Spicy Wing case study

Descriptive Statistics

Name

Date

After John Tyler graduated with an MBA program from the University of Phoenix, he decided to look for an employment opportunity in Hood, his little town where he was born. John decided to start a small delivery and take-out restaurant. He had relevant experience from his uncle restaurant he has been working in during school holidays. He purchased wings locally and seasoned them in his restaurant and later prepared them as packaged orders for his clients to pick up or delivered to them. His business flourished after a time and he had four employees.

John has faced escalating competition in the past with other food joints being set up in the region. There is many fish tacos, specialty pizzas, and gourmet burgers restaurant. Most of these new restaurants, however, were dine-in establishments providing carry-out and delivery as a customer convenience. He incorporated 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. Functions of statistics are useful in describing and summarizing the set of data provided(Saeed, 2014).

Table 1. Computed data of Spicy Wings Restaurant

• The sample size is the total number of samples = 200

• Five-number summary on the total time = 22.5226

After computing the data in a table, John will be able to make a descriptive analysis and determine the viability of his venture. The data shows that there is a high possibility of delivering the packaged orders, in less than thirty minutes. The average time taken for a packaged to be picked and reach the consumer is 22.5226 (+/ 4.861929). This means that the package will take at most 27.384529 minutes and lowest time of 17.660671 minutes to deliver a package. The analysis guarantees John probability of meeting his thirty minute or free strategy. A package will take a maximum drive time of 23.2568941 minutes to reach its destination and a maximum of 5.4659 minutes to be picked by the driver.

John will also be able to maximize deliveries on busy hometown Saturday football events. John should consider offering the guarantee on football Saturdays; since he can be reasonably sure the total time to deliver a customer’s order is less than 30 minutes, on average. John has an estimate of the actual time required to deliver a customer’s order on football Saturdays.

We determine the probability of the likelihood to deliver an order in more than 30 minutes by deducting the standard deviation from 30, we get 25.138. The time beyond this value is then determined and the sum divided by the sample population. The orders taking more than 25.138 minutes are 67. The percentage is . John has a 66.5% of delivering his orders. His chances of delivering are almost three times, the deal is viable and John should consider delivering the orders on football Saturdays. Based on the sampled data, John offers the guarantee on this busy day. The percentage of the Saturday deliveries would result in a customer receiving a free order is 33.5%. The inference has enabled us to make a generalization of the sample to population and parameter estimates(Saeed, 2014). Hypothesis test has enabled John to determine the viability of Saturday guarantees. By using the T-Test, differences in means across two subgroups, we assume interval scale measure of dependent variables. Saturday offer was authenticated after conducting a formal hypothesis testing to help John decide whether to offer the delivery guarantee or not.

I would urge John to make arrangements to increase the number of employees working on football Saturdays in order to improve his Saturday delivery times. He can hire workers into work in weekend shifts and outsource extra drivers. This will not only increase deliveries but also make sure that orders are delivered before the guarantee expires. The time taken to reach the client will reduce if drivers pick the order on time.

Reference

Saeed, G. (2014). Fundamentals of Probability, (5th Eds). New Jersey : Prentice Hall