Insurance Networking News asked David Pedersen, senior vice president at Insurity, Hartford, Conn., to explain how a data integration project can evolve from an enterprisewide objective to a successful way of life.INN: Do most insurance companies have a data strategy, and why is it important?

PEDERSEN: Most insurance companies do have data strategies. The understandable problem is that those strategies tend to focus first on tactical deliverables such as metrics, measurements and management reports. To be most effective, the data strategy should derive from a clear vision of organizational objectives. The IT infrastructure should be capable of employing data as automated business intelligence. The application of that data should be at the level of operations and business processing. When the data strategy is executed in that way, every tactical deliverable has a discernible organizational value.

INN: Should the ultimate goal be streamlined operations, speed to market, cost reduction or enterprisewide accessibility?

PEDERSEN: All of the above. A data-integration strategy streamlines operations-improving underwriting and risk-selection, improving claims-management and loss-mitigation, revealing business results and patterns, and supporting strategic decision-making. By helping to increase operational efficiency and improve decision-making, it can help cut costs. By helping to increase the speed at which market opportunities are identified and acted on, it can help generate revenue. By helping to increase the speed at which products and services are delivered, it can help improve customer relationships, satisfaction and the ease of doing business. Ease of doing business creates customer loyalty. And by making data accessible across the organization, a data-integration strategy helps insurers determine appropriate investment decisions, develop competitive positions and retain those positions through continued analysis and monitoring.

INN: How should carriers proceed when the decision is made to overhaul data-integration efforts?

PEDERSEN: The first step is to determine the organizational objectives that need to be achieved, whether they be better data; more stringent risk-assessment; faster, more consistent decision-making; higher throughput; more detailed reporting, and so on. The next step is to understand current data flow-how and from where data is captured from system to system-and compare the current state to a desired state. Then it's a matter of defining the data required to create the desired state, defining appropriate data sources, mapping processes and defining infra- structure requirements.

INN: How much attention should carriers pay to risk and compliance issues when implementing a strategy?

PEDERSEN: Compliance is not so much about discrete projects as it is about sustainable, common-sense processes. While compliance mandates are intended to protect the public, they require processes that most companies conduct to protect themselves anyway. The computerization of business transactions and record-keeping has increased the risk of accidental disclosure. But the requirements of SOX, GLB, HIPAA, SB 1386, et al., can be satisfied by protecting information and demonstrating proof of control. For most companies, the compliance crux is in the data - and they ways in which they secure and protect it.

INN: How important are automated data acquisition and cleansing programs to ensure high-quality integrated data?

PEDERSEN: Automation is crucial to speed and efficiency, while the need for cleansing is dependent on the source of the data and its use. Obviously, it's important to acquire timely and reliable data, especially as a means of ensuring efficiency and competitive advantage. But "cleansing" can have varying definitions. When it comes to cleansing, the key is to identify the data that is critical to the particular process. For instance, in one system, an invalid Social Security number may be unacceptable. In another, it may be inconsequential, as long as there is a valid tax-id number. The need for cleansing programs can be determined by making sure that the use cases are understood and that the requirements-gathering phase of any data-integration project is conducted stringently. The bottom line: Trust your data-acquisition source and your data-integration vendor.

INN: In which area is data integration most beneficial (i.e., where does it provide the greatest ROI)?

PEDERSEN: Because a data-integration strategy benefits the entire organization, it's most beneficial in the areas in which it fills the biggest gaps. Putting all requisite processes on a single platform, populated with the requisite data, enables straight-through processing. Automating those core business processes reduces time, errors and cost. The responsiveness enabled by automation makes it possible to implement process improvements, manage workloads and develop production and service standards. That not only enables CRM, it enables complete channel management.

Register or login for access to this item and much more

All Digital Insurance content is archived after seven days.

Community members receive:
  • All recent and archived articles
  • Conference offers and updates
  • A full menu of enewsletter options
  • Web seminars, white papers, ebooks

Don't have an account? Register for Free Unlimited Access