Research

Population Health Analytics Part III: Best Practice Examples

By Dwight N. McNeill, Jul 23, 2015

Available to ERS Clients only

This Research Brief is the last of a three-part series on population health analytics (PHA). The prior briefs have focused on definitions, frameworks, and application models. Now we turn to real examples of putting population health analytics to work: to identify and manage high-cost and high-need patients; to improve individualized care by taking into account data on the social determinants of health; and to achieve optimal health outcomes for all people through community action.

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My plea to HR (and any other department hiring a Data Scientist)? Stop hiring real Data Scientists until you’re ready to do real data science.

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The Analytics Leader’s New Clothes

By Jack Phillips, Jul 17, 2015

No amount of spending, and no technology stack is going to make a company analytical. We’ve seen this fact lost on too many companies. Research shows that more than half of analytics projects fail, and technology is most frequently not the culprit.

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Inquiry Response: How to Organize for Data, BI and Analytics

By IIA Faculty, Jul 16, 2015

Available to ERS Clients only

The IIA Faculty answers a question around how best to organize a global business team for data (big and small), business intelligence and analytics.

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Would The Last Marketer Please Turn Out the Lights

By Thomas H. Davenport, Jul 14, 2015

Marketing is becoming increasingly automated, and before long there may be little need for lights in the marketing department. Humans will still oversee these automated efforts, but there will probably be substantially fewer of them.

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I spend a lot of time these days talking with companies about the need for a formal approach to enabling what is often called “discovery analytics” or “exploratory analytics.” What I find is that many people have a fundamental misunderstanding of what discovery analytics is all about.

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Inquiry Response: Machine Learning Best Practices

By IIA Faculty, Jul 08, 2015

Available to ERS Clients only

An IIA Research Client asks about best practices around decision making in a machine learning / big data environment.

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June 2015 Research Roundup

By IIA Faculty, Jun 30, 2015

To recap our work for June 2015, check out the following summary of our publications and activities.

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The State of Hadoop Adoption

By Jack Phillips, Jun 29, 2015

Available to ERS Clients only

In this phone briefing, Jack Phillips shares IIA’s new findings from the recent research report, “The Current State of Hadoop Adoption”. In this briefing, Jack explores the pros and cons of using Hadoop, including examples of how companies get value from Hadoop and the key challenges organizations face when implementing a Hadoop solution.

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The Science of Data Visualization

By Lindy Ryan, Jun 29, 2015

Available to ERS Clients only

It’s a cognitive truth: our visual system is enormously influential in our brains. As an information learning and processing mechanism, our brains are our best tool in decoding and making sense of information presented visually. The best data visualizations are designed to properly take advantage of “pre-attentive features” – a limited set of visual properties that are detected very rapidly (typically 200 to 250 milliseconds) and accurately by our visual system, and are not constrained by display size.

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