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Attendees at this week’s National Workers’ Compensation and Disability Conference (NWCDC) will undoubtedly hear a lot about all things analytics, from Big Data to the Internet of Things to predictive modeling. It’s important to remember, however, that high-quality, complete and relevant data is the foundation of effective analytics of any kind. There are some important, often-unappreciated prerequisites for effective analytics that insurance entities should bear in mind.
For today’s carriers and TPAs, analytics supports core operations across policy, billing and claims; analytics is also critical to monitoring the business, creating new products and programs, satisfying client needs and fulfilling regulatory requirements. Chances are, you’re well aware that your organization wants bigger and better data stacks, so it can perform more extensive analysis in support of business decisions.
It’s no exaggeration to say that data is the lifeblood of an insurance enterprise. The data elements being captured and reviewed need to be broader than ever, and the data quality must be higher than ever, as well. Specifically, there are five important considerations to remember when considering how data quality directly impacts the effectiveness of their organization’s analytics.
If you’ll be attending NWCDC this week, please visit booth #523 to talk about how data quality impacts analytics, and the steps you can take to improve your organization’s data quality. Whether your organization handles data management and processing internally or uses a third party, the five considerations outlined above are crucial to effective analytics.
Dawn Zoppa is a Ventiv Technology vice president and practice leader of the Data Transformation business unit. Contact Dawn at 312.635.4183 or email@example.com.
Nov 11, 2015
| Originally posted on
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