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Case Study – Spicy Wings Case Study

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Following his graduation from the MBA program at the University of Phoenix, John Tyler wanted to live and work in the little town of Hood. However, the community was small and there were not a lot of readily available opportunities for college graduates. Fortunately, John had some experience working in the food service industry gained in summers and throughout high school at his uncle’s restaurant in Franklin, a few miles away from the town of Hood. When John decided to leverage his experience into a small delivery and take-out restaurant located close to his home, he thought he had hit on a great idea. John would offer a limited fare consisting of the buffalo wings his uncle had perfected at his restaurant. John called his restaurant, Spicy Wings. Although success came slowly, the uniqueness of John’s offering coupled with the growth of the community made Spicy Wings a success.

John’s business was pretty simple. John purchased wings locally. The wings were then seasoned and prepared in John’s restaurant. Once an order was received, John cooked the wings, which were then delivered or picked up by the customer. John’s establishment was small, and there was no place for customers to dine in the restaurant. However, his wings proved so popular that over time, John hired several employees, including three delivery drivers. Business was steady and predictable during the week, with the biggest days being home-game football Saturdays.

A little over a year ago, the little town of Hood began to grow and expand. John noticed his business was beginning to suffer when other fast-food delivery restaurants opened around the town. Some of these restaurants were offering guarantees such as “30 minutes or it’s free.” John’s Spicy Wings now had to compete with fish tacos, specialty pizzas, and gourmet burgers. Most of these new restaurants, however, were dine-in establishments providing carry-out and delivery as a customer convenience. However, John was certain he would need to offer a delivery guarantee to remain competitive with the newer establishments.

John was certain a delivery guarantee of “30 minutes or it’s free” could easily be accomplished every day except on football Saturdays. John thought if he could offer a 30-minute guarantee on his busiest day, he would be able to hold onto and perhaps even recover market share from the competition. However, before he was willing to commit to such a guarantee, John wanted to ensure that it was possible to meet the 30-minute promise.

John knew it would be no problem for customers to pick up orders within 30 minutes of phoning them in. However, he was less confident about delivering orders to customers in 30 minutes or less. Not only would the wings need to be cooked and packaged, but the delivery time might be affected by the availability of drivers. John decided he needed to analyze the opportunity further.

As a part of his analysis, John decided to take a random sample of deliveries over five different football weekends. Cooking time and packaging time were not considered in his analysis because wings were not cooked for individual orders. Rather, large numbers of wings were cooked at a single time and then packaged in boxes of 12. John decided to focus his analysis on the time required to deliver cooked and packaged wings. He collected information on the amount of time an order had to wait for a driver (the pick-up time), as well as the amount of time required to transport the wings to the customer (the drive time). The sampled information is in the Excel^® file, Spicy Wings Data Set. John is not willing to offer the guarantee on football Saturdays, unless he can be reasonably sure the total time to deliver a customer’s order is less than 30 minutes, on average. John would also like to have an estimate of the actual time required to deliver a customer’s order on football Saturdays. Finally, John would like to know how likely it is the total time to make a delivery would take more than 30 minutes. Based on the sampled data, should John offer the guarantee? What percent of the Saturday deliveries would result in a customer receiving a free order? What recommendations might help John improve his Saturday delivery times?