These restaurant chains' successes are unusual considering the indigestion companies in other industries have got from their BI initiatives. "Most BI implementations fall below the midpoint on the scale of success," says Ted Friedman, an analyst with Gartner. Restaurant chains use BI effectively and realize value from it for a variety of reasons, and other industries would do well to pay more attention to restaurant chains, according to Hartmann. Because their industry is so competitive, they have to be agile, so their cultures are accustomed to rapid change. Also, their BI initiatives are closely aligned with their business strategies, and the insights that their BI systems produce contribute to improving operations and the bottom line. Finally, they've found ways to address three of the biggest barriers to BI success: having to winnow through voluminous amounts of irrelevant data, poor data quality and user resistance.

"If you're just presenting information that's neat and nice but doesn't evoke a decision or impart important knowledge, then it's noise," says CKE's Chasney. "You have to focus on what are the really important things going on in your business," he says.

At Ruby Tuesday - as at most restaurants and, indeed, in most companies - sales, products and service are the most important levers in its business. So, in August 2003, when the chain's BI system identified a restaurant in Knoxville, Tennessee, that was underperforming, it used the very same system to drill down into that store's specific problems in an effort to help the company determine what corrective actions to take.

The company's BI software indicated that customers were waiting longer than normal for tables and for their orders once they were seated. It was a recipe for customer dissatisfaction, and of course poor sales. Management at corporate headquarters wanted to know what specifically was wrong. Was the restaurant not adequately staffed? Was the problem with the kitchen staff, a server, an assistant manager, a general manager - or with something beyond the company's control, like the location?

Managers used BI tools to study food costs. High food costs might have indicated inadequately trained cooks who were ruining a lot of food before getting dishes right, which would have contributed to increased wait times. But food costs were normal.

Managers then assessed the time it took for a table to change hands from one patron to the next, using the BI system to calculate the time between when a waitstaffer opened a docket on the point of sale to the time the customer paid the tab. Nick Ibrahim, senior vice president and CIO of Ruby Tuesday, says the average time it takes a restaurant to turn over a table from one customer to the next is 45 minutes. So if the company sees in its BI system that it takes 55 to 60 minutes to close a bill at a particular restaurant, people aren't getting their food as fast as they should. (The problem is rarely a matter of diners lingering over their meals, especially if it's taking the waitstaff at every table 55 minutes to close the docket.) Management concluded based on this information and by visiting the restaurant that the long wait times were a result of increased demand. The area had been through an economic boom, and the restaurant was running at full capacity. The company made changes to the layout of the kitchen, the placement of food and the location of cooks so that everyone had easy access to the food and equipment they needed to produce dishes faster, to move more customers through the restaurant and ultimately to increase sales. The changes increased the rate at which tables were turned by 10 percent, which in turn decreased wait times for customers.