daily volume and pulse of network communications. This is where security analytics holds promise. Security analytics provides the necessary and timely visibility into normal and abnormal network behavior.

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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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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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IIA Analytics Symposium: Chicago - April 13, 2016

By Daniel Magestro, Apr 29, 2016

Available to Research & Advisory Network Clients Only

On April 13, the International Institute for Analytics hosted the first 2016 Analytics Symposium at the Gleacher Center in Chicago. The event brought together IIA clients, partners, and faculty for a day of open conversation, best-practice sharing, and lessons learned – all intended to provide fresh perspectives on the various aspects of building and strengthening the analytics capabilities of our member companies.

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The following is the agenda used during the 2016 Analytics Symposium - Chicago, held at the Gleacher Center in downtown Chicago, IL.

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2016 Analytics Symposium Chicago Slides

Apr 25, 2016

Available to Research & Advisory Network Clients Only

The 2016 Analytics Symposium - Chicago took place on April 13 at the Gleacher Center in downtown Chicago, IL. The event brought together IIA clients, faculty and experts to participate in moderated discussions on key analytics topics, including talent, technology, industry maturity, and more. The slides presented during this event are available to members of IIA’s Research and Advisory Network.

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The Intelligent Systems Eco-System

By Kris Hammond, Apr 21, 2016

Available to Research & Advisory Network Clients Only

It is undeniable. A new renaissance of intelligent systems has begun. We now have systems that are labeled as Cognitive Computing, Machine Learning, Deep Learning, Predictive Analytics, Recommendation Engines, and a half dozen other names. And one way or another, they are all embodiments of the idea that there are some types of very human reasoning that can now be done by machines.

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