An organization’s ability to transform inputs into outputs is deter-mined by the level of its transforming resources (Figure 6.2), which include its:
Facilities
Technology
Workforce
Ability to acquire inputs, including financial resources.
When capacity management decisions are being made, the effects of each type of input on the operation’s ability to perform work must be considered. For example, the number of patients that can be seen in a hospital department depends on the number of staff employed, the
Transforming inputs Facilities
People Technology
Transforming inputs Material
People Information
Capacity Transformationprocess Outputs
number of beds available, and the availability of operating theatres and other specialized technologies. The number of automobiles that an assembly plant can produce will be limited by the number of workers, the process technology, and the availability of inventory.
Facilities
At the level of a manufacturing plant or service facility, operations management is concerned with determining the level of resources necessary to support strategy or alternately maximizing the level of outputs at a given level of resources. Capacity management here will be concerned with both the absolute level at which the operation can produce outputs and the range and/or mix of outputs that can be produced. This is important because one of the ultimate goals of a business organization is to generate profits, not to maximize invest-ment in assets.
In the long term, organizations match capacity with demand through changing the number, location and processing capacity of facilities. At the organizational level, the number and location of facilities is a strategically important decision that will affect the total output of the organization. At the operational level, a major influence on the capacity of an individual manufacturing or service facility is the physical space available.
Facility location is important for operations that involve either production facilities manufacturing physical goods or service facilities that need to serve customers through direct customer contact. Facility location decisions are influenced by various factors, including the locations of customers, suppliers and workers, how local conditions affect business operations, and costs of doing business (including infrastructure). A good review of these factors can be found in Michael Porter’s book The Competitive Advantage of Nations (Porter, 1990).
Figure 6.2 The effect of capacity in the transformation model.
An organization may decide to centralize the production of all of its outputs in a single large facility, or to invest in multiple facilities, either located close to markets or specializing in a particular output or range of outputs. Organizations may use a ‘hub and spoke’ network for linking facilities; this is a popular arrangement for airlines and overnight package delivery companies. The London Underground is an example of a highly centralized system; nearly all the tube lines are laid out so that it is difficult to go from one point on the periphery to another without passing through the centre of London (with the exception of stations on the Circle line).
Physical location is no longer central for some types of operations.
The rise of virtual organizations and the increasing amount of transactions conducted over the telephone, dedicated communica-tions systems and the Internet means that availability to customers through electronically-mediated means, rather than physical location, is becoming increasingly important to customer choice. We have already discussed the ability of banks to deliver financial services through multiple channels, including face-to-face transactions, ATMs, telephone banking, dial-up services, and over the Internet. Support services such as call centres and data processing can be located anywhere – some remote fishing villages in Scotland have become major players in call processing, and data processing for major organizations can be done in India overnight for records updating.
Work is also being done within organizations on a remote basis;
teleworking and telecommuting are becoming popular alternatives to commuting to the office via crowded roads or railways.
Economies of scale
In deciding the best size for a manufacturing or service facility, managers generally try to select a size that minimizes the average cost per unit of output over the life of the facility. You should already be familiar with the concept of fixed and variable costs (Figure 6.3). Fixed costs remain constant over a range of volume of outputs, whilst variable costs are proportional to the volume of outputs.
The concept of economies of scale suggests that costs decrease as the volume of outputs increase, because fixed costs can be spread over a greater number of units of output whilst variable costs remain the same. Organizations often use the concept of economies of scale to find an optimum size of facilities based on the decrease in average cost per unit of output as the volume increases. However, average cost per unit doesn’t decrease forever, because the price of many inputs will increase in a ‘lumpy’ way with increasing volume, especially when
Cost
Volume Total cost
Variable cost
Fixed cost
resources must be acquired externally. For example, heating and air conditioning equipment comes in standard sizes rather than being customized.
The optimum family size, according to food manufacturers, is four or six, as we can see from the fact that food products are generally packed in lots of four or six, but never five! Similarly, transportation vehicles such as coaches come in fairly standard passenger ranges (although the passenger capacity of an aeroplane can be varied by allocating more or less space to economy, business and first-class compartments, and by varying the space between seats and the width of the seats).
Figure 6.4 shows how economies of scale influence facility size. The average cost per unit of output has been plotted across a range of capacities for facilities A, B, C and D of increasing size. Within each plant, there is an optimum level of capacity that minimizes the average per unit cost for that plant. Across all the plants there may be an operating level that offers a lower average per unit cost than the other plants; however, this plant and operating level will be selected only if it is also the best match for the level of market demand.
The power of economies of scale is illustrated by the rise of superstores and hypermarkets in retailing. The retail organization can spread overhead costs across a much larger range of products and wider customer base, so that the cost per item sold is much lower than in conventionally-sized retail stores. They are also generally built outside town centres, not only because more space is available there, but also because land and building costs are cheaper. With a much Figure 6.3 Fixed and variable contributions to total cost.
Average
lower cost structure, these stores can undercut town-centre shops; this has led to the ‘hollowing’ of many high streets in the UK. (You might also know that recently there has been a move by the same companies whose superstores caused a migration of stores and shoppers from town centres back into town centres, with much smaller outlets such as Tesco Metro.)
In general, the concept of economies of scale suggests that there is an optimum level of capacity that minimizes the average per unit cost for all types of organizations. However, manufacturing facilities tend to be large in scale and centralized, whilst customer-processing facilities tend to be smaller in scale and close to their customers. That said, service operations that support customer processing (such as call centres, data-processing or other facilities) are more like manufactur-ing operations, and may be large, central sites supportmanufactur-ing many other local sites.
Layout In many services, customers are involved in some aspects of the transformation process. In a retail bank, counter personnel deal directly with customers to handle transactions and customer inquiries, whilst other staff deal with processing cheques, etc., and are rarely in contact with customers. Many operations separate high-contact and low-contact operations in time and/or in space. When separated, high-contact operations are described as front-room operations, whilst low-contact operations are called back-room operations.
Obviously, physical space alone will not completely determine capacity. For example, the physical space available at a call centre will Figure 6.4 Economies of scale for different-sized facilities.
determine the number of operators who can work at a given time, but capacity will also be determined by the number of telephone lines that the telephone exchange can handle simultaneously.
Technology
As Chapter 4 highlighted, process choice, including process type and layout, is highly related to where the operation is positioned on volume and variety.
After the facility’s physical size, a second influence on capacity is technology, which was discussed in Chapter 4. Technology includes the investments in machines, equipment, computer and communications systems, and technological know-how.
Technology costs can add significantly to the investment required in productive resources. These costs include not only that of purchasing the technology, but also the associated operating costs, including staff training. In addition, obsolete or worn-out equipment must be upgraded or replaced. This can be as often as every 1–2 years for computer and communications equipment.
Workforce
The third major determinant of an operation’s capacity is the size and capabilities of its workforce. Organizations consist of both direct and indirect workers. Direct workers participate directly in the productive process. In manufacturing, these include people who operate machines, assemble components or transport materials. In services, this usually describes the front-line employees who are in direct contact with customers or clients, and the back-room employees who support their work. Indirect workers include everyone else, and are there to support the direct workers.
The organization’s workforce includes permanent, part-time work-ers and temporary workwork-ers. In many countries, changes to the permanent workforce are restricted by law. The workforce may work overtime (or extra shifts) to increase capacity. The organization may also use subcontracting to extend its capabilities. Many organizations have begun to distinguish between core and peripheral workers, who cannot necessarily be distinguished by the length of their association with the organization. Microsoft, the computer software company, has traditionally employed a high proportion of its workers on a temporary contract basis, both for flexibility and to avoid paying high levels of benefits.
In some organizations, multi-skilling – training workers in more than one job so that if someone is absent or otherwise occupied another worker can step in to perform that task – can be used to maintain capacity.
In manufacturing, the use of highly integrated equipment and information technology means that fewer and fewer workers are needed to produce a given level of output. In the 1970s the trend toward increasing automation was argued to be leading inevitably towards ‘lightless factories’ – production facilities with no employees that could be started up and run unattended.
Service organizations generally (but not always) rely more on employees than on capital equipment. Normann (2000) describes services by whether they are personality-intensive or not. Services rely on employees who are skilled with information technology.
Measuring workforce capacity
Unlike machines and other automated equipment, workers tend not to work at a programmed, uniform pace. First, the actions and activities performed by humans are rarely as repeatable or repetitive as those performed by machines. Furthermore, one machine is usually very much the same as other machines of the same type, but people often vary considerably in the level of work that they can achieve.
Finally, people usually need time off, whereas machines and systems can often be run continuously over a long period.
People are also more flexible than automated systems in responding to changing needs and variations in the environment. In a famous study, Sutton and Rafaeli (1988) found that when stores are busy and there are many people queuing, convenience store clerks tend to spend less time serving customers and engage less in friendly behaviours such as smiling or thanking customers. On the other hand, when times were slow, the clerks and/or customers initiated small talk and engaged in more friendly behaviours in order to make work more interesting. In other words, the clerks focused on efficiency when there were a lot of customers queuing, but on social interaction when things were less pressured.
Because of this inherent variability in people’s work pace, special sets of tools and techniques have been developed to measure what work levels people can achieve under normal circumstances. Time and work measurement describes a set of tools used by operations managers to estimate the time taken to perform a task. The two goals of time and work measurement are to identify and eliminate wasted time, and to set time standards for tasks. Method study aims to eliminate unnecessary operations and waste.
Work measurement techniques include time study and pre-deter-mined motion time studies (PMTS). The data for such studies can come from records of past output, observations of work being done, or recordings of work being done. Standard time can be defined as the total time in which a job should be performed, including rest time.
Work study is often linked to the principles of scientific management, which was developed by F. W. Taylor during the 1880s and 1890s.
Taylor started out by studying ways to improve production in machine shops, where skilled machinists acted as subcontracts rather than workers as we understand today.
Based on his beliefs about how to organize machining operations efficiently, Taylor developed an approach to the organization of work that treated workers as another element in the machine that was the organization. A job comprised all the tasks performed by a worker.
Taylor broke jobs down into their simplest activities and simplified job designs so that each worker would only execute a limited range of skills in a particular job. Tasks could be broken down into individual activities called elements, and elements were made up of job motions, or basic physical movements.
The idea of specialization of labour was nothing new, as discussed in Chapter 1, but it was extended into a new context. The main idea underlying scientific management was that once jobs had been analysed and reorganized, precise time standards and production targets could be set up. Since workers were generally paid on a piece-rate system, where extra money could be earned by exceeding the standard target, setting piece-rate standards and pay was important to company profits. Taylor was probably more na¨ıve than malevolent in devising his system of scientific management, but in practice scientific management systems were often implemented as a means of reducing the amount paid to workers, and by 1920 labour resistance to Taylor’s methods in the USA was significant; European countries had not widely adopted Taylorism anyway.
Work study can help modern operations in many ways. For example, Brown (1994) observed how Work study methods were being used in quality initiatives in a number of plants in the USA and UK, and Adler (1993) reported how the General Motors/Toyota plant (NUMMI) used Work study as a central feature to manufacturing performance.