Scheduling Workers in Service Operations Operations Management Assignment Help

Scheduling Workers in Service Operations

Why Scheduling Is Important in Services

As discussed previously. one of the main distinctions between manufacturing and service operations is the customer’s direct interaction with the service delivery process. Because of this interaction, the determination of the proper number of workers to schedule at any particular  tme is critical to the success of every service operation. On one hand, scheduling too few workers results in unnecessarily long customer waiting times. On the other hand, scheduling too many workers results in overstaffing and the incurrence of unnecessarily high labor costs, which negatively affect profits. The service manager. consequently, needs to schedule workers in a way that effectively satisfies customer demand while minimizing  unnecessary labor costs.  The cost of labor in most services is a major cost component, often running 35 percent of sales and higher. For some services, in fact, virtually all of the direct costs can be considered as labor (examples of these types of services include consulting, legal work, home care nursing, and hair salons). Thus a small but unnecessary increase in labor can have a very significant impact on a firm’s profits.

A Framework for Scheduling Service Workers

Work schedules in service operations are usually developed on a weekly basis for several reasons. First, there are state and federal laws that specify the maximum number of hours and/or days an employee can work in a given week, after which overtime premiums must  paid. Second, the distinction between full-time and part-time workers is often made on he basis of the number of hours worked in a calendar week. Full-time versus part-time status often determines the ben fits paid by the employer. and may be related to union

contracts that specify the minimum number of hours workers in each category may work. Finally. many workers, especially hourly workers. are paid on a weekly basis that is often mandated by local or state laws.  The procedure for developing a schedule for service workers can be divided into the following four major elements, as illustrated in Exhibit 12.8: (a) forecasting customer demand, (b) converting customer demand into worker requirements, (c) converting worker requirements into daily work schedule, and (d) converting daily work schedules into weekly
work schedules.

Forecasting Demand

Since the delivery of most services takes place in the presence of the customer, the customer’s arrival rate directly correlates with the demand level for the service operation. For example, the customer must be present at a restaurant to partake in the meal being served; the patient must be present in the hospital to receive treatment. In addition to the customer’s presence at the point of service, the potential for high variability in the pattern of customer demand makes it extremely important for service managers to efficiently schedule workers. The first step, therefore, in developing a schedule that will permit the service operation to meet customer demand is to accurately forecast  heat demand. There are several patterns of demand that need to be considered: variation in demand within days (or even hours), variation across days of the week. variations within a month. and seasonal variations. Because demand is often highly variable throughout a day. forecasting within-day variation is usually done in either hour or half-hour increments. Today, with the use of computers and more sophisticated point-of-sale (POS) equipment. the ability  to record customer demand in even. shorter time increments is possible (for example. IS-minute time intervals). To develop a forecast we need to collect historical data about customer demand. The actual number of customers expecting service in a given time interval (that is. half hour or hour) is the preferred data. Fortunately, there is a wide range of POS equipment available that can capture this type of data, and, in many cases. even download it onto a computer for subsequent analysis.

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