Question

1. McDonald’s makes the claim that it takes 90 seconds or less from the time a car stops at the order point to delivery of an order through the window. How can McDonald’s substantiate this claim when drive-thru times vary?
2. How does McDonald’s quantify the uncertainty surrounding its estimate of drive-thru service time?
3. How can the variability in drive-thru service times be quantified? Why is it important to understand variability?
4. Why is it important for McDonald’s to effectively communicate its statistical findings? What types of decisions depend on these data?

Answer 1

1. McDonald’s makes the claim that it takes 90 seconds or less from the time a car stops at the order point to delivery of an order through the window. How can McDonald’s substantiate this claim when drive-through times vary?

Even though drive-through service times at McDonald’s vary, they can back their claim by collecting data. Data allows McDonald’s to be relatively confident that the drive- through service time is, on average, within a certain range. The appropriate statistical inference procedure for this scenario is to construct confidence intervals for the average drive-through service time.

1. How does McDonald’s quantify the uncertainty surrounding its estimate of drive-through service time?

When constructing a confidence interval for a mean, the uncertainty surrounding the estimate depends on the level of confidence desired, the variability in drive-through service times, and sample size. The more data collected, that is the larger the sample size, the better the estimates. Also, better estimates can be obtained by reducing the variability in drive-through service times, say through quality improvement efforts.

1. How can the variability in drive-through service times be quantified? Why is it        important to understand variability?

Measures of variability that can be used for drive-through service times are the range, variance and standard deviation. The standard deviation is used in constructing a confidence interval for the mean. It is important to measure (and monitor) the variability because even if the mean service time is on target, a large amount of variability means that too many customers will have a poor drive-through experience. In addition, by

understanding the sources of variability (inadequate staffing, inefficient layout, inappropriate equipment) efforts can be made to improve the process and reduce variability. Data collection after making improvements can determine whether improvement efforts were successful.

1. Why is it important for McDonald’s to effectively communicate its statistical findings? What types of decisions depend on these data?

It is important to communicate statistical findings in everyday language for management to make decisions about staffing (e.g., using a wireless order taker), layout design (e.g., side-by-side drive-through), and capital investments.