Sales per customer, however, began decreasing above a certain threshold (about 5.76 diners per server per hour, a level experienced by only some of the servers at certain times). The servers spent more time taking orders and delivering food and had less opportunity, and less motivation, to try to get the customers to buy additional items or expensive drinks, the authors argue. The higher workload could also make the servers distracted or fatigued, contributing to the slump in performance.
Overall, the restaurants’ average of 4.3 diners per server meant it was significantly overstaffed and that its servers were falling short of the optimal workload for hourly sales by almost a customer and a half.
Using regression analysis, the authors calculated that the optimal staffing levels would result in a rise in hourly sales per customer of 41 percent, given that a server’s selling of an additional appetizer, dessert, or glass of wine is worth that percentage of the cost of an entrée. But they also calculated that increasing the hourly workload to the optimal level would cost about 6 percent in sales because diners would spend about 2.5 percent less time having their meal, slightly reducing opportunities to buy more food. This leaves the restaurants with a 35 percent boost in sales.
Additionally, the authors found that the restaurants were overstaffed more than 75 percent of the time by an average of 1.14 servers per hour. Cutting those excess staff hours would save about 20 percent in labor costs, the authors calculated.
For service-sector businesses that rely on customer sales to drive profits, balancing employee workload and performance can have a significant impact on a firm’s bottom line. Based on a case study of a large restaurant chain, this paper pinpoints an optimal staffing level to maximize sales and finds that the restaurants could reduce the number of hours that their employees work and yet increase their revenue.