3 Steps to Good Data
Insurance Experts' Forum, July 8, 2010
These days, with margins thin and competition intense, organizations of all types are turning to data analytics to gain that extra edge in understanding both what customers are doing, and what they intend to do.
However, the act of identifying, gathering and turning data into useful insights can consume significant bandwidth—something in precious supply in many overstretched, understaffed insurance operations. This is something that concerns Stuart Rose, global insurance industry marketing manager at SAS, a company that lives, eats, sleeps and breathes analytics.
“Because most insurers spend so much time gathering and cleaning data and creating reports, there is little time left to explore data for insights that can have a positive impact on the bottom line,” he says.
The solution? Rose believes insurers need to take a closer look at their data management processes across the enterprise, from back-office to front-end.
Rose says there are three elements that should be part of any effective data management effort:
1. Data mapping: This is the most challenging part of data management, taking up to 70% of the data management effort, Rose says. But it's the most essential step. “Often, data resides in multiple legacy systems, various formats and an assortment of different databases,” he explains.
2. Data quality: This is paramount for any system, as the value of information depends on it. “No insurance company can ever be sure that its premium calculations, loss reserving or statutory reports are accurate and reliable if the supporting data is not cleansed and validated according to defined business rules,” Rose says. He recommends techniques, such as plots and descriptive statistics, to identify issues with data. In addition, many insurers are using a “unified data model that not only helps with data quality but ensures consistency in the terminology of the data items,” Rose adds. “For example, a simple description or abbreviation can have multiple meanings. Just consider the wide variety of different types of policy coverage. Within auto insurance, the abbreviation BI stands for bodily injury, while for business owners policy insurance BI represents business interruption.”
3. Data governance: Make sure someone is in charge of the way data is handled and prioritized, either through a committee, or by a “data steward.” As Rose observes: “to resolve many data issues, insurance companies are beginning to assign a designated data steward who is responsible for the reliability, availability and utilization of data throughout the organization.”
“Data management and data quality are no longer 'nice to have' options; they are essential,” Rose states.
For more on this topic, I explore the challenges and opportunities insurance companies face in a new report here at Insurance Networking News.
Joe McKendrick is an author, consultant, blogger and frequent INN contributor specializing in information technology.
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