"If your business intelligence system is not going to improve your decision making and find problem areas to correct and new directions to take, nobody's going to bother to look at it," says Chasney.

Start with the Freshest Ingredients
The key to getting accurate insights from BI systems is standard data. "Data quality remains a very overlooked issue in business intelligence, but a massive one," says Gartner's Friedman. "I continue to see failures due to a lack of attention to data quality." Data is the most fundamental component of any BI endeavour. It's the building blocks for insight. Companies have to get their data stores and data warehouses in good working order before they can begin extracting and acting on insights. If not, they'll be operating based on flawed information.

Ruby Tuesday's Ibrahim advises companies to develop plans that outline what they're going to do with data once they get it, practices for preventing redundant data and methods for organizing it in a way that makes sense to the business. For instance, Ruby Tuesday organizes its data around three categories - sales, labour and food costs - that happen to be the key drivers of its business. Those three categories are tracked in a database and put into separate table spaces for ease of reporting and processing, Ibrahim says. That way, information on what products are selling does not get mixed up with information on labour and vice versa.

Knowing that the key to using information to improve decision making is ensuring that the transactional data collected at the point of sale is consistent and accurate, Ibrahim standardized all of the company's restaurants (700 at the time), including those run by franchisees, on a common technology platform in 2001. He also moved the company onto a Microsoft SQL server and open-architecture databases, which makes it easier for business analysts to get to the data they need. The open architecture lets analysts run specific queries against databases when they're looking to find out, say, how many margaritas the company sold on Cinco de Mayo, rather than having to sift through mountains of data to get the answer.

Unfortunately, few companies have the luxury of replacing disparate technology with common systems across all of their units. Wendy's is a case in point. While all 1500 of the company-owned restaurants use the same technology, approximately 5000 franchises don't. The sales data that franchises send to corporate headquarters looks different from the data that company-owned stores submit because franchise data is reported on a weekly basis at an aggregate level. By contrast, more granular transactional data collected directly from the point-of-sale systems of company-owned stores is sent to corporate headquarters on a daily basis. As a result of those differences, Wendy's corporate doesn't have the highest possible level of visibility into its franchise operations.