Case study:Forecasting at Olive Garden and Red Lobster
It's Friday night in the college town of Gainesville, Florida, and the local Olive Garden restaurant is humming. Customers may wait an average of 30 minutes for a table, but they can sample new wines and cheeses and admire scenic paintings of Italian villages on the Tuscan-style restaurant's walls. Then comes dinner with portions so huge that many people take home a doggie bag. The typical bill: under $15 per person.
Crowds flock to the Darden restaurant chain's Olive Garden, Red Lobster, Seasons 52, and Bahama Breeze for value and consistency-andthey get it.
Every night, Darden's computers crank out forecasts that tell store managers what demand to anticipate the next day. The forecasting software generates a total meal forecast and breaks that down into specific menu items. The system tells a manager, for instance, that if 625 meals will be served the next day, "you will serve these items in these quantities. So before you go home, pull 25 pounds of shrimp and 30 pounds of crab out, and tell your operations people to prepare 42 portion packs of chicken, 75 scampi dishes, 8 stuffed flounders, and so on." Managers often fine-tune the quantities based on local conditions, such as weather or a convention, but they know what their customers are going to order.
By relying on demand history, the forecasting system has cut millions of milers of waste out of the system. The forecast also reduces labor costs by pro- viding the necessary information for improved scheduling. Labor costs decreased almost a full percent in the first year, translating into additional millions in savings for the Darden chain. In the low-margin restaurant business, every dollar counts.
1- find 6 article that talks about that topic, and one of those articles will be the book.
2- Do an annotated bibliography on those articles.
3- have each article written in a separate page even if you wrote half a page on one article, just have it separated from the rest so 6 different pages.