Data Management’s Dirty Little Secret

Business Intelligence Woes Leave Insurers Poorly Positioned to Compete

The scene: The boardroom of a major insurance company. The situation: New sales are flat. The latest product launch was disappointing, and producers are complaining that competitors already have an edge on the Web. The chief marketing officer says he needs better customer and producer data to offer more segmented products targeted to the right distribution channels. The problem is the company uses a variety of data management tools that source data from a variety of heterogeneous systems, and getting a consolidated view is no easy task.

All eyes turn to the CIO. Sound familiar? Scenes like this are playing out in the boardrooms of large corporations around the globe. And in most situations, companies are confronting the fact that they lack the business intelligence needed for an overall view of their enterprise.

“Many corporations are facing a data quality crisis, and it’s a dirty little secret that nobody wants to talk about,” said Jerry Boltin, director of CSC’s Business Intelligence Practice. “Making business decisions without accurate data can cause massive disruptions, and the issue for many companies begins with a problem with the source data itself, in addition to the way that data is processed, analyzed and reported to management.”

Reliable, Relevant Data

Armed with good business intelligence, insurance companies can do a better job of introducing products that appeal to the market, and they can fine-tune those products based on customer, producer and competitor analytics. Business intelligence also supports the automation of key processes such as underwriting decisions, and it improves management’s ability to monitor business performance.

“The key to successful business intelligence initiatives is getting reliable, relevant data in a configurable format to the people who need it on the frequency that they need it – from real-time to established cycles depending upon the decision context and use,” Boltin added. “It takes the IT department out of the critical path and allows for real-time decisioning throughout the organization including call centers, Web portals and the underwriting desk.”

Solving business intelligence problems takes more than just an investment in a new tool. In fact, many companies are deluged with tools, often using different ones for various lines of business.

Crossing Organizational Boundaries

CIOs typically must work with multiple business units and vendors to build a true master data management system.

“The CIO can’t do it alone, and business unit managers are often reluctant to move to a new analytical environment that crosses organizational boundaries,” Boltin noted. “It’s essential to have a good change management plan to demonstrate the benefits of the new program. The days of ‘my data’ and ‘your data’ are gone. Companies must rethink their basic governance structure to ensure someone is always accountable for data management at the enterprise level.”

Data management is especially challenging for insurance companies. Data sources are typically siloed like the organization itself. Departmental tactics on data warehousing over the years have left the organizational data fragmented, built with differing standards and overly focused on narrow requirements.

“Large-scale business intelligence programs require specialized skills most companies don’t have in house, and building up that competency can be time-consuming and expensive,” Boltin said. “Not only do they need to know where to put their investments but also the right metrics to gather. Underlying this is the need for better data security, which is becoming increasingly complex to manage.”

The Master Data Management Approach

Wondering if master data management is right for your company? Bert Lasley, director of CSC’s Data Transformation Practice, offers the following advice to insurers:

• Create a shared services framework. Organizations must define who’s responsible for data at the enterprise level and create a roadmap for implementing change. A shared services approach can help pool resources and tools and ensure data management processes are standardized across the organization. Companies can unlock data currently stored in multiple silos and get a more cost-effective approach to technology consolidation and modernization.
• Cleanse and reconcile data from multiple sources. A recent report by the Data Warehousing Institute found that 83 percent of organizations suffer from bad data because of inaccurate reporting, internal disagreements over which data to use and incorrect definitions that render the data unusable. The coordinated use of data warehouses, data marts, operational data stores and master data repositories will ensure reliable and consistent data definitions, no matter what the source.
• Gain greater insight into customer and distribution trends. The right set of metrics can equip insurers with better information for finding the right customer, determining the customer’s propensity to buy or simply identifying customer segment characteristics that would best respond to specific products and campaigns.
• Develop a dashboard of corporate performance metrics. The CEOs of mid-tier companies and presidents of market segments of larger carriers will be better positioned to make more productive capital allocation decisions with an easy-to-read dashboard consolidating data related to new business, sales backlogs, investments, claims and other liabilities and operating expenses.

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