Using KM to Insure Profitability
Many companies talk about using customer data to improve decision making and increase business. But too often those vital statistics end up in a growing mass of data that only fosters a sense of information overload across the company.
Life of the South Service Co., located in Jacksonville, Fla., sells payment protection insurance indirectly through banks, automobile dealerships and other consumer finance operations. Customers buy this insurance to protect expensive purchases such as cars and electronics. If they become sick or injured and unable to work, Life of the South will make their payments. If they die, the company will pay the account in full.
Like most other insurance companies, Life of the South faces two major constraints on its efforts at profitability and growth. First, state insurance commissions regulate insurance rates. Second, says Robert Fullington, the company's senior vice president and CIO, the insurance business is "basically a data business," in which companies balance the cost of claims against the number of policies they gain income from. To improve profits and margins, insurance companies must be adept at managing, reviewing and identifying profitability on tens of thousands of accounts and developing new products aimed at emerging market niches.
As a standard measure of profitability, all insurance companies figure a loss ratio, which is calculated by dividing losses incurred by premiums earned. For example, losses of $250,000 divided by earned premiums of $1 million produce a 25 percent loss ratio. Loss ratio and policy sales commissions together produce a combined ratio, which Life of the South would like to see at 85 percent. So management was dismayed at its inability to reduce it from 92 percent; just a few points' improvement in this ratio can mean an extra million dollars of profit.
Too much information
Revenues at Life of the South have grown steadily since its founding in 1982, but with only 200 employees, trying to sift through the data from 65,000 accounts became a monumental challenge. The marketing staff and a probability analyst had time to examine only a handful of those thousands of accounts each quarter. "We used to take a set of accounts and go through a set of query tools and spreadsheets to construct a profitability model," says Fullington. "We could do about three at a time and never with any depth."
Life of the South invested $250,000 and what Fullington calls "a horrendous amount of time" over three months in 1998 to build a data warehouse using the Rodin Data Asset Management 3.2 application from Coglin Mill of Rochester, Minn. The project's goal was to provide a way to gather information from various company resources, including the people who track finances, those who process premiums and those who take claims, as well as employees at insurance companies in all 50 states for whom Life of the South performs third-party administration.
The choice of product and the installation proved more straightforward than explaining to Life of the South managers how data warehousing would help them work more effectively, according to Fullington. "We had never had experience using this kind of product," he says. "It was foreign." So Life of the South began with the basics, getting employees to use the software to create simple financial summaries. Eventually they became confident enough to perform specific analyses, says Fullington, and were able to "make better decisions because they understood the dynamics of the business better."
As well as working with data differently, people also had to change their attitudes toward its possession. "People consider their data to be their own," says Ned Hamil, Life of the South's president. "So there is some adjustment when all of us use data drawn from a common warehouse rather than asking people questions and fitting that into the puzzle." The price of having more accurate information available more quickly is that departments must let go of territorial feelings and embrace widespread sharing.
For the 20 employees who use the system regularly for analysis, the switch was not so difficult. Robert Hudson, senior vice president and COO, who remembers doing business without computers, welcomed the transformation of mountains of paper reports into a data warehouse. Hudson uses the software to help solve mysteries. For example, in trying to figure out why the number of claims has gone up in a particular location, he might learn that people in the area are experiencing high unemployment and a large number of health problems; in this case, the company has to raise prices to protect its profitability.
Or Hudson might query the data warehouse to examine the average age of purchasers. If he finds that an account is selling primarily to older individuals he might encourage the salespeople to focus on a wider age range, because while senior citizens are more inclined to buy life insurance, they bring in lower profits than younger individuals. "If we sold where everybody is 55, we'd lose our shirts," says Hudson.
Tailored products
Life of the South also wanted to pinpoint ways to improve the attractiveness of existing products. One example is a policy for an individual who holds a six-year loan but doesn't want to buy insurance to cover payments for the entire period. Running the analysis across all its policies helped the company recognize that the critical period of that loan is the first two years, when the balance of the loan is highest. With that understanding it could tailor its product to cover only those years, thereby reducing the cost to the consumer and making the insurance more attractive, in the hope of increasing sales.
Being able to sift through the accumulated history of its policies also dispelled some myths. When one of Life of the South's bank customers insisted that no one who takes out a loan of more than $20,000 ever buys insurance, the data proved otherwise. "We pointed out that a fairly significant number of people were doing just that," says Fullington. "Before, that market didn't have a loan. After seeing the data, they put an emphasis on that market and sold more insurance."
staff productivity has increased as well. Previously, when company representatives fielded calls from the banks, credit unions and auto dealers that make up its clients, only about 20 percent of the questions would be answered immediately. Now, because employees have greater access to information from their desktop computers, the percentage of questions that can be answered quickly has tripled. And because each claim examiner can look closely at the number and type of claims handled daily, along with where the potential to save time exists, the number of claims that individuals handle has risen.
Life of the South's small staff is further freed by its clients' ability to use the system directly and to receive specific responses even to "fuzzy" requests, for which no report already exists. For example, the owner of 10 branch banks can easily find out how many insurance policies two of his branches sold this month in comparison to the same month a year ago.
Sharing data has helped to boost the company's income in premiums from about $250 million to $300 million annually by allowing management and the marketing experts to measure the value of customers by profit--customers who provide the highest return--instead of by revenue. Life of the South has saved $3.5 million and reduced its combined ratio from 92 percent to 88 percent by canceling unprofitable accounts in which claims exceeded premiums. "Under the old method, we would never have recognized them," says Fullington. "Because they're not high-volume accounts, we would never have looked at them."
An unanticipated benefit of sharing has been to level hierarchy. "Before, information was created in the financial department, passed to the vice president or chief financial officer and then delivered to the president," says Fullington. "Now, preliminary information is available to everyone quickly. I never thought about that result, but it's a positive thing."
Of course, the president still makes the ultimate decision, but he also appreciates the speedy availability of critical data. "The earlier I get information," says Hamil, "the earlier we can take action."