Nonfinancial data can predict future profitability.(SELECTED TOPIC)

Data on intangibles such as customer satisfaction can yield significant forecasts of earnings only when they are analyzed in conjunction with financial statistics, according to recent research. Accounting Professor Madhav Rajan used a collection of wide-ranging customer relationship data from 115 retail banks to develop the most powerful guidance yet for managers wanting to know how to use nonfinancial metrics effectively.

His key finding is that no single customer relationship metric can be used to predict future earnings. Rather, when considered in relationship to other measures, such metrics can lead to a financial profitability number 15 percent closer to the actual figure for the coming year than is otherwise possible. Such a percentage is gold for the soothsayers of finance.

In his study, Rajan, the Business School's Gregor G. Peterson Professor of Accounting, examined the interactions of metrics such as customer satisfaction, employee turnover, the speed of loan processing, and the average number of products and services customers purchased against prices, costs, and other figures.

"Looking at a customer satisfaction number alone doesn't do you much good unless you know the costs involved in achieving it," says Rajan, who conducted his research with Venky Nagar, associate professor of accounting at the University of Michigan. "Customers might be satisfied because you're giving them everything for free, but this doesn't say much about what your future profitability will be."

In other words, says Rajan, a bank must compare customer satisfaction to a cost such as the amount of interest it pays out. "We found that high customer satisfaction and low interest costs push profitability significantly," he says. The bottom line: a bank can rely on the customer service metric as a predictor of profitability only when its interest or "deposit" costs are low.

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