Research

Population Health Analytics: Framework, Toolkit, and Strategies Part II

By Dwight N. McNeill, May 27, 2015

Available to ERS Clients only

Part II: PHA Applications and Toolkit Key Takeaways Population health analytics can support the attainment of population health goals through four applications areas: high-cost case identification and management, individualized health, community health, and multi-sector alliances. Today, U.S. healthcare approaches population health primarily by addressing “super-utilizers.” In order to achieve better health outcomes for more people, it needs to advance up the maturity curve by adopting community-level strategies. This progression will challenge population health analytics to deliver and manage multiple data sources, new information delivery systems, complex data integration, and organizational performance metrics. Overview Population health analytics (PHA) is a…

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The 10 Levels of Analytics

May 26, 2015

Available to ERS Clients only

In this phone briefing John Elder and Andrew Fast describe the types of analytics inquiry and categories of modeling technology, illustrated with examples drawn from tabular data but also from advanced information types, such as sequences, text, and links.

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Get Real: Real Options and Strategy Tactics

By Mark Dobeck, May 22, 2015

Available to ERS Clients and Professional Members

The strategy and supporting tactics of an organization link the firm to opportunities in the external environment. There are several segmented and widely accepted business environments that must be considered by a firm when making strategic decisions. These include the ecological, societal, industry/competitive, and the internal environment (resources, capabilities, and competencies). Also, strategic decisions are of considerable significance in comparison to operational decisions and should be considered as rare, consequential, and directive.

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Realizing the Potential of Machine Learning

By Robert Morison, May 20, 2015

Available to ERS Clients and Professional Members

Machine learning is rapidly coming of age. Three forces – highly scalable computing, the ability to handle vast amounts of structured and unstructured data, and sophisticated algorithms and methods – combine to advance the power of machine learning and put it to work in a growing array of business applications. We discussed the opportunities with two of Intel’s leading experts, Bob Rogers, Chief Data Scientist for Big Data Solutions, and Kathleen Crowe, Director of Data Science.

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The Current State of Hadoop in the Enterprise

By IIA Faculty, May 20, 2015

Available to ERS Clients and Professional Members

Taken together, the actual experiences of Hadoop users today temper the fervor of the various Hadoop related market segments. Hadoop will undoubtedly play a central role in the data and analytics architectures of the future, but can also carry with it expense, rapid change and frustration in the near-term. As the Hadoop ecosystem continues to develop, reality will come into line with the promise.

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On the Lighter Side…

By Jack Phillips, May 19, 2015

On the lighter side this week, I was reminded of how commonplace data and analytics have become among young generations.

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Applying Lean Principles to Analytics Projects

By IIA Faculty, May 18, 2015

Available to ERS Clients only

An IIA Client asks about ways to improve their analytical process by applying lean principles to analytics. We offer ways to incorporate lean principles successfully.

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Data and, therefore, information, is valuable. I assume that anyone reading this will agree with that assertion. At the same time, any given piece of information may not be relevant or helpful for any specific purpose. In other words, information has value when placed in the right context.

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Supply Chain Planning is Garbage In Garbage Out

By Cheryl Wiebe, May 12, 2015

Lean manufacturing has been massively adopted over the last 10 years. Lean is driving attention to the notion of supply chain variability and accuracy of planning factors. But lean assumes your supply chain is infallible. Here’s how to incorporate analytics to improve supply chain planning.

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Healthcare Data and Analytics in the Cloud

By IIA Faculty, May 08, 2015

Available to ERS Clients only

An IIA Client asks about performing high volume computational analytics in the cloud, and in particular, using a private cloud on Amazon Web Services of Google running full PHI and PII data.

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