Example 13.1 in the book presents a nave capacity planning exercise and was criticized for using averages. Recall the concept of a "bottleneck" from Chapter 5, "Supporting Facility and Process Flows," and suggest other reservations about this planning exercise.

Background info:

Example 13.1: Capacity planning for cookies and cream - naive approach: An enterprising student is considering opening a "cookies and cream" shop in space that has become available in a food court. Observations of traffic during the lunch hour suggest that a potential peak demand of 50 customers, each ordering on average on ice cream sundae, six baked-to-order cookies, a 12-ounce self-serve soft drink, and spending 20 minutes at a table. A cookie sheet can accommodate a dozen cookies and baking time is 10 minutes. One server requires on average 6 minutes to take an order, mix a batch of cookies, and assemble the order. Capacity requirements are determined by calculating the units of facility, equipment, and labor needed to accommodate the anticipated peak demand. Facility requirements include the seats necessary to accommodate diners. We will use a relationship called "Little's Law," discussed later in the chapter, to calculate the seats required. Little's Law states that the average number of customers in a system (L) is equal to the arrival rate times the average waiting time. With 50 customers arriving during the peak hour and each staying approximately 20 minutes, or one-third of an hour, we need (50)(20/60)=16.7 chairs. Equipment requirements include the calculation of the number of cookie sheets needed. This is determined by dividing the total number of cookies ordered for the hour by the capability of one cookie sheet that is used for only 10 minutes per batch (i.e., reused six times per hour). Assume that orders can be combined to fill a sheet. Labor requirement is focused on calculating the number of severs required. As in the equipment calculations, we divide the total minutes of server time demanded for one hour by one unit of service capability )i.e., 60 minutes available for the hour). Caution needs to be exercised in implementing the results of such a naive capacity planning exercise. Excess capacity is required in a service system because variability in customer arrivals and service times is the expectation and creates idle capacity that is lost. As we shall see in the queuing model section, the capacity to serve must exceed the arrival rate to avoid out-of-control waiting lines. Because the calculations for capacity needs are based on averages, the results represent an infeasible solution to our capacity requirements. Our capacity planning analysis of Cookies and Cream will be revisited in Example 13.6 with a more sophisticated queuing analysis after our discussion of queuing models.