Jan/Feb 2014

Decision Management Solutions (DMS) recently conducted research into predictive analytics in the cloud. Sponsored by FICO, Lityx and SAP, the research has at its core a survey of more than 350 respondents from a wide range of industries. Following up on a 2011 survey, the 2013 results make it clear that predictive analytics in the cloud is becoming increasingly mainstream, with broader and accelerating adoption.

• James Taylor

So you’ve decided to break free of whatever organization you worked for and go out on your own as an analytics guru, have you? Solo practice does have its attractions. You’ll have a boss you can always reason with. You get to set your own hours, rates and expectations. Freedom! But there are a few things you had better keep in mind.

The purpose of this article is to provide potential employers and clients of analytics professionals with useful information about the Certified Analytics Professional (CAP®) program offered by INFORMS, the leading professional membership organization in the world for advanced analytics. Beyond providing some updates regarding the CAP program, we also offer suggestions on how certification should (and should not) be used and attempt to answer questions such as, “How can certification help you find and retain analytical talent?” and “Why should I support certification for my existing employees?”

• Polly Mitchell-Guthrie
• Scott Nestler, CAP-X

In my last article I highlighted opportunities for health analytics entrepreneurs in the field of radiology services and revenue cycle management. This article focuses on two more opportunities, which are also part of the Centers for Medicare & Medicaid Services’ (CMS) reportable quality measures for provider organizations: managing population health and medication adherence. Some healthcare organizations have already achieved early success using analytics, but many have yet to adopt it. During the next three to five years, I predict we will see increased adoption of analytics in these two areas, driven by the need of compliance and the search for profitability.

• Rajib Ghosh

Missing values – and how to deal with them – is an inevitable problem for statisticians, data miners or anyone working with analytical data. Missing values in the data create uncertainty for the analyst and the information consumer because decisions need to be made without having the full picture. Missing values should trigger a discussion about randomness and systematic patterns, as they might introduce more fuzziness and/or bias into the picture.

• Gerhard Svolba