Medical malpractice insurance could be one of the riskiest businesses on the planet today. Competition for customers is fierce. Claims can be complex. Litigation is often protracted and expensive, and sometimes not even the sky is the limit for the awards. How can an insurer prosper in such an environment? The answer today appears to be a combination of guts, experience and timely information. For Frontier Insurance Company of Rock Hill, New York, we can add data warehouse technology to the list. Over the last decade, Frontier has established a phenomenal reputation in the insurance industry as a leading provider of specialty insurance. They provide traditional coverage for medical malpractice and workers' compensation, but also an eclectic array of coverages, from campground operators to crane rental operations.

The company reported nearly $300 million in premium revenue in 1996; it holds over a billion dollars in assets and has more than $200 million in surplus reserves. By insurance industry standards, this is not particularly large, but in the specialty insurance business, it is remarkable.

Medical malpractice coverage, or med-mal, is one of the fastest growing areas of the company. Demand for coverage has never been higher, yet many large insurers have discontinued the med-mal line, creating enormous opportunity--with high potential risk. As Joe Loughlin, Frontier vice president of Medical Malpractice Claims and Legal said, "Being successful in the med-mal business requires innovation and sound historical information." Frontier has always been strong on innovation, but by using data warehouse technology it has also begun to harness the power of its information.

Loughlin further explained, "There are two critical points where information affects our bottom line. The first is in underwriting. A solid claims history helps enable us to quote rates that make good business sense. Knowing which business to walk away from protects the strength of the company and the other insureds. The second critical point is in claims. An accurate history of claims, settlements and litigation in specific venues helps us make sound decisions on new claims."

Prior to September 1996, the Frontier med-mal business unit was operating three separate systems for claims information. We had a service bureau, WANG versus AS/400 with DB2/400. Each had its own data formats and produced its own reports, causing ever-increasing information delays. Loughlin says, "The systems infrastructure was the greatest impediment to our company growth."

For over a decade, Frontier's evolving information systems needs were met by adding entire hardware/software environments. Even though each system held essential data, the dissimilar data types could not be consolidated into meaningful reports. We had to consolidate two years of DB2 information with eight years of flat-file systems. Administrative staff manually rekeyed information to generate reports. In 1995, Frontier purchased several products from LANSA USA to assist in the company's application development process. Since LANSA technology is ideal for consolidating information, Loughlin asked MIS to consider a data consolidation project. That was the beginning of the med-mal data warehouse project.

The Technical Challenge

The main challenges were trying to understand the data as it existed in each system and making the new system easy to understand and use. LANSA is a systems architecture that allows data to be stored centrally using RAID 5 on a disk type 6606 and then accessed by applications written in RDML (the LANSA fourth generation language) or by other application development tools such as Visual Basic or PowerBuilder. Applications can then be deployed to work on AS/400 workstations or PCs as required. We have a Novell Network using IPX protocol to Netware for SAA/Gateway.

"For this project, we built fields in the LANSA repository to correspond with field names in each source system. This required building data extraction and data scrubbing functions in RDML to eliminate the need for manual correction and consolidation of dissimilar information. When this phase was complete, all data was finally being presented in a standardized format." Making the system user-friendly meant getting claims and legal terms standardized on all field names, a task complicated by various business units calling the same thing by different names. Using LANSA/OPEN for PC-to-AS/400 transportation and LANSA/CLIENT, the query and reporting tool, we were able to provide instant access to the data.

As for the future of Frontier Insurance, Loughlin says, "This company has grown from a small regional operation to one that will be in the top 100 property/casualty insurers in the country in 1997. We acquired three new companies within the last year which creates yet another data integration challenge. We are looking to LANSA to potentially integrate their systems into our data warehouse, but more than that, to be our secret systems weapon for maintaining strong, profitable growth in the years to come."

Don't think that a data warehouse project is going to be easy. Plan on experiencing tremendous amounts of frustration and do not attempt to build a large-scale data warehouse all at once. Start small, but keep in mind the ultimate goal is a large scale enterprise and evolve into that as you go. Building a data warehouse requires a huge commitment from the people who work on the project. It becomes part of you and is forever ongoing. Be prepared to make that type of commitment or don't start the project at all. Try to recruit a sponsor who will support you and the team's effort and fight for you when you have setbacks.

If I had to do it over again, I would not allow project scope creep to occur and I would have more resources available to get the job accomplished faster. People have a tendency to change their requirements and ask for more as the project goes on. Business requirements change so rapidly today and building a data warehouse requires so much time that by the time you provide what they initially asked for, they either no longer need it or it isn't as important as when they initially asked for it. However, it was difficult to justify a lot of resources in the beginning because there was no evidence of any tangible benefit of doing data warehousing within our organization.

One of the biggest obstacles to overcome is trying to stay focused on the long-range goal. We tried to do too much, attention to detail suffered, and then problems happened. We could have prevented our problems had we kept our documentation and flow charting (meta data layer) up to date and not succumbed to the political pressures of the organization by trying to please too many people at once.

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