In April 1999, one of Capital Blue Cross's health-care insurance plans had been in the field for three years but hadn't performed as well as expected for the Harrisburg, Pa.-based company. The ratio of premiums to claims payments wasn't meeting historic norms. In order to revamp the product features or pricing to boost performance, the company needed to understand why it was underperforming. To do this, it needed to analyze relational customer usage data -- medical claims, drug claims and demographics of its 1.5 million customers -- to figure out the"" problem and where to make adjustments. Unfortunately, that data was dispersed in transactional systems, stored in flat files. It had been a struggle to make meaningful deductions using existing methods of reentering transactional flat file data into spreadsheets.

External deadlines added to the pressure. Before Capital could make any product modifications, it had to submit the proposed changes for approval by state regulators, and the submission cutoff date was February 2000 -- only 10 months away. Miss the date, and Capital would have to wait six months to a year for another chance to submit.

Because any change to the insurance product would affect the finance and operations groups and involve data, the major stakeholders were the CFO, the executive vice president of operations, and CIO and Senior Vice President Ted DellaVecchia. (DellaVecchia recently left this post to become CIO and senior vice president at Starbucks Coffee Co.) These three, plus members from the user teams, sat down last April to do the Concept Exploration, facilitated by Director of Quality Mick Meckler and his team.

Identify the Business Need

The stakeholders came to the discussion already knowing they needed better extraction and analysis of usage data in order to understand product shortcomings and recommend improvements. "We hadn't gotten at the answers and the underlying issues," DellaVecchia says. "The true facts weren't there to work with."

Identify Alternatives

After listening to input from the user teams, the stakeholders proposed three options. One was to persevere with the current manual method of pulling data from flat files via ad hoc reports and retyping it into spreadsheets. This wasn't merely a straw-man alternative, DellaVecchia points out.

The second option was to write a program to dynamically mine the needed data from Capital's customer information control system (CICS). While the system was processing claims, for instance, the program would pull out up-to-the-minute data at a given point in time for users to analyze. (In retrospect, this option probably would have proved technologically impractical, DellaVecchia says, but it was a legitimate alternative at the time.)

The third alternative was to develop a decision-support system to allow users to make relational queries from a data mart containing a replication of the relevant claims and customer data.

Each of these alternatives was evaluated on cost, benefits, risks and intangibles.

Estimate Cost Versus Value

Capital's valuation incorporates cost and payback in dollars, the relative quality of the outputs the systems would deliver

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