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Carriers and TPAs know it’s all about analytics these days; but are they paying enough attention to their data foundations?

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 risk analytics software 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.

  • Accuracy: How closely does your organization’s data represent the form and content of your business?  Even though you may ensure validity, are you ensuring accuracy
  • Consistency: How uniform or erratic is your data over time? Are you capturing excessive amounts of strange, default or unexpected values?
  • Relevance: When you have questions about your business, can you confidently turn to your data for meaningful insights? Does your data satisfy the needs of your key stakeholders?
  • Completeness: Do you have data for all areas of business that you need to measure and understand? Is there anything substantially missing from your data that weakens your ability to use and apply it as widely as you’d like?
  • Timeliness: Is there a delay between when you get your data (in a usable form) and when you need to act upon it?

Data Transformation Services, Download your copy now 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 dawn.zoppa@ventivtech.com.


Nov 11, 2015

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