The Data Dilemma in Predictive Analytics

By Robert Regis Hyle

It's hard to predict the future without a crystal ball. In terms of what insurance carriers do, when predicting how things will turn out, the data is their crystal ball.

Those with good data can turn it into actionable decisions and those without good data are doomed to poor decisions, according to Merit Smith, vice president of Robert E. Nolan Co. "I think divisional-level operations and IT staffs probably have a more realistic sense of data quality issues and how well their data would facilitate advanced analytics," he says. "Generally, before you can do anything you really need to tend to your data, clean it up, and get it in properly structured models. So there is better understanding of that need closer to the operation level than at the corporate level."

Smith is featured on a new podcast with Tech Decisions editor-in-chief Bob Hyle as they discuss data and predictive analytics. To learn more and to hear their entire conversation, click here.

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Date: August 25, 2010 | Time: 2:00 PM EST

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