Enterprise Data Warehousing Solution Applebee’s International implemented an enterprise data warehouse (EDW) from Teradata with data analysis capabilities that helped management acquire an accurate understanding of sales, demand, and costs. An EDW is a data repository whose data is analyzed and used throughout the organization to improve responsiveness and ultimately net earnings. Each day, Applebee’s collects data concerning the previous day’s sales from hundreds of point-of-sale (POS) systems located at every company-owned restaurant. The company then organizes this data to report every ticket item sold in 15-minute intervals. By reducing the amount of time required to collect POS data from two weeks to one day, the EDW has enabled management to respond quickly to guests’ needs and to changes in guests’ preferences. With greater knowledge about their customers, the company is better equipped to market and provide services that attract customers and build loyalty.
Business Improvements Applebee’s management gained clearer business insight by collecting and analyzing detailed data in near real time using an enterprise data warehouse. Regional managers can now select the best menu offerings and operate more efficiently. The company uses detailed sales data and data from customer satisfaction surveys to identify regional preferences, predict product demand, and build financial models that indicate which products are strong performers on the menu and which are not. By linking customer satisfaction ratings to specific menu items, Applebee’s can determine which items are doing well, which ones taste good, and which food arrangements on the plates look most appetizing. With detailed, near real-time data, Applebee’s International improved its customers’ experience, satisfaction, and loyalty—and increased the company’s earnings. For the third quarter of 2007, total system-wide sales increased by 3.9 percent over the prior year, and Applebee’s opened 16 new restaurants.
Lessons Learned from this Case This case illustrates the importance of timely and detailed data collection, data analysis, and execution based on insights from