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Business Intelligence (BI) for the Mid-Market

By Allan Holmes

January 15, 2007 — CIO — Chris Boebel, the director of information technology at Delta Sonic Car Wash Systems, had a big sales job on his hands.

Delta Sonic executives knew they could run the chain of car wash and convenience stores more efficiently. They also wanted to boost sales. But they had few tools with which to pinpoint their best-selling products, most-popular car washes, top marketing promotions and the impact of those promotions on sales in other parts of the business. For Delta Sonic to keep growing, such insight into the business and its customers was critical.

Boebel believed that a business intelligence (BI) application could help unlock future growth for the Buffalo-based company. A BI system could feed data on product sales and customer response to discounts back to the finance and marketing departments so that executives could zero in on what worked and what didn’t.

But Boebel (pronounced BAY’-bill) knew winning approval from the business for a BI application would require a deft negotiating touch. Some business unit managers were likely to view BI as too expensive and elaborate a solution for a midsize company. Many Delta Sonic executives were wedded to decades-old, mostly paper-based reporting systems and would need to buy in to the promise of the new technology. Boebel would also have to overcome the sentiment that BI was only for the big boys—megacorporations with nationwide or global operations that manage tera- or petabytes’ worth of information.

But after months of attending BI conferences, talking with numerous vendors and creating a presentation that showed how a simple BI Web tool could help the car washes to staff more efficiently, Boebel was ready. His careful research and early test results helped him line up support with the CFO, operations manager and some key business unit leaders to argue for a bigger investment in BI. In 2004, he got an OK from Delta Sonic’s family owners to invest $250,000 in Cognos’ 8 BI application; this was a large investment for a company with annual revenue of $200 million, as reported by Hoovers. In the spring of 2006, after deploying some simple analysis of convenience store sales—showing which promotions were increasing beer sales and why, and which brands of cigarettes were the biggest sellers—Boebel and his team expanded the system to other business units such as the car wash and oil change business. The information gleaned from the convenience stores and car washes—based on knowing which promotions work best and generate sales of other products and services plus the ability to better track cashier statistics to prevent losses—have returned enough to recover half of the initial investment. "It’s really paid off," Boebel says.

 

 

 

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