PERATIONS MANAGEMENTLEARNING OBJECTIVES On completion of this chapter, you should be able
to:
•explain what is meant by the term operations management;
•understand some of the basic concepts of operations management;
•distinguish between different types of operations;
•appreciate the growing importance of service operations; and
•understand the impact of globalization on the practices of operations management. H&M: A
GLOBAL FASHION COMPANY
From its humble beginnings in 1947 as a single shop in Sweden, H&M is now one of the biggest
names in the retail fashion industry. H&M employs over 130,000 people, both in Sweden and in its
nearly 4,000 stores, which are in over 60 countries, right the way across the globe, including most
countries in Europe, as well as many in the Middle East, Africa, Asia and the Americas. It plans to
open further stores (it has a target of increasing the number of stores by 10–15 per cent each year),
as well as expanding its online sales operations by rolling out its digital presence to an increasing
number of countries. H&M’s digital ambition means setting up not only a dedicated website to serve
each new country, but also the physical systems that can ensure goods ordered on it will be delivered
to customers in that country.
The most visible part of H&M’s operations is its stores. The company says it wants these to provide
an ‘inviting, inspiring and exciting experience’ to shoppers. While every store is unique, any is
immediately recognizable as H&M from its signage, window displays and internal layouts. All stores
seek to place the clothes centre stage through the use of internal displays that aim to provide styling
tips and inspiration. H&M’s online stores try to emulate this experience in the virtual world, while
providing additional accessibility for customers who can’t easily get to H&M physical stores, and
enhanced levels of service by enabling customers to view and order a much wider range of
merchandise (and in many more sizes) than would be possible in any physical store.
However, the stores are only the end point of a much longer supply process. This starts with design.
All of H&M’s garments are designed in Stockholm by its in-house team of clothing designers, patternmakers and print designers. They aim to provide something for men, women, teenagers and children,
whatever their taste or style.
In contrast to the design process, H&M does not produce any of its garments in-house. Rather, it
draws on a network of over 1,900 factories owned by as many as 900 independent suppliers, which
are based in countries such as China, Turkey, Bangladesh, Cambodia and India. H&M views its
suppliers as long-term strategic partners who manufacture its products, including being responsible
for sourcing the necessary
fabrics (mainly cotton) and the other components needed. H&M’s logistics and distribution
operation must then ensure that the right goods end up in the right quantity as required by each
store. Factory shipments are transported, mostly by sea and rail, to H&M’s logistics centres, which
are strategically located in the geographic vicinity of its stores in each region. Stores do not hold
backup stocks, and so must replenish as required from the distribution centres. In 2013, H&M
launched its Garment Collecting Initiative, which enables customers to hand in clothes that they no
longer want for reuse or recycling. This is aimed at creating a closed loop in textiles, so that nothing
ever goes to waste. The first H&M garments containing materials from the Garment Collecting
Initiative were launched in 2014 – denim garments that contained 20 per cent recycled cotton.
Source: www.hm.com (accessed 8 September 2016).
POINTS TO PONDER AS YOU READ THIS CHAPTER:
»Notice the different types of operations occurring throughout H&M’s business (e.g. design,
production, logistics and distribution, retail). Some of these are manufacturing operations, and some
are service operations. Each uses different types of resources to produce different kinds of outputs.
»Notice how H&M’s shops rely on a complex interconnected global supply network to ensure that
goods are available to customers.
»Think about what led H&M to operate on such a vast global scale and about the challenges posed in
managing all of these operations, both individually and collectively. INTRODUCTION
Operations management is crucial to the lives of all of us. That is because operations management is
responsible for the creation and delivery of all the products and services that we need for our daily
lives, including all the food that we eat, the clothes that we wear, the transport we use, the health
services that we receive, and so on. All of these were brought to you courtesy of operations
management. Unless you live as a self-sufficient hermit in an isolated cave, there is unlikely to be any
aspect of your life that is not entirely dependent upon operations management. That is because
nearly every physical product or intangible service that you consume or use is created and delivered
by some kind of business organization. And the operations function is the part of that organization
that is responsible for producing the goods and services it supplies to its customers. All organizations
have operations functions, although they often go under other names. These often reflect the
specific activities that they carry out, for example catering, distribution or nursing. There is a
misconception that operations management is only concerned with manufacturing activities.
Although many of the concepts on which the academic study of operations management is based do
have their origins in the manufacturing industries, many are equally applicable to services.
Conversely, recent advances in the study of service operations have yielded valuable insights into the
management of manufacturing operations. The distinction between manufacturing and services is in
many respects artificial and increasingly irrelevant because most products have some element of
service accompanying them. For example, when you buy a new computer (an entirely physical
product), you assume that you are also buying access to aftersales services, such as operating
guidance, software updates and repairs. Equally, many services have a tangible product as an integral
part of what is delivered to the customer. For example, as a passenger on an airline (an entirely
intangible service), your flight, especially if it is long-haul, is usually accompanied by the provision of
on-board food and drink (an entirely physical product).
Operations management is concerned with the management of the resources and processes
required by an organization to produce goods or services for customers.
The operations function is that part of the organization that has the responsibility for operations
management.
Operations management is the most exciting of the business disciplines. Marketing is concerned with
identifying and creating customer needs. Finance is concerned with ensuring that the organization
has the necessary financial resources to conduct its business. Similarly, human resource
management is concerned with ensuring that the organization has the necessary human resources it
needs. Operations management is concerned with the management of the resources and processes
required by an organization to produce goods or services for customers. The operations function can
best be thought of as the ‘doing’ part of the organization. It is where the action is. Operations
management is critical to the success or failure of an organization. Any organization exists to deliver a
service of some kind and/or to make a product. If its operations management fails, then the
organization will fail. The operations function is responsible for the majority of the organization’s
costs, assets and people, typically accounting for 60–70 per cent of each (Hill, 2005). Operations
management is important because of its direct impact on costs. No organization can be successful
unless its operations are managed cost-effectively. However, operations management is also
important because of its impact on non-cost factors such as the quality, availability, timeliness and
reliability of the goods and services provided by the organization. All customers judge the value of
what they receive by some combination of these factors. No organization will be successful for long
unless it provides goods and services in a way that satisfies its customers by providing them with the
value they seek.
The context in which operations management is practised has been changing in recent years. Until
comparatively recently, most production processes in most organizations were organized and took
place within national boundaries. Although manufacturers may have imported the raw materials
they needed, most produced goods primarily, if not exclusively, for local consumption. Similarly, it
was rare to find any service that was not produced and consumed locally. It was unusual to find
production processes that crossed national boundaries. This has been changing for some time as the
forces of globalization have led to the internationalization of operations. For many organizations, the
last decade has seen an acceleration of the trend towards the fragmentation of production
processes. Today, many operations processes cross international boundaries in ways that were not
previously possible. For example, the cup of coffee that you buy from your local Starbucks coffee
outlet may depend on operations taking place in as many as 19 different countries. The coffee beans
may come from plantations in countries as diverse as Kenya, Saudi Arabia, Indonesia and Colombia.
The beans would have then been sent to one of the company’s roasting, manufacturing and
packaging plants in the US. The paper for the cups and napkins could have been produced from
forests in Sweden. The sugar could have come from Brazil. The milk could have come from Australia.
All the required final products would then have to have been transported to your local Starbucks,
one of 22,000 outlets worldwide in over 60 countries. Neither is Starbucks exceptional.
Improvements in transport systems have made the movement of materials much easier and cheaper.
New centres of manufacturing have emerged in newly industrialized economies (NIEs), such as
China, India, Brazil and Mexico, that offer resources, particularly labour, at a fraction of the cost
available in traditional manufacturing locations. Workers, especially those with the most sought-after
expertise, can move between countries with much greater speed and ease than was the case in the
past. Today’s financial systems and markets enable virtually unlimited amounts of capital to be
transferred across the world instantaneously. And, perhaps most importantly, unlimited quantities of
information, including new ideas and innovations, can be communicated and shared almost
instantaneously across the world thanks to the Internet. These factors have all become increasingly
important not only to manufacturing, but also in many services, and particularly in information- and
knowledge-based contexts.
Internationalization is the process of expanding business operations across international boundaries.
At first, this might only involve exporting or importing goods and/or services. But it might go on to
involve the establishment of production facilities in other countries, as well as facilities to support
sales, research and development, and other activities in foreign countries.
A newly industrialized economy (NIE), sometimes also termed a newly industrialized country (NIC), is
a country that has undergone a considerable level of industrialization in the recent past, switching its
primary economic activity from agriculture to manufacturing, and possibly services. NIEs are not
quite yet at the status of the industrialized nations of the West, but are more advanced than the
countries of the Third World.
The transformation process is the system by which inputs of resources (e.g. people, equipment,
materials, energy, information) are converted into outputs of goods and services.
THE TRANSFORMATION MODEL
Any operation can be depicted as a transformation process that converts inputs into outputs of
goods and services (see Figure 1.1).
For the inputs, it is useful to distinguish between:
»The primary inputs that are themselves transformed to become part of the output of the operation.
These are sometimes referred to as ‘transformed resources’ (Slack et al., 2013). Primary inputs can
be materials and/or information and/or customers.
»The resources necessary to carry out the transformation, but which do not themselves form part of
the output. These are sometimes referred to as ‘transforming resources’ (Slack et al., 2013). Figure
1.1 The input-output transformation model for operations
Source: adapted from Operations Management, 7th edition, by Nigel Slack, Alistair Brandon-Jones
and Robert Johnston, Pearson Education Limited. © Nigel Slack, Stuart Chambers, Christine Harland,
Alan Harrison, Robert Johnston 1995, 1998. © Nigel Slack, Stuart Chambers, Robert Johnston 2001,
2004, 2007, 2010. © Nigel Slack, Alistair Brandon-Jones, Robert Johnston 2013.
These can typically be classified as:
»Facilities: These are the resources that are necessary to undertake the operation, but which are not
used up in the operation. Typically, these include the land, buildings, equipment and vehicles used by
the organization to perform the operation. These resources are usually intended to be used over
several years. Consequently, they are normally designated as fixed assets by accountants, and their
value appears in the fixed assets column of the balance sheet.
»Consumables: These are the resources that are used up as part of the operation. Examples include
the energy necessary to power buildings, plant and machinery, and the materials necessary to
maintain, repair and operate them (often referred to as MRO supplies).
»People: The human resources necessary to undertake the operation. These will usually include the
staff of the organization. However, employees of other organizations might also be involved in the
transformation process, for example those belonging to the suppliers or subcontractors of the
organization undertaking the operation.
The transformation model sees operations management as those activities that are concerned with
how these resources are managed in order to produce the required outputs of goods and services.
DIFFERENT TYPES OF OPERATIONS
Operations can be classified into three different types depending upon which type of primary input is
principally being transformed in the operation:
»Material-processing operations are those in which materials are transformed either from one form
to another, and/or from one place to another. Manufacturing operations in which raw materials and
components are transformed into finished products fall into this category (e.g. manufacturing a car
or producing a garment). Other material-processing operations include mining, and the transport,
storage and distribution of goods in warehousing and retailing operations.
»Information-processing operations are those in which information is transformed from one form to
another and/or from one place to another. There are many examples of information processing,
including accountancy, banking, financial services, telecommunications and research of all kinds.
Nowadays, it is difficult to think of information-processing operations that do not involve the use of
computers.
»Customer-processing operations, in which the customer is transformed by the operation. There are
many examples of this type of operation, including medical services (e.g. hospitals) in which sick
people are, hopefully, made well, education, where people are transformed by gaining additional
knowledge or skills, and entertainment, where people are transformed by the emotional benefit
gained from the event.
While one of these types of processing often predominates in any particular operation, many
operations also typically involve two or even all three types. For example, a restaurant processes
both materials (food) and customers; a book publisher processes both information (the text for the
book) and materials (the paper, ink, etc.); and an airline processes customers (passengers) and
materials (their baggage). TOYOTA: THE WORLD’S NUMBER ONE
With global sales now at 10 million vehicles per annum and climbing, Toyota finds itself as the
world’s leading auto manufacturer. US giant General Motors, which had previously held this title for
74 years, was dethroned in 2006, and the Japanese automaker has not looked back since. In a
financial climate in which most of the top automakers have experienced declines both in sales and
profits, Toyota stands out for its burgeoning financial returns, which are not restricted to the
established US market, following investment in China’s developing market. Environmental and
technological advancement, in the form of its part-electric, part-petrol hybrid models, also creates
healthy demand. Toyota’s Lexus subsidiary also taps into the US luxury market, propelled in 2016
through its RX crossover model, which exceeded sales forecasts.
Despite the fact that it dates back to 1937, Toyota rose from relative obscurity in the 1950s through
Taiichi Ohno’s development of the Toyota Production System (TPS). Based on Japanese principles
such as jidoka (referring to human automation), muda (elimination of waste) and kaizen (continuous
improvement), TPS enables greater cohesion within the manufacturing process, particularly with
regard to team- and management-based tasks. In an industry that is so dependent on intricate
supplier collaboration, it has been claimed that TPS helps to achieve this end, insofar as it minimizes
defects. The eradication of such design flaws also allows newly created products to reach the
customer in a shorter time than can be achieved by other companies, and with a greater level of
quality control. Getty Images/Hero Images
This approach to production has been researched and emulated by a number of international
carmakers and is now considered the industry gold standard, while also finding traction within other
sectors. Now articulated as ‘lean’ production, numerous service environments have also
incorporated this approach. One such surprising application of TPS methodology can be found within
the field of healthcare, in which the traditional focus upon meeting objectives is replaced with the
prioritization of processes. Each role within the organization is defined in terms of key competencies,
and, as these are met, patient needs are satisfied with greater consistency.
TPS has been regarded as the secret to Toyota’s success, implementing increased flexibility and
productivity while eradicating many of the production errors that plague other car manufacturers. As
a result, the company does not need to resort to competitor-minded discounts in order to satisfy a
customer base that is happy to pay for quality. As Toyota continues to outperform its rivals for a
fourth consecutive year, it now contemplates consolidating its position through business
partnerships with manufacturers such as Daihatsu and Suzuki. And yet, at the heart of this
increasingly outward-looking company remain the streamlining qualities facilitated through the TPS,
which acts as an integral foundation for such growth.
Sources: Magee, D. (2007) How Toyota Became #1, 1 December, available at:
www.ft.com/content/c2cd0f74-9c76-11dc-bcd8-0000779fd2ac (accessed 3 October 2016).
Toussaint, J., Conway, P.H. and Shortell, S. (2016) The Toyota Production System: What Does It Mean,
and What Does It Mean for Health Care?, 6 April, available at:
http://healthaffairs.org/blog/2016/04/06/the-toyota-production-system-what-does-it-mean-andwhat-does-it-mean-for-healthcare/ (accessed 3 October 2016).
Toyota Press Room (2016) Toyota Motor Sales Posts January 2016 Results, 2 February, available at:
http://corporatenews.pressroom.toyota.com/releases/toyota+lexus+scion+january+2016+sales+
release.htm (accessed 3 October 2016).
Treanor, S. (2014) Toyota Retains Number One Slot in Global Care Sales, 23 January, available at:
www.bbc.co.uk/news/business-25860234 (accessed 3 October 2016).
QUESTIONS
1.What type of operations are most important to Toyota?
2.To what extent does Toyota’s success depend on its operations? SERVICE OPERATIONS
Operations can be classified more simply in terms of their outputs, as either goods or services. The
factors that distinguish them are:
»Tangibility: Goods are physical products that can be touched, seen, tasted or smelled. As physical
entities, goods can be stored and transported. The ownership of goods can be transferred from the
supplier to the customer. Services, on the other hand, are intangible, and therefore unlikely to
possess any of these properties.
»Simultaneity: Services are distinguishable from goods in that their production and consumption
usually takes place simultaneously. As such, it is usually not possible to store a service that has just
been produced for consumption at some time in the future. Normally, customers have to be present
to receive the service when it is produced. On the other hand, goods can usually be stored ready for
future consumption by a customer.
»Customer contact: Because of their intangibility and simultaneity, services normally require some
degree of contact with the customer, although the degree of that contact can vary. Similarly, some
services are much more labour-intensive than others, and might involve the customer coming into
contact with large numbers of employees of the service delivery organization, such as in a visit to a
hospital or staying in a hotel.
»Quality: Because of the nature of the output of a service operation, it is much more difficult to
define and measure the quality of a service. The quality of a product can be defined and measured in
terms of its functionality (i.e. its fitness for the purpose for which it is intended). The quality of a
service, on the other hand, can often only be judged by its recipient. Service quality is dependent on
the perception of a customer. Such perceptions may vary between one customer and another, and
between the customer and the service deliverer. As such, service quality often depends upon the
psychological state of a customer at the time of consumption. Indeed, some services are intended to
change a customer’s psychological state.
Services are the intangible outputs from an operation.
It is possible to think of examples that equate to the extremes of pure goods (coal mining) and pure
services (psychotherapy). However, a closer consideration of the outputs of most operations reveals
that it is rare to find such extremes. Usually, there are elements of service in most goods-producing
operations. For example, even extractors of commodity goods such as coal or oil typically provide
their customers with information about their chemical composition or offer technical advice on their
use. Similarly, even producers of a highly customized service such as management consultancy will
usually produce some tangible output, such as a written report of some kind. It is usually more
helpful to think of the outputs of operations as being located somewhere on a continuum between
pure services and pure goods (see Figure 1.2).
Many service operations are different from those in manufacturing, in that they usually require the
operation to have some degree of contact with the customer. Organizations that treat their
customers in the same way that they treat the inanimate objects that are materials are neither likely
to retain existing customers nor attract new ones.
The study of service operations has led to the development of some useful concepts in addition to
those that have emerged from the study of manufacturing. One such concept is that of the
difference between the front office and the back office. The area in which contact with customers
occurs is termed the front office. This primarily involves customer-processing operations. The area
where there is normally no contact with customers is termed the back office. This may involve
information- and/or material-processing operations (see Figure 1.3).
The transforming resources required in the front office are likely to be significantly different than
those needed in the back office. In particular, operations in the front office need to revolve around
the customer. The people that work in the front office are likely to require quite different skills than
those in the back office. Front office staff need high levels of interpersonal skills if they are to interact
successfully with customers. The physical resources used in the front office, buildings, machinery and
equipment may also need to be quite different from those in the back office. Indeed, the front and
back offices may well be physically located in quite different places. However, the relationship and
interaction between front and back office operations is often a key part of the management of
operations.
The front office is the area of an operation in which contact with customers normally takes place.
The back office is the area of an operation in which there is normally no contact with customers.
Figure 1.2 The goods-services continuum Source: inspired by information in Slack et al. (2013). Figure
1.3 Front office/back office operations
Source: adapted from Operations Management, 6th edition, by Nigel Slack, Stuart Chambers, and
Robert Johnston, Pearson Education Limited. © Nigel Slack, Stuart Chambers, Christine Harland, Alan
Harrison, Robert Johnston 1995, 1998. © Nigel Slack, Stuart Chambers, and Robert Johnston 2001,
2004, 2007, 2010.
WHEN THINGS GO WRONG HONG KONG DISNEYLAND: THINGS CAN ONLY GET BETTER However,
after opening its gates in September 2005, it became clear that there were some significant problems
in its operations. Despite the fact that, at 30,000 visitors, the park had the lowest capacity of all
Disneyland parks, this was revealed to be an unmanageable number when 29,000 locals converged
on Hong Kong Disneyland on the day prior to its grand opening. Unfortunately, these prospective
visitors fell victim to the irony of 45-minute waits for fast food and ride queues of up to two hours, a
fact not wasted on local media, who were quick to comment on the park’s chaotic management. The
day after, on the park’s official opening, a seemingly manageable 16,000 visitors gained entry, with
approximately one-third comprising of mainland Chinese park-goers, and it was this group that locals
blamed for, among other things, smoking in non-designated areas, GRAPHEAST
Hong Kong Disneyland’s final construction on the reclaimed land of Lantau Island in 2005 marked the
culmination of a $1.8 billion joint partnership with the Hong Kong government. Targeting not only
the flourishing wealth found among China’s citizens, the park also attracted a significant number of
visitors from surrounding South East Asia. To this end, designers wished to incorporate elements of
Chinese tradition and culture through the use of feng shui in its stylistic composition. Reportedly,
such design choices even dictated the rotation of the front gate by 12 degrees, which a feng shui
specialist assured would lead to greater prosperity in the park’s future. Clearly, park management
were leaving nothing to chance. queue-jumping, public urination and spitting. Park staff also bore the
brunt of customer blame on the basis that such visitors should not have been admitted entry, and,
even on the opening day itself, it was reported that staff were discourteous and unhelpful.
For Hong Kong Disneyland, the problems did not end on its opening day, as approximately 50 rides
experienced technical difficulties, leading to the employment of safety protection systems. As a
result of such shutdowns, there were six instances of visitor sickness and minor injuries sustained. In
addition, worker complaints included commuting, rota and management communication problems.
Marking perhaps the nadir of the park’s woes, during Chinese New Year, in February 2006, a ticketing
malfunction led to entrance having to be refused to new visitors who had valid tickets, because the
park was already full to capacity. As a consequence of the over-ticketing fiasco, some prospective
park-goers stormed their way in, and the sight of a child being passed over spiked gates to his openarmed parents who waited inside the park provided local television with a poignant visual example
of the park’s inadequate planning.
Since then, further complaints have been made regarding the park’s lack of size, attractions and
competent staff. Disney enthusiasts also make unfavourable comparisons between Hong Kong’s 22
major attractions, compared with Tokyo’s 45, and Paris and Florida’s 44 and 65, respectively. This
considered, Hong Kong bears the highest cost per ride of all its equivalent parks. As previously
alluded to, tensions between Hong Kong locals and mainland Chinese visitors can quickly escalate,
and such visitors lamented the park’s lack of Mandarin instruction, which is the dominant language
of China. This problem arises from the fact that Cantonese is the language of southern China,
including Hong Kong, but it is unintelligible to a purely Mandarin speaker, which remains the
language of the Chinese government. One implication of this linguistic impasse was found in the live
shows, in which the characters spoke no Mandarin and the props and voice-overs on all but one of
the rides were in English. The resort’s management acknowledged such developmental difficulties,
vowing that such problems remained common to all new ventures and that improvements could be
made.
At the peak of the park’s problems in 2006, even the Hong Kong government was forced to
call on Disneyland to make improvements both to entry procedures and ticketing. Since this
intervention, park pricing, opening times and ticket policy have been altered in order to spread
admittance throughout the week and ease the strain that is placed on the park infrastructure. Datespecific tickets are now used to ease congestion during busy periods, and particularly Chinese
holidays. Better staff training now ensures that Cantonese, English and Mandarin can be spoken and,
along with multilingual guide maps, these help to ensure that customer satisfaction is achieved
across the broad range of visitor nationalities.
A new induction programme, aimed at quickly introducing mainland tourists who are unfamiliar with
the Disney brand, has also been introduced. Clearly, without the previous childhood exposure to
such characters, a visit to the park would represent an extremely disorientating, and perhaps even
alienating, experience, so Disney has worked to minimize this possibility, and, in doing so, maximize
brand exposure. To this end, the park has developed a pre-show movie that can be shown to its
visitors when they initially get to the park. Upon entry, visitors are taken to an area for approximately
15 minutes, where they are regaled with the cornucopia of Disney characters and their associated
attractions. This allows Chinese tourists to learn about Disney’s history while rendering Hong Kong
Disneyland as increasingly attractive to Chinese travel agents.
Finally, in 2012, the park turned its first profit, following six years of continual losses. Attraction
investment has facilitated consistent visitor figures, and the park finds itself in the prestigious group
of the world’s top 15 most visited theme parks. And yet, significant threats are posed by a struggling
Chinese economy and the rival Disneyland Shanghai park, which is three times its size. However, as
Hong Kong Disneyland has shown, the Shanghai park must continue to closely monitor the 10,000
employees who worked on its opening day in order to make continual improvements to customer
experience.
Sources: Boland, R. (2016) What Is the Difference between Mandarin and Cantonese?, 30 March,
available at: http://gohongkong.about.com/od/travelplanner/f/languages_mandarin_cantonese.htm
(accessed 3 October 2016).
Bradsher, K. (2006) At Hong Kong Disneyland, The Year of the Dog Starts with a Growl, 4 February,
available at: www.nytimes.com/2006/02/04/world/asia/at-hong-kong-disneyland-the-year-of-thedog-starts-with-a-growl.html (accessed 3 October 2016).
Holson, L.M. (2005) The Feng Shui Kingdom, 25 April, available at:
www.nytimes.com/2005/04/25/business/worldbusiness/the-feng-shui-kingdom.html?_r=1
(accessed 3 October 2016).
QUESTIONS
1.What were the main problems experienced by Hong Kong Disneyland in its ‘front office’
operations?
2.What seem to be the main causes of these problems?
3.What more could have been done to overcome these problems? TAKING IT FURTHER Much of the
academic discipline of operations management is underpinned by the ideas of ‘systems theory ’, also
often referred to as ‘systems thinking’. Investigate the ideas of systems theory and systems thinking
to gain a better understanding of what they mean when applied to the management of business
operations. In particular, note the difference between an open and closed system. Consider the
extent to which operations systems in organizations are open or closed, and what this means for
their management. THE CHANGING NATURE OF OPERATIONS MANAGEMENT
In recent years, the way both academics and practitioners think about the subject of operations
management has been changing. This has been reflected in the content of operations management
as an academic discipline. The most notable of these are:
A supply network is the set of interconnected relationships between all the parties that supply inputs
to, and receive outputs from, an operation (including the suppliers’ suppliers and their suppliers,
etc., and the customers’ customers and their customers, etc.).
Moving beyond the factory
The roots of operations management lie in manufacturing, and for many years the subject focused
almost exclusively on what went on within the confines of the factory. This had the benefit of
enabling the development of very specific and detailed expertise about the production of physical
goods. In particular, it enabled very many mathematically based tools and techniques to be
developed that could help in vitally important factory tasks such as production planning and
scheduling (see Chapter 8), inventory control (see Chapter 9) and quality control (see Chapter 11).
However, restricting operations management to the consideration of factory-based activities alone is
limiting because the performance of operations is affected by what goes on outside of the factory as
much as by what goes on within it. Most operations take place within a supply network, which
comprises all the suppliers to the operation (and all their suppliers and their suppliers) and the
customers of the operation (and all their customers and their customers). The performance of an
organization’s operations and the extent to which it can satisfy customers depends significantly on
the performance of suppliers and others in its supply network (see Chapter 7). Thus, supply network
relations are increasingly recognized as being vitally important in operations management.
Within the organization, interactions with the other functional areas of business also have a
significant impact on the performance of operations. For example, if the marketing department’s
advertising campaign raises customer expectations in ways that make it difficult for the operations
department to meet, there will be an increased likelihood of customer dissatisfaction. Similarly, the
operations function cannot operate effectively unless the finance department is able to arrange
adequate funding and the human resource management department is able to attract and retain
workers with the right skills and attitude (see Chapter 12). As will be discussed in Chapter 3,
functional-level strategies (for operations, marketing, finance, human resource management, etc.)
need to be consistent with one another and with the organization’s business strategy if they are to
contribute to achieving a competitive advantage. In the past (and perhaps too often today), many
organizations considered the prime role of operations as being concerned with cost-cutting and
efficiency gains in order to achieve the lowest possible operating costs. Viewing operations in this
way severely constrains its strategic role. As not all organizations compete on the basis of price alone,
operations can only be used strategically as a competitive weapon if its performance objectives are
aligned with those of the organization’s business strategy. These may well require operations to meet
customer requirements in other aspects of performance (e.g. quality, flexibility, dependability and
speed), and not just cost alone (see Chapter 2).
The increased importance of the supply network
For many years, there has been a trend for organizations to obtain a greater proportion of their
inputs from external suppliers, buying them externally rather than producing them internally. In
particular, many organizations have been making greater use of suppliers based in other countries, as
they can often offer lower prices. Such international sourcing means that more organizations become
part of international supply networks. The greater use of offshoring in the sourcing of suppliers
typically causes the physical lengthening of the supply chain and increases its vulnerability to
disruption. The management of international supply is both more important and more complex than
when purchasing from local suppliers. It is difficult to envisage any reduction in the
internationalization of supply networks, so this aspect of operations management seems set to
remain important for some time to come.
The growing importance of services
It is invariably the case that as a country develops economically, the proportion of its national
economic output arising from services increases. Similarly, the proportion of its citizens in paid
employment in service industries also tends to increase. Thus, the service sectors of most national
economies have continued to grow in importance. Even China, where GDP has rocketed in recent
years on the back of its hosting of offshored manufacturing operations from the West, has now
reached the point where the growth in its service industries is outstripping that of its manufacturing
industries. In most countries today, services normally account for the majority of the value of a
country’s output, its gross domestic product (GDP), as illustrated in Table 1.1.
Offshoring involves moving certain operations to another country. This could be done either by
relocating the affected operations to the organization’s own facilities in another country, or by
outsourcing the operations to a foreign supplier. The motivation for this is often, but not exclusively,
cost saving.
Gross domestic product (GDP) is a measure of the size of a country’s economy. It is defined as the
market value of all final goods and services produced within the country.
As services have grown in importance in most of the world’s major economies, service operations
management has emerged as an increasingly important field of study. It would be odd indeed if
operations management as a subject were to ignore this vitally important sector of most national
economies. It would do a grave disservice to those working in the service economy and sideline the
subject of operations management (and those who teach it) within the business school curriculum.
Operations management academics have therefore been giving service operations much more
attention in recent years. They have done this in two ways. First, by seeking to apply concepts and
techniques developed in manufacturing contexts to service environments. Examples of this include
the application of lean thinking (see Chapter 10) to services such as hospitals and statistical quality
control techniques (see Chapter 11) to monitor performance in sectors such as hospitality and air
travel through the use of customer feedback questionnaires. Second, by developing new concepts
and techniques that take account of the specific characteristics of service operations. Examples of
this include the quality gaps model, described in Chapter 11, and queue management techniques,
discussed in Chapter 8. Both of these trends seem set to continue as services grow in economic
importance. Therefore, it is likely that greater consideration will continue to be given to service
issues within the operations management discipline for some time to come. Some important
associated developments in service operations management include: Table 1.1 Percentage GDP
(2012) by sector for selected countries
Source: The World Bank: World Development Indicators: Table 4.2 Structure of output, available at:
http://wdi.worldbank.org/table/4.2(accessed 26 February 2015). To view the terms of use, please
visit www.worldbank.org/terms-of-use-datasets
Mass customization is the use of a single process to produce a wide variety of products (or services).
It aims to realize unit cost reductions through economies of scope in the same way that mass
manufacturing aims to achieve economies of scale.
Economies of scale are reductions in unit cost of output due to increasing production volumes. Unit
cost savings are achieved by spreading the fixed costs of production over an increased volume and
from the increased efficiency available from the division of labour and from using large-scale
machinery.
Servitization is the process through which manufacturers provide an accompanying service or
services for their traditional product offering in order to add additional value for their customers
when they are using that product.
The internationalization of service operations
In the past, most services had a high degree of simultaneity (i.e. their outputs were consumed at the
point of production). This made them difficult, if not impossible, to trade between countries, as
providers needed to be physically present at the point of consumption. However, Internet
technologies are now changing this, reducing or removing the need for service provider and
consumer to be in physical contact. For example, some medical diagnosis and even treatment can
now be conducted via telemedicine techniques. Similarly, many tangible aspects of services can be
digitized (e.g. the written word, music, moving images), making it possible to deliver them
electronically from a distance. This is prompting two trends. First, operations that were previously
thought of as front office, such as the provision of most aspects of personal financial banking
services, because of the requirement for both customer and service provider to be in the same
location at the same time, can now be transferred to the back office. It is the information that travels
rather than the people. Second, there is now a reduced need for front office and back office
operations to be co-located. This means that there are ongoing opportunities to locate back office
operations in other areas, often in offshore locations, where there is an abundance of either low-cost
or high-skilled workers.
Mass customization in services
The use of digital technologies has opened the way to mass customization in ways that were not
previously possible, making it possible to tailor products and services to individual customer
requirements, while at the same time lowering costs due to economies of scale in production. A
good example of this is recorded music. When this had to be transmitted via a physical device such as
a CD, then the list of tracks included was predetermined by the supplier. Only the mass production of
identical products could enable each CD to be produced at a low enough cost for it to be offered at
an affordable price to customers. Now that music can be digitally downloaded from Internet sites or
heard via online streaming services, customers can select whatever pieces of music they want, in
effect creating their own customized CDs. Furthermore, they can do so at as low or perhaps a lower
price per track than would have been on the CD.
Servitization to differentiate products
Despite moving their manufacturing operations to lower labour cost offshore locations, many
suppliers of physical goods still find it difficult to achieve satisfactory levels of profits in highly
competitive markets. More and more are therefore looking to use the provision of accompanying
services as the means of differentiating their offerings from competitors and customizing their
offering to meet specific customer needs. An example of such servitization is provided by aero engine
maker Rolls-Royce. They offer customers a ‘power by the hour’ package of aero engine performance
for an aircraft that takes care of all of the necessary support, including maintenance, rather than
merely selling engines and providing a separate maintenance service. This means that their
customers, the airlines, in effect, only pay for their engines when they are working.
THE INTERNATIONAL CONTEXT FOR OPERATIONS MANAGEMENT
It is generally accepted that over the last 30 years or so, a number of powerful factors have
combined to produce the phenomenon that has become known as globalization. This has led to the
increasing integration of economic activity around the world, evidenced in the growth in
international trade and the increasing interdependence of national economies. Many commentators
also emphasize the increase in cross-border social, cultural and technological exchange as essential
concomitant elements of globalization. Globalization has proved to be a contentious issue. Its critics
point to the dominance of Westernized free-market economics, the growing power and influence of
multinational enterprises (MNEs), and the detrimental impact on less developed countries (LDCs)
and the natural environment. This book will studiously avoid considering the rights and wrongs of
globalization. There are many other forums in which to do so. Our concern is rather to understand
the phenomenon and its resultant impact on the internationalization of operations management.
The factors driving globalization can be classified under four broad headings: technological, political,
sociocultural and economic. These are now discussed in turn below.
Technological
The digital technology revolution, driven by ever-increasing processing power of computers and the
near ubiquitous presence of the Internet, continues apparently unabated. Many analysts argue that
these information and communication technologies (ICTs) and their supporting infrastructure of
cables and satellites have created a new techno-economic paradigm that is underpinning a fifth
Kondratiev long wave1 of economic growth (Dicken, 2015). There can be no doubting the growing
importance of the Internet for businesses and individuals. In advanced economies, all but the
smallest firms make at least some use of the Internet in their businesses. In the retail sector, use of
the Internet is now mature, with, for example, nearly 70 per cent of Swedes, 65 per cent of British
and 57 per cent of Americans undertaking some of their shopping online in 2015, according to Digital
Strategy Consulting (2015). The Internet now has over 3 billion users, and 40 per cent of the world’s
population have an Internet connection (Internet Live Stats, 2015). However, Internet penetration
rates vary widely. Extreme examples are the case of Eritrea, where less than 1 per cent of the
population have Internet access, and Qatar, where 97 per cent have Internet access.
Globalization refers to the increasing integration of economic activity around the world, evidenced in
the growth in international trade and the increasing interdependence of national economies. An
increase in cross-border social, cultural and technological exchange is also a feature of globalization.
A multinational enterprise (MNE), or sometimes also termed a multinational company (MNC), is a
business organisation that has operations in a number of different countries.
A less developed country (LDC) is one whose economy is underdeveloped, relying mostly on
agriculture (and possibly extractive industries), and whose population has a low standard of living.
One of the main benefits of the Internet is that it facilitates cheap and easy direct personal contact,
irrespective of distance. Whether we have yet come to a point where the Internet has led to the
death of distance (as predicted by Cairncross, 1997) is probably questionable. But the Internet’s
ability to reduce the effects of distance can be significant. The use of email, instant messaging
(Facebook, Twitter, WhatsApp, etc.) and other forms of digital communications enables individuals
and organizations to communicate with one another almost anywhere on the planet. Almost
limitless quantities of data can be transferred within seconds. Low-cost video conferencing services
such as Skype and FaceTime can enhance, if not completely replace, the more impersonal aspects of
communicating via the written word on a computer, tablet or smartphone screen.
Within a few short years, online trading between businesses (B2B) and between businesses and
consumers (B2C) has become commonplace. Traditional business supply chains have been disrupted,
with both disintermediation and re-intermediation in evidence. In some cases, suppliers have chosen
to bypass the traditional distributors of their industry and trade directly with customers (e.g.
Amazon, Dell). In other cases, new intermediaries have emerged and reconfigured supply (e.g.
Travelocity for travel and Amazon for shopping). If products can be digitized (e.g. music, movies, the
written word), they can be delivered directly to consumers via the Internet, thereby removing the
need for the traditional distribution channels. The Internet can facilitate access to new customers at
a fraction of the cost of more traditional means. For example, online banking makes it possible to
offer customers the ability to undertake almost all traditional transactions without the need for
traditional banking halls.
B2B (i.e. business to business) refers to a transaction that takes place between one business
organization and another.
B2C (i.e. business to consumer) refers to a transaction that takes place between a business
organization and an individual consumer (i.e. individual citizens).
Disintermediation is the removal of one or more intermediaries (such as a distributor, wholesaler,
broker or agent) in a supply chain (known colloquially as ‘cutting out the middleman’). This is a
common feature of e-commerce, especially B2C e-commerce.
The Internet is also being used by organizations in their dealings with suppliers. For example, the use
of online auctions can enable companies to attract bids from many more potential suppliers than
would be economically viable using more traditional means. For many years, large organizations have
usually conducted much of their business with their suppliers through electronic data interchange
(EDI) systems, improving information flows between the companies, allowing them, for example, to
enable exact order requirements and for stock positions to be updated instantaneously. Now the
Internet has dramatically reduced the cost involved in operating EDI, enabling companies of any size
to make use of its benefits. Global positioning satellites have enabled the exact location of goods in
transit to be tracked. ICTs are also used by organizations to enable workers in different locations to
work together effectively. This has been particularly pronounced in the separation of front and back
office operations in some service organizations. In all cases, the impact of technology is to shrink
distance, reducing the importance of proximity between supplier and customer.
It is also worth noting the impact that improvements in technology in the latter half of the twentieth
century have had on the speed and cost of transportation of both goods and people. Advances in air
travel mean that virtually any part of the inhabited world can be reached from any other in less than
a day. Improvements in transport infrastructures on both land and sea, and in transportation systems
(particularly the near universal adoption of containers), have led to dramatic reductions in the total
time taken to transport goods. Taken together with the impact of Internet-based ICTs, the world can
truly be said to have shrunk.
Political
For almost half a century after the Second World War, the world was essentially divided into three
groupings. The industrialized countries of the ‘West’ (North America, Western Europe and Japan)
manufactured most of the world’s goods and accounted for most international trade. The USA was
the most dominant political and economic force as the European powers and Japan recovered from
the devastation of war. Second, the ‘communist bloc’ of the Soviet Union and Eastern Europe sought
to create its own economic system quite separate from that of the capitalist West. The rest of the
world outside of these two groupings was the ‘Third World’. This comprised the mostly poor and
underdeveloped countries that were often the sources of the world’s raw materials and food. Many
countries were emerging from colonialism during this period and some became battlegrounds
(usually metaphorically, but sometimes literally) between the competing interest of the West and
communism.
Re-intermediation is the reintroduction of an intermediary in a supply chain. The growth of ecommerce has prompted the emergence of new kinds of intermediary in many industries.
Electronic data interchange (EDI) is the computer-to-computer exchange of structured information
via a telecommunication link. EDI has been used by business since the 1970s and there are agreed
international standards covering its use. It is still used by many MNEs to automate their purchase of
goods and services.
An increasingly important political development since the Second World War has been the
emergence of international agencies to promote international trade and development, such as the
WTO, the IMF, the AIIB and the World Bank. Most countries belong to such agencies. The World
Trade Organization (WTO) negotiates agreements between governments that govern the rules of
trade between nations. It has promoted trade liberalization by brokering deals that have
progressively lowered trade barriers and tariffs between countries. The International Monetary Fund
(IMF) promotes international monetary cooperation and provides temporary financial assistance to
countries in financial difficulty. The Asian Infrastructure Investment Bank (AIIB), initiated by China in
2009, supports the building of infrastructure in the Asia-Pacific region. The World Bank provides lowcost finance to developing countries for education, health and infrastructure projects. Although the
economic development of many Third World countries has been disappointing, some have advanced
significantly and are now considered as newly industrialized economies (NIEs). O’Neill (2001) coined
the acronym BRICs for what he saw as the strongest NIEs, namely Brazil, Russia, India and China. The
intervening years have seen somewhat mixed performances from the economies of these countries.
Most notably, China has become the world’s second largest economy (after the US). It is the world’s
largest manufacturing economy, and the largest trading nation, being the largest exporter and
second largest importer of goods (IMF, 2014). As such, it should perhaps not now be considered as
an emerging economy at all. As well as adding South Africa to the list of BRICs, O’Neill went on to
invent the further acronym MINT for the next group of countries, Mexico, Indonesia, Nigeria and
Turkey, assessed as significant NIEs (Magalhaes, 2013). The emergence of countries such as these is
characteristic of the changing economic order in the rapidly globalizing world.
As well as cooperating globally to promote increased international trade, countries have also done so
regionally to create formal trading groups. The first of these was the European Union (EU). Originally
formed by six countries in 1957 as the European Common Market, the EU now encompasses 28
countries. While there is the prospect of others joining in the future, the UK announced its intention
to quit the organization in 2016. Free trade is a central tenet of the EU. ASEAN (the Association of
Southeast Asian Nations) comprises 10 South East Asian countries who have pledged to create the
ASEAN Economic Community as a free trade zone. A similar free trade agreement, the North
American Free Trade Agreement (NAFTA) was set up between the US, Canada and Mexico in 1994.
Further moves to promote free (or at least freer) trade between groups of countries have been given
currency by the Trans-Pacific Partnership Agreement (TPPA), to which 12 Pacific countries are
signatories, and the Transatlantic Trade and Investment Partnership (TTIP) between the US and the
EU. The creation of free trade blocs such as these can particularly impact decisions about where
companies choose to locate their production and service delivery facilities. Locations within a
country that can offer tariff-free access to all of the countries within its trading block are usually seen
as highly attractive for firms seeking to access and penetrate those markets.
Sociocultural
The last two decades have seen an increase in the movement of people around the world. More
open borders and cheaper travel costs have contributed to the numbers migrating, both legally and
illegally, to seek work and improved economic circumstances, or to escape war and persecution.
More people travel greater distances to take holidays. Many young people now often undertake
extended periods of travel, sometimes including short periods of work, typically before going to
university or taking a permanent job. Many students now choose to study in universities outside of
their homelands. Satellite television and the Internet make it possible to learn about life in other
countries very quickly. People all over the world now aspire to access the same products and services
that might previously only have been available in the more advanced economies. This has fuelled the
trend for global products that have the same level of quality wherever in the world they are
produced and consumed. The world may not yet be a global village, but many people now feel
themselves to be citizens of the world as much as citizens of their country of origin or current
residence.
Economic
Until the financial crisis of 2008, the period since the end of the Second World War had seen the
most sustained period of economic growth in modern history. Despite the economic difficulties
suffered by many countries in the aftermath of 2008, in many ways it was the financial stability and
mostly continuous growth experienced in the preceding several decades that have underpinned the
forces of globalization. While the US and the countries of Western Europe were the driving
economies for much of that time, the emergence of new manufacturing centres in the NIEs of South
East Asia (e.g. South Korea, Taiwan, Singapore, Hong Kong, Malaysia, Thailand, the Philippines,
Indonesia), Latin America (e.g. Brazil, Mexico) and particularly China has provided a major stimulus
to the world economy. As previously discussed, the growth in the international trade in services has
become a notable feature of the world economy in recent years, far outstripping the growth in
manufactured goods (WTO, 2014). Advances in technology have enabled more services to be traded
internationally, especially in financial services and ICT. Of the developing countries, India has been
particularly successful in benefiting from this trend.
Finally, in discussing the economic drivers of globalization, the role of MNEs should be noted. These
are among the world’s largest businesses and they operate in countries outside of their homeland.
They include familiar names such as Exxon Mobil and Royal Dutch Shell (oil companies), General
Motors and Toyota (carmakers) and Apple and Samsung (electronics manufacturers). Indeed, their
activities often span the globe and their products can be found in virtually every country. The
financial value of the activities of such businesses can exceed that of many nation states. The
decisions taken by their executives can have a greater impact than that of many government
ministers. Unlike governments, their decisions are taken not in pursuit of national interest, but rather
in pursuit of growth and profits for their shareholders. Their decisions, about where to locate their
operations and where to source their suppliers, can have significant impacts on the economies of the
countries involved. In most countries, MNEs can take advantage of the freedoms afforded by banking
and financial systems that operate electronically on a 24-hour basis to transfer funds unhindered
from government restrictions. Thus, many MNEs are powerful economic forces in their own right
that often act independent of national governments.
Internationalization theories
In the face of the forces of globalization discussed above, more and more organizations have been
internationalizing their business operations. Although some businesses have always operated
internationally, these have generally been small in number but very large in size, as typified by large
multinational enterprises (MNEs).
A number of theories explaining this internationalization process have been promulgated, including:
Vernon’s product cycle theory
Vernon (1966) offered an analysis of the internationalization process. The essence of this theory is
that production increasingly moves away from the place of origin over time in a series of identifiable
phases. Vernon identified five such phases based on the product lifecycle model:
»Phase 1 – Introduction: All export markets are served from production in the home country.
»Phase 2 – Growth: Production facilities set up in high-income markets to serve local markets. Lowincome markets in less developed countries (LDCs) continue to be served from production in the
home country.
»Phase 3 – Maturity: The newer lower-cost facilities in the high-income markets export to LDCs,
displacing exports from the home country.
»Phase 4 – Saturation: The newer lower-cost facilities in the high-income markets export to the
home country.
»Phase 5 – Decline: Newer lower-cost production facilities set up in LDCs, which export back to the
home country.
Vernon’s theory was based on his analysis of the overseas investments of US corporations and his
prediction of likely future events. A frequently cited example of a product that followed the theories
of pattern of invention, growth and production is that of the personal computer and the US, where
the PC was invented and first manufactured. However, modern critics argue that his theory does not
explain more recent patterns of internationalization. They maintain that his model is too simplistic in
today’s much more complex world.
Dunning’s eclectic theory
Dunning (1976) argued that a firm will engage in international production at a particular location
when all of the following three conditions are present:
»Ownership-specific advantages: The firm must have access to assets not possessed by competing
firms. Such assets might be tangible (e.g. raw materials, plant and machinery, skilled labour) or
intangible (technological or marketing know-how, patents, brand names, management expertise).
Large firms tend to be better placed to internationalize as they usually have access to greater
amounts of finance at lower cost.
»Location-specific factors: There must be factors at the foreign location that make it more
advantageous for the firm to locate its operations there rather than at home. These factors might
include access to markets, the availability of resources, lower production costs, favourable political
conditions and cultural/linguistic affinities. The importance of each will vary depending on the type
of activity taking place.
»Internalization: The firm must internalize the use of its ownership-specific advantages at the
location, exploiting them itself, rather than selling them or leasing them to other firms.
Dunning’s theory is sometimes known as OLI, in reference to the three factors. Although some critics
argue that it is more a list of factors rather than a theory, it offers a useful framework to examine
specific cases of internationalization of operations.
Stage theories
Various authors have argued that firms internationalize in a series of incremental sequential stages. A
number of different models describe the various stages that have been put forward.
The best known of these is the Uppsala model (Johanson and Wiederscheim-Paul, 1975), which
identifies four stages:
»Stage 1: No regular export activity.
»Stage 2: Export to foreign countries via local sales agents.
»Stage 3: Establishment of a wholly or part-owned subsidiary company in order to sell directly to the
foreign country.
»Stage 4: Establishment of production facilities in the foreign country.
Ohmae (1994) adds two further stages beyond the Uppsala model. Ohmae’s stage 4 (his stage 1
equates to Uppsala’s stage 2, as he omits Uppsala’s stage 1) is complete insiderization. At this stage,
the firm becomes an ‘insider’ in the markets it services, with all the resources necessary for that,
including R&D, production and marketing. This requires the diffusion of organizational activities to
different locations around the world, to meet the needs of each of the different markets. The fact
that various functional activities have become replicated around the world is likely to lead to
tensions within the organization, with national managers attempting to meet the specific
requirements of local markets clashing with those at headquarters trying to coordinate and control
disparate efforts around the globe.
Ohmae’s stage 5 is true globalization. This requires all members of the organization to make a mental
adjustment and adopt a truly global mindset. This is one where the loyalty of each employee is to the
firm as a global entity, not to the headquarters or the country where they work, and the focus is on
meeting the needs of customers irrespective of where they are located in the world. Overcoming of
the problems caused by the dispersion of operations and functional activities around the world leads
to a new role for senior managers at corporate head office. Their role becomes one of guarding
corporate identity. As such, they will focus their efforts on controlling branding and ensuring that
corporate policies can meet the needs of all stakeholders across the globe. Thus, Ohmae’s stage
model has the following stages:
»Stage 1: Export via agents.
»Stage 2: Establishment of a sales subsidiary in the foreign country.
»Stage 3: Establishment of production in the foreign country.
»Stage 4: Complete insiderization.
»Stage 5: True globalization.
Stage model theories of internationalization have been criticized in a number of ways. First, they are
based on analyses of how a relatively small number of companies have behaved in the past. They do
not adequately describe how all companies have internationalized. Some empirical studies have
shown that some companies have followed a number of different paths to the establishment of
foreign production facilities, skipping one or more of the stages (e.g. Turnbull 1987; Clark et al.,
1997). Indeed, some companies can be ‘born global’ (Rennie, 1993), operating in international
markets on a substantial scale from their earliest days. Furthermore, some companies have behaved
differently when entering different overseas markets. Second, the models do not mean that all
companies must or will follow these stages in the future. The stage models do not necessarily
represent best practice, and organizational strategists may well be able to devise other ways to
internationalize. Finally, all stage model theories seem to assume that internationalization is marketled, with organizations entering particular countries to meet an identified market need in that
country. However, as will be discussed in Chapter 3, strategy can also be operations-led. Establishing
operations in one foreign market may be part of a process of building knowledge and expertise that
can subsequently be used, not only to expand further into that market, but also as a springboard for
entry into other markets. Lessons learnt from experiences in one market can be used to inform and
shape actions in others.
THE INTERNATIONALIZATION OF SERVICES
Most of the theories about internationalization discussed above are implicitly, if not explicitly, based
only on a consideration of manufacturing organizations. This may have been understandable up until
recently, as there have been few instances of service-based organizations operating internationally.
However, services have become increasingly important and now represent the overwhelming
majority of economic activity in industrialized countries. Also, it is fairly easy to think of examples of
service providers that do operate internationally (e.g. the banking and financial services, media,
telecommunications, business services industries). So, are we to simply assume that service
organizations internationalize in exactly the same way as manufacturers? Or, should services be
considered as a special case?
One of the most important distinctions made between services and manufacturing is that of
customer contact. Manufacturing does not usually require any direct customer contact. However,
back office services do not require direct customer contact either. A great deal of the
internationalization of services in recent years has taken place in back office services. The offshoring
of back office service operations has often been driven by a desire to move labour-intensive support
services to low labour cost locations. India has especially become a favoured destination for the
offshoring of back office services. Some companies have chosen to set up their own back office
operations in foreign countries. Others have outsourced these operations to locally owned external
providers. Back office operations can be viewed as another form of manufacturing, and so in many
respects it seems quite legitimate to consider their internationalization as being akin to that of
manufacturing operations.
Outsourcing is one of the terms used to describe the process of obtaining inputs of goods or services
from sources outside of the organization.
Front office operations, however, appear to be different, as these require some degree of customer
contact. So where and how that contact takes place is a key element in these operations. The
facilitation of contact between service provider and service user may necessitate one or other of
them to move. The service provider may need to move to meet the service user. The service user
may need to move to meet the service provider. Front office services can be categorized on the basis
of a 2x2 matrix formed by considering these movements (see Figure 1.4).
Separated services
These are services where there is no need for face-to-face physical contact between service provider
and user. Contact in these services is typically technology-mediated in some way, as is the case for
telephone and Internet services. Technological advances have seen an increase in cross-border
separated services. Telephone call centres are an obvious example. Reductions in the cost of
telecommunications have fuelled the vast increase in the offshoring of call centres, especially to India
and other low labour cost countries with an abundance of well-educated English speakers. The
widespread availability of the Internet has made it possible for businesses and consumers alike to
conduct most commercial transactions online. Increasing bandwidth is making Figure 1.4 Customer
contact service location matrix
Source: inspired by ideas in B890 International enterprise (1995-2002) The Open University.
it possible to deliver many services online via the Internet for the first time. This is especially so for
entertainment. It is now possible to download music, videos and movies from the Internet. Internet
technology is advancing rapidly and the possibilities seem unlimited. Technologically speaking, the
location of an online service provider has become irrelevant. This is opening up new approaches to
the internationalization of any service that can be digitized, and our understanding of the
internationalization process seems certain to be challenged.
Demander-located services
Some face-to-face services need to be provided at the user’s location, with the provider needing to
move to deliver the service. Management consultancy is one example of such a demander-located
service. Some industrial services such as the repair and commissioning of equipment also fall into
this category. The internationalization of this type of service requires the provider to have the
capability of delivering the service in the user’s country. This clearly has implications for the skills
required by the service delivery personnel, the provision of any necessary equipment they require,
the cost of delivery, and so on.
Provider-located services
The provision of some face-to-face services requires the user to move to the provider’s location. This
is often the case where the service needs specialist equipment or staff, as is often the case for
medical services. Some services are provided specifically for users who are themselves travelling,
whether for business or pleasure (e.g. in the hotel and hospitality industries). Sometimes the user
travels to the provider’s home country to receive the service, as is the case for some specialist
medical treatments. However, more normally, this category of service requires the provider to
establish service provision locations to suit the user. This clearly has implications for
internationalization.
Peripatetic services
Although they are more unusual, there are services where the provider and the user both move in
order to facilitate the service encounter. Trade shows, conferences and some live entertainments fall
into this category. The encounter needs to take place at a location suitable for the event, so both
service providers and users need to have the ability to access such venues.
Internationalization normally creates a conflict between the pressure to standardize provision
globally in order to maximize economies of scale and scope, and the pressure to customize in order
to meet the different requirement of customers in each locality. Services have traditionally been seen
as being more difficult to globalize because of the imperative to tailor the service offering to meet
different local needs. This is particularly true for front office services where the requirement of
customer contact makes them fundamentally different to manufacturing. This ought to prompt a
somewhat different consideration of the internationalization process for at least some types of
services. However, with some exceptions (e.g. Segal-Horn, 2005), the development of theory of the
internationalization of services has lagged that for manufacturing.
IFFERENT TYPES OF OPERATIONSOperations can be classified into three different types depending
upon which type of primary input is principally being transformed in the operation:
»Material-processing operations are those in which materials are transformed either from one form
to another, and/or from one place to another. Manufacturing operations in which raw materials and
components are transformed into finished products fall into this category (e.g. manufacturing a car
or producing a garment). Other material-processing operations include mining, and the transport,
storage and distribution of goods in warehousing and retailing operations.
»Information-processing operations are those in which information is transformed from one form to
another and/or from one place to another. There are many examples of information processing,
including accountancy, banking, financial services, telecommunications and research of all kinds.
Nowadays, it is difficult to think of information-processing operations that do not involve the use of
computers.
»Customer-processing operations, in which the customer is transformed by the operation. There are
many examples of this type of operation, including medical services (e.g. hospitals) in which sick
people are, hopefully, made well, education, where people are transformed by gaining additional
knowledge or skills, and entertainment, where people are transformed by the emotional benefit
gained from the event.
While one of these types of processing often predominates in any particular operation, many
operations also typically involve two or even all three types. For example, a restaurant processes
both materials (food) and customers; a book publisher processes both information (the text for the
book) and materials (the paper, ink, etc.); and an airline processes customers (passengers) and
materials (their baggage). TOYOTA: THE WORLD’S NUMBER ONE
With global sales now at 10 million vehicles per annum and climbing, Toyota finds itself as the
world’s leading auto manufacturer. US giant General Motors, which had previously held this title for
74 years, was dethroned in 2006, and the Japanese automaker has not looked back since. In a
financial climate in which most of the top automakers have experienced declines both in sales and
profits, Toyota stands out for its burgeoning financial returns, which are not restricted to the
established US market, following investment in China’s developing market. Environmental and
technological advancement, in the form of its part-electric, part-petrol hybrid models, also creates
healthy demand. Toyota’s Lexus subsidiary also taps into the US luxury market, propelled in 2016
through its RX crossover model, which exceeded sales forecasts.
Despite the fact that it dates back to 1937, Toyota rose from relative obscurity in the 1950s through
Taiichi Ohno’s development of the Toyota Production System (TPS). Based on Japanese principles
such as jidoka (referring to human automation), muda (elimination of waste) and kaizen (continuous
improvement), TPS enables greater cohesion within the manufacturing process, particularly with
regard to team- and management-based tasks. In an industry that is so dependent on intricate
supplier collaboration, it has been claimed that TPS helps to achieve this end, insofar as it minimizes
defects. The eradication of such design flaws also allows newly created products to reach the
customer in a shorter time than can be achieved by other companies, and with a greater level of
quality control. Getty Images/Hero Images
This approach to production has been researched and emulated by a number of international
carmakers and is now considered the industry gold standard, while also finding traction within other
sectors. Now articulated as ‘lean’ production, numerous service environments have also
incorporated this approach. One such surprising application of TPS methodology can be found within
the field of healthcare, in which the traditional focus upon meeting objectives is replaced with the
prioritization of processes. Each role within the organization is defined in terms of key competencies,
and, as these are met, patient needs are satisfied with greater consistency.
TPS has been regarded as the secret to Toyota’s success, implementing increased flexibility and
productivity while eradicating many of the production errors that plague other car manufacturers. As
a result, the company does not need to resort to competitor-minded discounts in order to satisfy a
customer base that is happy to pay for quality. As Toyota continues to outperform its rivals for a
fourth consecutive year, it now contemplates consolidating its position through business
partnerships with manufacturers such as Daihatsu and Suzuki. And yet, at the heart of this
increasingly outward-looking company remain the streamlining qualities facilitated through the TPS,
which acts as an integral foundation for such growth.
ERVICE OPERATIONSOperations can be classified more simply in terms of their outputs, as either
goods or services. The factors that distinguish them are:
»Tangibility: Goods are physical products that can be touched, seen, tasted or smelled. As physical
entities, goods can be stored and transported. The ownership of goods can be transferred from the
supplier to the customer. Services, on the other hand, are intangible, and therefore unlikely to
possess any of these properties.
»Simultaneity: Services are distinguishable from goods in that their production and consumption
usually takes place simultaneously. As such, it is usually not possible to store a service that has just
been produced for consumption at some time in the future. Normally, customers have to be present
to receive the service when it is produced. On the other hand, goods can usually be stored ready for
future consumption by a customer.
»Customer contact: Because of their intangibility and simultaneity, services normally require some
degree of contact with the customer, although the degree of that contact can vary. Similarly, some
services are much more labour-intensive than others, and might involve the customer coming into
contact with large numbers of employees of the service delivery organization, such as in a visit to a
hospital or staying in a hotel.
»Quality: Because of the nature of the output of a service operation, it is much more difficult to
define and measure the quality of a service. The quality of a product can be defined and measured in
terms of its functionality (i.e. its fitness for the purpose for which it is intended). The quality of a
service, on the other hand, can often only be judged by its recipient. Service quality is dependent on
the perception of a customer. Such perceptions may vary between one customer and another, and
between the customer and the service deliverer. As such, service quality often depends upon the
psychological state of a customer at the time of consumption. Indeed, some services are intended to
change a customer’s psychological state.
Services are the intangible outputs from an operation.
It is possible to think of examples that equate to the extremes of pure goods (coal mining) and pure
services (psychotherapy). However, a closer consideration of the outputs of most operations reveals
that it is rare to find such extremes. Usually, there are elements of service in most goods-producing
operations. For example, even extractors of commodity goods such as coal or oil typically provide
their customers with information about their chemical composition or offer technical advice on their
use. Similarly, even producers of a highly customized service such as management consultancy will
usually produce some tangible output, such as a written report of some kind. It is usually more
helpful to think of the outputs of operations as being located somewhere on a continuum between
pure services and pure goods (see Figure 1.2).
Many service operations are different from those in manufacturing, in that they usually require the
operation to have some degree of contact with the customer. Organizations that treat their
customers in the same way that they treat the inanimate objects that are materials are neither likely
to retain existing customers nor attract new ones.
The study of service operations has led to the development of some useful concepts in addition to
those that have emerged from the study of manufacturing. One such concept is that of the
difference between the front office and the back office. The area in which contact with customers
occurs is termed the front office. This primarily involves customer-processing operations. The area
where there is normally no contact with customers is termed the back office. This may involve
information- and/or material-processing operations (see Figure 1.3).
The transforming resources required in the front office are likely to be significantly different than
those needed in the back office. In particular, operations in the front office need to revolve around
the customer. The people that work in the front office are likely to require quite different skills than
those in the back office. Front office staff need high levels of interpersonal skills if they are to interact
successfully with customers. The physical resources used in the front office, buildings, machinery and
equipment may also need to be quite different from those in the back office. Indeed, the front and
back offices may well be physically located in quite different places. However, the relationship and
interaction between front and back office operations is often a key part of the management of
operations.
The front office is the area of an operation in which contact with customers normally takes place.
The back office is the area of an operation in which there is normally no contact with customers.
HE TRANSFORMATION MODELAny operation can be depicted as a transformation process that
converts inputs into outputs of goods and services (see Figure 1.1).
For the inputs, it is useful to distinguish between:
»The primary inputs that are themselves transformed to become part of the output of the operation.
These are sometimes referred to as ‘transformed resources’ (Slack et al., 2013). Primary inputs can
be materials and/or information and/or customers.
»The resources necessary to carry out the transformation, but which do not themselves form part of
the output. These are sometimes referred to as ‘transforming resources’ (Slack et al., 2013). Figure
1.1 The input-output transformation model for operations
Source: adapted from Operations Management, 7th edition, by Nigel Slack, Alistair Brandon-Jones
and Robert Johnston, Pearson Education Limited. © Nigel Slack, Stuart Chambers, Christine Harland,
Alan Harrison, Robert Johnston 1995, 1998. © Nigel Slack, Stuart Chambers, Robert Johnston 2001,
2004, 2007, 2010. © Nigel Slack, Alistair Brandon-Jones, Robert Johnston 2013.
These can typically be classified as:
»Facilities: These are the resources that are necessary to undertake the operation, but which are not
used up in the operation. Typically, these include the land, buildings, equipment and vehicles used by
the organization to perform the operation. These resources are usually intended to be used over
several years. Consequently, they are normally designated as fixed assets by accountants, and their
value appears in the fixed assets column of the balance sheet.
»Consumables: These are the resources that are used up as part of the operation. Examples include
the energy necessary to power buildings, plant and machinery, and the materials necessary to
maintain, repair and operate them (often referred to as MRO supplies).
»People: The human resources necessary to undertake the operation. These will usually include the
staff of the organization. However, employees of other organizations might also be involved in the
transformation process, for example those belonging to the suppliers or subcontractors of the
organization undertaking the operation.
The transformation model sees operations management as those activities that are concerned with
how these resources are managed in order to produce the required outputs of goods and services.
DIFFERENT TYPES OF OPERATIONS
Operations can be classified into three different types depending upon which type of primary input is
principally being transformed in the operation:
»Material-processing operations are those in which materials are transformed either from one form
to another, and/or from one place to another. Manufacturing operations in which raw materials and
components are transformed into finished products fall into this category (e.g. manufacturing a car
or producing a garment). Other material-processing operations include mining, and the transport,
storage and distribution of goods in warehousing and retailing operations.
»Information-processing operations are those in which information is transformed from one form to
another and/or from one place to another. There are many examples of information processing,
including accountancy, banking, financial services, telecommunications and research of all kinds.
Nowadays, it is difficult to think of information-processing operations that do not involve the use of
computers.
»Customer-processing operations, in which the customer is transformed by the operation. There are
many examples of this type of operation, including medical services (e.g. hospitals) in which sick
people are, hopefully, made well, education, where people are transformed by gaining additional
knowledge or skills, and entertainment, where people are transformed by the emotional benefit
gained from the event.
While one of these types of processing often predominates in any particular operation, many
operations also typically involve two or even all three types. For example, a restaurant processes
both materials (food) and customers; a book publisher processes both information (the text for the
book) and materials (the paper, ink, etc.); and an airline processes customers (passengers) and
materials (their baggage).
ERFORMANCE MEASUREMENTPerformance measurement is the process of quantifying actions taken
to improve performance.
‘If you can’t measure it, you can’t manage it’ is a phrase that encapsulates the role and importance of
performance measurement in operations management. At its most basic, the purpose of
performance measurement is to keep score. On first examination, performance measurement might
seem a fairly straightforward matter. Just decide what aspects of performance are important and
measure them. However, a deeper consideration raises a number of questions and issues.
First, performance objectives are usually expressed in numerical form. For example, cost objectives
need financial measures, while speed and dependability objectives need measures of time. This, of
course, assumes that the aspects of performance that managers are interested in can be quantified.
Sometimes this is not easy. For example, many aspects of quality are notoriously difficult to measure
(this is discussed in more detail in Chapter 11). Even if quantification is possible, the act of
measurement itself has costs associated with it. The more aspects of performance that are
measured, the higher the costs are likely to be. So an associated question is, given the costs, how
many measures should be used?
Second, how do you determine what aspects of performance should be measured? Another
important maxim in performance measurement is ‘what gets measured gets done’. This is because
the act of choosing a particular measure focuses attention on that aspect of performance, usually
with the specific intention of achieving a desired outcome. Indeed, performance measures are
usually chosen to measure progress towards achieving one or more specific performance objectives.
Thus, the choice of what to measure becomes a key decision. It immediately signals what is seen to
be most important to the organization’s operations, and hence what will become the focus for
management attention. The measures seen to be of most concern to managers will be the measures
people inevitably focus on.
Of course, for most organizations, ‘keeping score’ is only the starting point for performance
management. They will usually want to take actions that will improve performance in the light of the
measurements being taken. What is measured is vitally important because it will influence people’s
behaviour in one way or another. Indeed, much of the purpose of performance measurement is to
have a behavioural impact, to focus people’s attention on actions that will improve the chosen
measures. In some organizations, this intention is emphasized and reinforced by offering rewards,
often monetary, that are based on the achievement of specified performance measurement targets.
Performance-related pay, whether for shop floor workers or for senior executives, remains popular.
The whole point of such schemes is to provide direct financial incentives to people to improve
whatever performance measures are used as the basis for the scheme. It is important that such
measures do promote the kind of behaviour desired by the organization. There is a very real danger
that placing too much of an emphasis on certain performance measures can promote the kind of
behaviour that is not considered desirable and lead to unintended consequences. It may be that the
pursuit of a single performance target leads to other facets of performance being downplayed or
neglected. For example, many call centres have minimized the time it takes to answer the phone as
their prime performance objective. However, at periods of peak demand, that risks operators rushing
their responses to enquirers in order to move quickly on to the next caller. Callers may then feel that
the quality of service given to them has been poor because their enquiries have not been fully
answered and that the operator has been abrupt or even rude to them. An overzealous pursuit of
performance targets can also risk unscrupulous actions by some employees. In extreme cases, it may
even be that employees simply falsify records.
PERFORMANCE MEASURES
As discussed, determining what to measure is a key issue for performance measurement in
operations. The transformation model of operations (see Chapter 1) can be used as one basis for
classifying performance measures. Three types of measure can be identified dependent upon the
point in the process that they provide information about. These are measures of economy, efficiency
and effectiveness (see Figure 2.1.).
This classification is often referred to as the three Es of performance measurement, as it comprises
measures of:
The three Es of performance measurement are economy, efficiency and effectiveness.
Measures of economy are concerned with the cost of the goods and services required as inputs for
the operations process.
Economy
All organizations wish to acquire the inputs they need for their operations at the lowest possible cost.
Measures of economy are concerned with the cost of the goods and services required as inputs for
the operations process. While it is clearly important for those responsible for acquiring inputs to
achieve the lowest possible purchase price, buying on the basis of price alone is fraught with
difficulties. In organizations, it is usually better to consider purchasing decisions on the basis of the
so-called five ‘rights’ of purchasing: right quality, in the right quantity, at the right time, from the
right supplier, at the right price. Buying goods and services on the basis of price alone risks problems
in each of these categories:
»Quality: Focusing on price alone risks purchasing goods and services that do not have an adequate
specification for their purpose. If suppliers have had to quote very low prices to secure the business,
they may be tempted to cut corners to reduce their costs (and thus improve their profit margin), and
so endanger quality.
»Quantity: It is quite common to be able to negotiate a lower price with suppliers by agreeing to
purchase larger quantities. However, purchasing larger quantities than immediately required is likely
to involve increased stockholding costs.
»Timing: The timing of purchases is vital; too early and stockholding costs will increase, too late and
costly delays or disruption may occur in the operations process. Failure to consider this aspect of
purchasing risks higher costs.
»Supplier: In many respects, choosing the right supplier is the most important aspect of purchasing.
Failure to consider the reliability, capability and attitude of any supplier risks problems that are likely
to increase costs.
In short, a measure that accounts for the total cost of acquisition of goods and services, rather than
the purchase price alone, is likely to provide a much more meaningful measure of economy.
However, this is often difficult to establish in practice. Figure 2.1 The three Es of performance
measurement
Measures of efficiency are concerned with the performance of the transformation process itself, in
terms of its ability to make optimum use of resource inputs in the creation of outputs.
Efficiency
All organizations wish to make best use of the resources at their disposal by managing their
operations efficiently. A high level of efficiency helps ensure that the organization can achieve low
operating costs. Measures of efficiency are concerned with the performance of the transformation
process itself, in terms of its ability to make optimum use of resource inputs in the creation of
outputs. As such, measures of efficiency within the three Es framework are expressed in terms of a
ratio of outputs to inputs. These are often referred to as measures of productivity and derived from
the ratio: It is possible to construct a large number of productivity measures for any given operation.
Measures might be based on all the outputs from the operation. In the case of a manufacturing
operation, this would be the total quantity of products made; for a service operation, this would be
the total number of customers served. Alternatively, where an operation produces more than one
product type, different measures could be calculated for each different product or service type. For
manufacturing, these could be the total quantity of product A, the total quantity of product B, the
total quantity of product C, etc. For services, different measures could be produced for different
customer types (e.g. for a passenger airline, the numbers travelling in economy, business and first
class could be used).
Similarly, it is possible to calculate various productivity ratios based on different input factors (such as
the quantity of materials used to make a manufactured item or the number of labour hours needed
to serve a customer in a service operation).
Measures of productivity can either be:
Single factor productivity, based on a single input factor (e.g. labour and material costs). For
example: or:
Multi-factor, combining more than one input factor
or:
Total factor productivity, which seeks to account for all types of inputs. For example: Each of these
measures might be based on input volumes (or quantities) or values. Each will be more or less
difficult to calculate depending on the unique circumstances of the particular operation and its
organizational and industry context. Each will have its own particular advantages and disadvantages.
What is important is to be clear about the use to which any particular measure will be put.
Organizations usually focus most on those factors of productivity that they consider to be most
important. This is typically dependent on which aspects of their operations are most influential in
their sector (e.g. labour, materials, energy, land). Examples of productivity measures typically used in
particular types of organization are listed in Table 2.1 below. It is worth noting that these all use
single-factor productivity, rather than multi- or total-factor productivity ratios, and so are only partial
measures of productivity. Organization
Productivity measure Hairdressers
Chicken farm
Retail shop
Power generation plant
Paper mill Customers per labour hour
Kg of meat per kg of feed
Sales per square metre
Kilowatts of electricity per ton of fuel consumed
Tons of paper per cubic metre of wood Table 2.1 Examples of productivity measures in different
industries An electronic component manufacturer has supplied the following financial data (all in
US$): 2015
2014 Sales value
70,000,000
44,000,000 Labour costs
30,000,000
20,000,000 Raw material costs
25,000,000
16,000,000 Capital equipment depreciation
2,400,000
1,400,000 Other costs
9,600,000
4,400,000 Compare the labour, material and total productivity for 2015 and 2014.
Solution: Labour productivity
2.33
2.20 Material productivity
2.80
2.75 Total productivity
1.04
1.05 While productivity measures are often used as a surrogate for efficiency, another approach to
measuring efficiency is to calculate as the ratio of actual output to the expected output. Expected
output is calculated in terms of some standard production rate, which is the output that should be
achieved by a fully qualified and experienced worker operating under normal conditions. So: or:
Standard production rates and times can be calculated using work study techniques. Take the
example of a garment factory producing shirts. Work study analysts have calculated that each worker
should take one hour to produce a shirt. That is the standard time. So, if the factory employs 100
workers each working 35 hours a week, the standard output from the factory in each week should be
3,500 shirts. If the factory produces 3,000 shirts a week, the efficiency would be 85.7 per cent.
Whereas, if the output was 4,000 a week, the efficiency would be 114.3 per cent.
Effectiveness
All organizations wish to manage their operations effectively by ensuring that their customers believe
that they are receiving a high level of value. Measures of effectiveness are concerned with the extent
to which the outputs of a process meet the requirements of its customers; as such, they are often
much more difficult to determine. One approach is to measure levels of customer satisfaction
directly, for example through customer satisfaction surveys. It might also be possible to use indirect
measures of customer satisfaction, perhaps based on sales or market share. However, these can be
affected by external factors such as actions of competitors and the general economic conditions.
Some organizations prefer to use internally derived measures that relate more closely to actions
being taken within its operations, such as the numbers of repeat sales or returning customers. Being
effective means providing what customers want. Thus, it is important to base measures of
effectiveness on an understanding of what customers require from the operation. For example, a
restaurant might decide to use the number of people served per hour as a measure of its
effectiveness. This might be appropriate for a fast-food outlet, where customers want to be served as
quickly as possible. However, such a measure would be entirely inappropriate in an upmarket fine
dining restaurant where customers go to savour both the good food and the atmosphere.
Measures of effectiveness are concerned with the extent to which the outputs of a process meet the
requirements of its customers.
To be successful, an organization must manage its operations to achieve high levels of economy,
efficiency and effectiveness. The operations function is central to achieving these aims. Achieving low
costs by focusing entirely on economy and efficiency is rarely enough to ensure success.
Organizations must also ensure that their customers are satisfied with the goods and services they
provide for them. Operations management is important because of its impact on the quality,
availability, timeliness and reliability of the goods and services produced, as well as its impact on
costs. Customers judge the value of what they receive by some combination of these factors.
ERFORMANCE STANDARDSThe next question to consider is what the chosen measures used to
monitor the performance of an operation can actually tell managers and other interested parties
about the success of that operation. A performance measure can only be useful as a means of
determining whether an operation is performing successfully if there is some yardstick against which
to compare that performance. Answering this invariably requires that there is some comparator
against which to assess current performance. This principle is enshrined in the control loop model of
operations (see Figure 2.3).
A performance standard is the level of performance deemed suitable for use as the target level of
performance against which to compare a particular aspect of performance.
So the question is what should be used as a comparator? What is required is an agreed performance
standard that will serve as a comparator for actual performance.
There are a number of possible bases for such a standard:
»Internal standards:
(a)the organization’s past performance; and
(b)the organization’s own targets.
»External standards:
(a)competitors’ performance;
(b)best practice; and
(c)market requirements.
These are now each discussed in turn.
The organization’s past performance
The basis of this approach is the use of the organization’s own previous performance as a standard
against which to judge future performance. Improvement targets can then be set against those
standards. This might have the merit of being considered realistic by those involved, but it also runs
the risk of an inward focus, generating complacency. It tends to ignore both what the competition is
achieving and what the market may be demanding. If the organization carries out a particular
operation in more than one location, however, it could use performance measures that compare one
location against another to drive improvement up to the standard of the best-performing operation.
This approach can be particularly useful to organizations operating internationally as it enables them
to compare the performance of operations in different countries. In this category, the cost of
collection and presentation of information should be relatively small. Figure 2.3 The control loop
Source: inspired by information in Slack et al. (2013).
The organization’s own targets
Perhaps the most widely used internal performance standard is the annual budget or target. The
budget is normally of paramount importance in most organizations. Indeed, the achievement of
budget figures often forms the basis of reward (or punishment!) for many managers. The budget
specifies directly or indirectly the level of performance required by particular operations. The main
problem with budgets is twofold. First, they are self-determined, and therefore internally focused.
Like all internal standards, they can ignore the performance of competitors and the requirements of
customers. Second, most budgets are based primarily on financial information. This can make for a
very narrow information set on which to measure and assess performance. Internally derived
performance measures do, of course, have the benefit of being based on information that should be
readily available and accessible. The cost of collection and presentation of such information should
also be relatively small.
Competitors’ performance
In an increasingly competitive environment, it makes sense to adopt performance standards that
enable an organization to compare its performance with that of its direct competitors. While it might
be possible to do this at an organizational level on the basis of published information, it is usually
extremely difficult to access the necessary information to be able to make such a comparison at the
level of an individual operation. There are, however, many potential sources of information about
competitors at their operations. These include:
1.Published sources: Annual reports, press reports, company literature, analysts’ reports,
government reports, etc.
2.Secondary sources:
»Interviews with analysts, journalists, academics, etc.
»Direct contacts: plant visits, observations, etc.
»Indirect contacts: industry associations, technical seminars, trade associations, chambers of
commerce, etc.
3.Primary market research: Consumer surveys, trade surveys, industrial market research, etc.
4.Sales analysis: For example, by analysing competitive bids lost and won to identify strengths and
weaknesses in comparison to competitors.
5.Product comparison: Reverse engineering of products to assess the level of quality and technical
sophistication achieved by competitors.
6.Soft information: Informal information gathered by word of mouth from own and competitors’
employees.
While it can be difficult and time-consuming to gather and analyse, such information can provide
invaluable insights into the performance of competitors. It may be necessary to piece this together to
build up a less than complete picture, but it should be sufficient to draw up some standards based on
competitors’ performance. The mere act of putting together such information forces operations
managers to look outside their own organization, and can provide insights into how competitors
achieve their results.
Best practice
The intention here is to look beyond direct competitors and identify organizations whose practice in
a particular activity is recognized as being the best around. In this respect, at least in theory, an
organization could look anywhere in the world for examples of exemplary practices, wherever they
can be found. The idea is to use the level of performance achieved through the use of best practice
as the standard against which to compare current organizational performance in that particular
activity. So, for example, if a manufacturing company wanted to establish a standard for the
performance of its customer telephone helpline, it might look to an organization with a strong
reputation for answering calls quickly, such as the emergency services. The major advantage of
looking to organizations in different industries is that they are not direct competitors, and so are
more likely to be more willing to divulge information.
Market requirements
While looking to external organizations to set performance standards is likely to be more difficult
than generating ones internally, it is likely to provide more exacting and challenging targets. However,
this approach risks ignoring what must be the most important task of any business: namely, satisfying
customers. If organizations are not meeting customer requirements, then it is difficult to accept that
they are performing successfully. Arguably, the objective of any organization’s operations is to satisfy
customers. Therefore, performance standards should be based upon customer needs and
requirements. The task of identifying customer needs is usually considered to be a marketing activity.
Various market research techniques have been developed encompassing quantitative and qualitative
methods, using both primary and secondary data. However, leaving this task solely to marketers is
likely to prove less than satisfactory as the operations function can have much to contribute. People
working in operations, particularly service operations, have many contacts with customers and
potential customers. They are often well placed to gain an excellent understanding of how well (or
badly) the organization’s products and services are currently meeting customer needs. They can
provide valuable information that can help establish the level of performance required to meet
customer requirements. Also, as customer expectations change over time, usually becoming more
exacting, organizations need to continually monitor customer needs and requirements and adjust
their performance standards accordingly.
BENCHMARKING
The term ‘benchmarking’ is commonly used to refer to the application of the ideas of performance
standards as discussed above. It is usually used to refer to those practices aimed at comparing the
performance of an operation with that of similar operations in other locations. However, the term
can have a number of different meanings. At its most basic, it merely involves measuring various
aspects of performance in two or more different locations for comparison purposes, the idea being
to establish a performance standard that can be used as a target for performance improvement.
However, the main strength of benchmarking is when it is applied as a springboard to drive
performance improvements. As discussed earlier in the chapter, the act of measuring particular
aspects of performance signals its importance to the organization. When accompanied by
challenging performance standards, this should galvanize managers to achieve progress towards the
targeted level of performance. However, an even more potent aspect of benchmarking is when it
goes beyond measuring performance to encompass the study of the practices of the benchmarked
organizations. The idea is to compare the organization’s own practices and methods with those used
in similar operations by organizations that achieve much better levels of performance. Where
deficiencies are found, improvements can then be made based on what has been observed in those
better-performing organizations. When used in this way, benchmarking can offer a powerful
mechanism to drive organizational learning.
As with performance measurement benchmarking, practice benchmarking can be undertaken by
making comparisons in a number of different ways. There are three main approaches to practice
benchmarking:
1.Internal benchmarking: This is where practice in one of an organization’s locations is compared to
that in another. The advantage of this is that information about these operations should be readily
available and reliable. It should similarly be fairly easy to gain access to the organization’s other
facilities in order to study the practices. It may be that different practices have evolved in different
locations due to different contextual factors. Organizations that operate internationally can be
particularly well placed in this respect, and hence in a much better position to learn, than those that
only operate in one country. The main disadvantage of internal benchmarking is that even the best
level of performance within the organization may be much worse than that achieved elsewhere.
2.Competitive benchmarking: Here, organizational practices are compared to those of direct
competitors. This is often felt to be the most effective form of benchmarking as competitors are likely
to be operating similar processes. Competitors are easy to identify, but they may not be very
enthusiastic about allowing a direct competitor to learn from them, and thereby endanger their
competitive advantage. One way to overcome this in service businesses is to observe a competitor’s
front office operations from the perspective of a customer. It is more likely that an organization will
allow their operations to be studied by someone in the same industry who is not perceived to be a
direct competitor. Consequently, it might be possible to gain access to study an organization that
operates in a different country or one that serves a very different market segment.
3.Best practice benchmarking: Here, practice in a particular operation within an organization is
compared to practice in a similar operation in an organization thought to be exhibiting best practice,
preferably world-class performance. The idea is to learn from the best performers, wherever they are
found. It can be particularly instructive to study similar operations carried out in different industries
and in different countries, where different practices may have arisen. The advantage of looking to
organizations in different industries, and hence those that are not direct competitors, is twofold.
First, it can encourage innovative thinking through using different methods. Second, such
organizations are likely to be more willing to divulge information. The disadvantage is that it may be
difficult to know exactly where the best practice for a particular operation is to be found. Also, it may
prove difficult to apply their working methods in a very different industry. A well-known, if slightly
extreme, example of best practice benchmarking is provided by Southwest, the low-cost US airline.
They studied the practices of the pit crews at the Indy 500 motor racing circuit in order to help
reduce the turnaround time of aircraft between landing and take-off at airports.
The extent to which an organization can benefit from benchmarking will depend on the importance it
attaches to the exercise. Voss et al. (1998) claim that it is possible to identify four different
organizational attitudes towards benchmarking, which are revealed by their responses to the receipt
of performance data from a benchmarking exercise:
»Can do organizations are those that score badly on operational performance practice but use the
benchmarking exercise as an opportunity to take action to improve operational performance.
»Can’t do organizations are those that score badly on operational performance practice but fail to
use the benchmarking data to take any action. This can often be due to business pressures.
»Will do organizations are high-performing organizations that use the results of the benchmarking
exercise to take action to further improve operational performance. These are true learning
organizations.
»Won’t do organizations are high-performing organizations that fail to use the benchmarking
exercise to take any further action. These are typically complacent organizations who consider they
know all that is needed. The performance of these organizations is under threat in the longer term.
Organizations that operate internationally have greater opportunities to benchmark the performance
of their operations using comparators from different countries. This is likely to bring significantly
more benefits than benchmarking, using only domestic comparators. Organizations that operate
internationally not only have direct experience of operating in different national contexts, but are
also more likely to value the learning obtained from those experiences. As such, they are much more
likely to be open to ideas from outside of their own domestic environment.
A major problem with all forms of external benchmarking is finding organizations that are prepared
to grant access to outsiders. There is a natural reluctance to reveal organizational secrets that might
ultimately finish up in the hands of competitors and potential competitors, or others who might use
such information to the organization’s detriment, such as suppliers and customers. One solution to
this problem is based on the premise that any organization is likely to want to learn from another.
This has led to the setting up of benchmarking clubs. These are networks of organizations that, in
order to benchmark their operations against others, are prepared to grant access to others who want
to benchmark them. There are many such benchmarking clubs, organized by neutral bodies such as
management consultancies and trade associations. For example, the Chartered Institute of Public
Finance and Accountancy (CIPFA) runs a benchmarking club to enable local authorities in the UK to
compare their performance with peers, thereby identifying areas for improvement. Such bodies are
often able to collect a wide range of performance measures from their members, and get their
agreement to release them on the condition that they are never revealed on an individual basis, but
are instead published as part of industry-wide aggregate figures.
PERATIONS STRATEGY – PROCESSThe process of operations strategy concerns the way an
organization develops its operations strategy. Operations strategy might come about in a top-down
process, being cascaded down as a result of deliberate strategy at the corporate and business levels.
An operations strategy might also come about in a bottom-up process, in which a recognizable
strategy emerges as a pattern in a stream of actions. Similarly, an operations strategy might be
developed in response to market requirements (i.e. market-led) or be based on the capabilities of its
operations resources (i.e. operations-led). As illustrated in Figure 3.1, this gives rise to four
perspectives on operations strategy (Slack and Lewis, 2014). Each perspective places a different
emphasis on the nature of the operations strategy process.
Top-down The top-down perspective is one in which the operations strategy is derived from, and is
supportive of the organization’s business strategy; in other words, the organization bases its
operations strategy of identifying an operation’s ‘task’ to realize its business strategy. This concept is
in line with that of the Hayes and Wheelwright stage 3 organization. According to this perspective,
devising an operation strategy first requires the organization to identify an operations ‘task’ (Skinner,
1969). The task would be determined logically from the business strategy. Using Slack et al.’s (2013)
five operations performance objectives (see Chapter 2) is one way of articulating the operations task.
For example, if the organization’s business strategy is one of offering low prices, then the operation’s
task should be one of achieving low costs in operations. If the business strategy is based on offering
customers fast delivery, the operations task should be one of achieving speed in operations, and so
on. An example of this is fast-food restaurant company McDonald’s, whose main task for the
operations in its over 35,000 outlets across the world is to ensure consistency. Figure 3.1 The four
perspectives on operations strategy Source: adapted from Operations Strategy, 2nd edition, by Nigel
Slack and Michael Lewis, Pearson Education Limited. © Nigel Slack and Michael Lewis 2002, 2008.
In a multi-business organization, the top-down perspective envisages that operations strategy
supports the strategy of each business unit. In a diversified conglomerate, such as India’s Tata, such
business units can operate in very different industries (e.g. steel-making, motor car manufacturing,
tea production, consultancy, mobile phone operator), each of which may require very different
strategies. This then raises the question of whether it is possible to talk of a ‘corporate’ operations
strategy. If a corporate operations strategy means commonality in all aspects of operations, then this
would only be possible if each business unit had similar business strategies and similar operations
tasks. However, some authors (e.g. Hayes et al., 2005) argue that a corporate operations strategy
does not mean that every facet of operations must be the same in each business unit. Rather,
operations decisions are considered holistically at the corporate level with a view to meeting
corporate strategic objectives. A failure to do this means that operations decisions are taken only at
the level of the business unit, with a view to meeting the immediate needs of that business unit. The
dangers of doing this have been pointed out by Prahalad and Hamel (1990), who caution against
letting the needs of the business unit dominate strategic thinking. This can lead to operational
competencies being confined within individual business units, thereby restricting their future
development, preventing their spread to other business units and limiting opportunities for
synergistic developments across the corporation. This can be particularly important in multisite,
multinational enterprises.
Bottom-up The bottom-up perspective is one in which operations strategy emerges through a series
of actions and decisions taken over time within operations. Companies, such as Apple, that rely on
constant innovation for their success, provide examples of the bottom-up perspective. In these
organizations, actions and decisions might at first sight appear somewhat haphazard, as operations
managers respond to customer demands, seek to solve specific problems, copy good practices in
other organizations, etc. However, they can build over time to form a coherent pattern recognizable
as an operations strategy. The actions taken within this kind of strategy are likely to be characterized
by a continuous series of incremental improvements rather than the large one-off technologically led
changes that require large capital investments in new plant and machinery. The bottom-up
perspective is one in which the organization learns from its experiences, developing and enhancing
its operational capabilities as operations managers try out new things in an almost experimental
fashion using their workplaces as a kind of ‘learning laboratory’ (Leonard-Barton, 1992). Many of the
manufacturing practices that are now considered leading edge (such as just in time, total quality
management, statistical process control) were developed in just such a fashion by Japanese
manufacturers responding to the constraints placed upon them in the aftermath of the Second
World War. One of the problems associated with this perspective is that the organization may not
recognize what its operations strategy is. Mills et al. (1998) have developed a technique that aims to
overcome this by enabling managers to construct a visual representation of operations strategy as
realized. It does this by tapping into the organization’s collective memory (whether written or verbal)
to map all the most significant events in
operations over the previous number of years. This should enable managers to recognize the
patterns that now make up the existing operations strategy.
Market-led The market-led perspective is one in which the operations strategy is developed in
response to the market environment in which the organization operates. Many FMCG (fast-moving
consumer goods) companies, such as Unilever and Proctor & Gamble, offer examples of this
perspective.
There are a number of approaches in the operations strategy literature that suggest how this might
be done. The best known of these is that of Terry Hill (1985). He suggests that an organization’s
operations strategy should be linked to its marketing strategy by considering how its products and
services win orders in the marketplace. He believes it is possible to identify two types of competitive
criteria in any market: market qualifying and order winning. Market-qualifying criteria are those
factors that must be satisfied before customers will consider making a purchase in the first place.
Order-winning criteria, on the other hand, are the factors on which customers ultimately make their
purchasing decision. For example, for many airline passengers, the order-winning criteria is price,
with criteria such as destination city, time of flights and convenience of travel to and from airports
being market-qualifying criteria. For others, notably business travellers, the order-winning criteria
may be in-flight service or total travel time. Consequently, an operations strategy should be
developed that will satisfy market-qualifying criteria but excel at order-winning criteria for the
market segment that the operations wishes to serve.
Platts and Gregory (1990) use an approach that audits the products or groups of products that the
organization offers to its markets. The aim is to identify any gaps between market requirements for
particular products and services and the performance of the organization’s operations in delivering
those products and services. First, the market requirements for the product or service are analysed
in terms of various competitive factors (such as cost, quality, reliability). The performance of the
organization’s operations against those factors are then assessed. An operations strategy should be
developed that will enable operations to match the level of performance required by customers in
each of the competitive criteria.
Operations-led The operations-led perspective is one in which its excellence in operations is used to
drive the organization’s strategy. This is in line with the Hayes and Wheelwright stage 4 organization
and fits with the resourced-based view (RBV) of strategy that currently dominates the strategic
management literature. The premise of the RBV is that superior performance comes from the way
that an organization acquires, develops and deploys its resources and builds its capabilities rather
than the way it positions itself in the marketplace (Wernerfelt, 1984; Barney, 1991). Thus, the
process of strategy development should be based on a sound understanding of current operational
capabilities and an analysis of how these could be developed in the future. This can then provide the
basis for decisions about which markets are likely to be the best in which to deploy current and
future capabilities, which competitors are likely to be most vulnerable and how attacks from
competitors might best be countered (Hayes et al., 2005). Perhaps the best-known example of an
operations-led strategy is Toyota, whose operations have been synonymous with the lean production
model of operations excellence (see Chapter 10). More recently, Amazon seem to be emerging as an
example of operations-led in digital business.
Mills et al. (2002) have developed methods through which organizations can apply these ideas in
practice. These involve undertaking an analysis of the resources that have underpinned the activities
of a business unit over an extended period of time (at least the previous three to five years). Six
resource categories, which are not mutually exclusive, are used: tangible resources, knowledge
resources skills and experience, systems and procedural resources, cultural resources and values,
network resources, and resources important for change. The resources are evaluated against three
criteria: value, sustainability and versatility. Resources that individually or collectively score highly in
these criteria are considered to be important resources. They are sources of existing or potential
competitive advantage to the organization.
HE MEASUREMENT OF CAPACITYIn the same way that capacity is difficult to define, it is also difficult
to measure. Only in operations producing standardized products using a repetitive process is the
measurement of capacity likely to be straightforward. There are essentially two approaches to
measuring capacity. One is to measure units of input of a process, the other to measure units of
output. So the capacity of a machine might be measured in terms of the number of machine hours
available to operate (input), or in terms of the number of items processed (output). Similarly, a
hospital might measure capacity in terms of the number of beds available (input), or in terms of the
number of inpatients treated.
Any operation will have a theoretical capacity. This is normally referred to as the design capacity, the
level of output that can be achieved by operating continuously at maximum rate. However, this level
of capacity is not likely to be achievable in reality, especially over an extended period of time. Even a
plant intended for 24 hours a day, seven days a week operation will need some down time to allow
for repair and maintenance to machinery. There may also be unavoidable operating time losses due
to machine changeovers, or to allow time for operators to change shifts. Effective capacity is the term
used to describe the capacity after deduction of planned stoppages. Actual output is that achieved
operating under normal working conditions. That is likely to be less than effective capacity due to
unplanned or avoidable stoppages due to machine breakdowns, absenteeism, quality problems,
material shortages, and so on. Actual output can be compared to design and effective capacity by
calculating the ratios:
Design capacity is the theoretical output that could be achieved by operating continuously
throughout a given period at maximum rate.
Effective capacity is the output achievable in a given period after deduction of output lost due to
planned stoppages. A food canning plant is capable of filling 100 cans per minute and is operated for
24 hours days, seven days a week. In a certain week, the record of lost production time and its causes
was as follows:
»Routine machine maintenance: 21 hours
»Product changeovers: 16 hours
»Shift changeovers: 9 hours
»Routine quality checks: 8 hours
»Machine breakdowns: 6 hours
»Labour shortages: 12 hours
»Quality problems: 7 hours
»Material shortages: 5 hours
Calculate the utilization and efficiency of the plant for this week.
design capacity = 168 hours per week = 1,008,000 cans per week
planned losses = 21 + 16 + 9 + 8 hours = 54 hours = 324,000 cans
avoidable losses = 6 + 12 + 7 + 5 hours = 30 hours = 180,000 cans
effective capacity = design capacity − planned losses = 168 − 54 = 114 hours
actual output = effective capacity − avoidable losses = 114 − 30 = 84 hours Calculation of capacity and
its use in the calculation of performance figures is often a topic of debate inside an organization.
Even if agreement can be reached within a single organization on how to do this, there is typically no
agreed or standard approach within its industry, let alone across industry sectors. This makes
comparisons very difficult. Any discussion of capacity needs to be approached with extreme caution
and a clear understanding of definitions and terminology established before any progress is likely to
be made.
While achieving a high level of utilization may seem desirable, low figures may not always be
indicative of poor performance. This might, for example, be caused by a lack of demand, rather than
machine breakdowns, labour unrest or materials shortages. Neither is it always sensible to seek to
operate at high levels of utilization. This might, for example, lead to necessary equipment
maintenance being ignored. It can also create pressure to carry excess inventory, especially in the
form of raw materials and excess labour, to avoid having to stop operations due to input shortages.
As discussed later in this chapter, in customer service operations, having insufficient excess capacity
can lead to unacceptably long waiting times for customers.
FORECASTING DEMAND
The challenge of managing capacity is one of matching supply and demand. It would obviously be
easier to arrange to provide for an appropriate level of capacity if future demand was known.
However, as this is usually not the case, organizations have to try to make some kind of forecast of
likely future demand. Forecasting future demand is important both in the longer term and the
shorter term. Longer-term forecasts are needed when considering the design of new products and
services and when planning future levels of capacity, for example by investing in new facilities and
equipment. Shorter-term forecasting is needed in order to manage existing capacity in the most
effective and efficient manner. There are many different forecasting techniques, the detailed
consideration of which is beyond the scope of this book. There are two basic approaches to
forecasting. One relies on quantitative methods, the other qualitative methods.
Forecasting is the act of predicting the likely level of future demand for products and services.
Forecasting methods can be either quantitative or qualitative.
Quantitative methods are either based on time series analysis or causal analysis.
»Time series analysis essentially involves extrapolating past data into the future. Analysts use
mathematical techniques to look for patterns in the data over time. At its simplest, this might involve
merely smoothing out random fluctuations in the data by averaging the data over a longer time
period using moving average calculations (e.g. for a month, a quarter, or even a year) or by using
exponential smoothing techniques. Sometimes no patterns can be found in the data using such
approaches, in which case it might be possible to decompose the data into up to four components:
trend, cyclical, seasonal and random. A trend is a gradual change in the data over time. Cyclical
movements are recurring patterns in the data occurring over a period of more than one year.
Seasonal movements are recurring patterns in the data occurring over a period of less than one year.
Random movements are irregular deviations in the data that cannot be predicted. The idea behind
decomposition analysis is that if cyclical and seasonal effects can be isolated and understood, then
the trend can more easily be separated from random movements. Decomposition analysis relies on
more sophisticated mathematical techniques, for which there are a number of software packages
available (these are often to be found in standard spreadsheet programs). The advantage of time
series analysis methods is that they are relatively easy and cheap to use. However, they are based on
the premise that the past can be used to predict the future, which may not prove to be the case.
»Causal analysis seeks to identify and model any cause and effect relationship between demand data
and some other variable. For example, sales might be related to spending on advertising. Sales of
some products are weather dependent; specifically, sales of ice cream and beer are temperaturedependent. Causal forecasting uses techniques such as linear regression, curvilinear regression and
multiple regression to establish relationships between demand and one or more variables, and
derive a model for their behaviour. The science of econometrics tries to model the behaviour of
entire national economies. Like decomposition analysis, causal analysis relies on computer software
packages (also often to be found in standard spreadsheet programs). Causal analysis methods are
based on the premise that past relationships will hold up in the future. They are more complex, and
hence more costly to use, than simple time series analysis. However, increasing levels of complexity
and sophistication do not always make for more accurate forecasts.
Qualitative methods use subjective techniques based on estimates and judgement to try to predict
future demand. There are a number of techniques, including:
»Market surveys: Data is collected from customers about their future buying intentions. In mass
consumer markets, this is likely to involve conducting a survey of a sample of customers. The
accuracy of any survey depends on many factors, including the design of the questionnaire, the use
of an appropriate sampling method, and the extent to which customers’ replies can be trusted.
Surveys can be costly and time-consuming.
»Delphi studies: These involve canvassing the opinions of a panel of experts, questioning them
independently about future trends. Their initial views are then collated and circulated anonymously
to all group members, who are then each invited to refine their opinions. The process continues until
a group consensus is reached. This can then be used to provide a guide to future demand.
»Scenario planning: This gives a structure to managers’ thinking about the future. The idea is that a
team of experts meet to construct a small number of likely future ‘scenarios’ that the organization
might face. Each scenario is based on different combinations of likely future situations. Future
demand is then assessed for each of the scenarios. The strength of this technique is that it requires
managers to think about how they would respond to a number of different possible futures.
In reality, organizations often use a number of different forecasting methods. Unfortunately, none of
them have a particularly good record of accurately predicting future demand. The longer the time
horizon of the forecast, the less accurate it is likely to turn out to be. Similarly, it is more difficult to
forecast in some business contexts and some markets are much more volatile than others. For
example, at the moment, some parts of the world have been experiencing very rapid rates of growth.
It is very difficult to know whether these rates can be sustained over longer periods of time. Thus,
organizations seeking to serve new and unfamiliar markets are faced with high levels of risk and
uncertainty. Nonetheless, any forecast is almost certainly better than none. Arguably, the mere act of
thinking about the future forces managers to consider how they might best respond to changes in
demand, no matter how volatile and rapid those changes might be. Although practising operations
managers will invariably call for better and more accurate forecasting, in an increasingly unstable
business environment this is easier said than done. It might therefore be better for managers to
concentrate more effort on devising ways of increasing flexibility in order to increase the
responsiveness of their operations.
TAKING IT FURTHER
HE MEASUREMENT OF CAPACITYIn the same way that capacity is difficult to define, it is also difficult
to measure. Only in operations producing standardized products using a repetitive process is the
measurement of capacity likely to be straightforward. There are essentially two approaches to
measuring capacity. One is to measure units of input of a process, the other to measure units of
output. So the capacity of a machine might be measured in terms of the number of machine hours
available to operate (input), or in terms of the number of items processed (output). Similarly, a
hospital might measure capacity in terms of the number of beds available (input), or in terms of the
number of inpatients treated.
Any operation will have a theoretical capacity. This is normally referred to as the design capacity, the
level of output that can be achieved by operating continuously at maximum rate. However, this level
of capacity is not likely to be achievable in reality, especially over an extended period of time. Even a
plant intended for 24 hours a day, seven days a week operation will need some down time to allow
for repair and maintenance to machinery. There may also be unavoidable operating time losses due
to machine changeovers, or to allow time for operators to change shifts. Effective capacity is the term
used to describe the capacity after deduction of planned stoppages. Actual output is that achieved
operating under normal working conditions. That is likely to be less than effective capacity due to
unplanned or avoidable stoppages due to machine breakdowns, absenteeism, quality problems,
material shortages, and so on. Actual output can be compared to design and effective capacity by
calculating the ratios:
Design capacity is the theoretical output that could be achieved by operating continuously
throughout a given period at maximum rate.
Effective capacity is the output achievable in a given period after deduction of output lost due to
planned stoppages. A food canning plant is capable of filling 100 cans per minute and is operated for
24 hours days, seven days a week. In a certain week, the record of lost production time and its causes
was as follows:
»Routine machine maintenance: 21 hours
»Product changeovers: 16 hours
»Shift changeovers: 9 hours
»Routine quality checks: 8 hours
»Machine breakdowns: 6 hours
»Labour shortages: 12 hours
»Quality problems: 7 hours
»Material shortages: 5 hours
Calculate the utilization and efficiency of the plant for this week.
design capacity = 168 hours per week = 1,008,000 cans per week
planned losses = 21 + 16 + 9 + 8 hours = 54 hours = 324,000 cans
avoidable losses = 6 + 12 + 7 + 5 hours = 30 hours = 180,000 cans
effective capacity = design capacity − planned losses = 168 − 54 = 114 hours
actual output = effective capacity − avoidable losses = 114 − 30 = 84 hours Calculation of capacity and
its use in the calculation of performance figures is often a topic of debate inside an organization.
Even if agreement can be reached within a single organization on how to do this, there is typically no
agreed or standard approach within its industry, let alone across industry sectors. This makes
comparisons very difficult. Any discussion of capacity needs to be approached with extreme caution
and a clear understanding of definitions and terminology established before any progress is likely to
be made.
While achieving a high level of utilization may seem desirable, low figures may not always be
indicative of poor performance. This might, for example, be caused by a lack of demand, rather than
machine breakdowns, labour unrest or materials shortages. Neither is it always sensible to seek to
operate at high levels of utilization. This might, for example, lead to necessary equipment
maintenance being ignored. It can also create pressure to carry excess inventory, especially in the
form of raw materials and excess labour, to avoid having to stop operations due to input shortages.
As discussed later in this chapter, in customer service operations, having insufficient excess capacity
can lead to unacceptably long waiting times for customers.
FORECASTING DEMAND
The challenge of managing capacity is one of matching supply and demand. It would obviously be
easier to arrange to provide for an appropriate level of capacity if future demand was known.
However, as this is usually not the case, organizations have to try to make some kind of forecast of
likely future demand. Forecasting future demand is important both in the longer term and the
shorter term. Longer-term forecasts are needed when considering the design of new products and
services and when planning future levels of capacity, for example by investing in new facilities and
equipment. Shorter-term forecasting is needed in order to manage existing capacity in the most
effective and efficient manner. There are many different forecasting techniques, the detailed
consideration of which is beyond the scope of this book. There are two basic approaches to
forecasting. One relies on quantitative methods, the other qualitative methods.
Forecasting is the act of predicting the likely level of future demand for products and services.
Forecasting methods can be either quantitative or qualitative.
Quantitative methods are either based on time series analysis or causal analysis.
»Time series analysis essentially involves extrapolating past data into the future. Analysts use
mathematical techniques to look for patterns in the data over time. At its simplest, this might involve
merely smoothing out random fluctuations in the data by averaging the data over a longer time
period using moving average calculations (e.g. for a month, a quarter, or even a year) or by using
exponential smoothing techniques. Sometimes no patterns can be found in the data using such
approaches, in which case it might be possible to decompose the data into up to four components:
trend, cyclical, seasonal and random. A trend is a gradual change in the data over time. Cyclical
movements are recurring patterns in the data occurring over a period of more than one year.
Seasonal movements are recurring patterns in the data occurring over a period of less than one year.
Random movements are irregular deviations in the data that cannot be predicted. The idea behind
decomposition analysis is that if cyclical and seasonal effects can be isolated and understood, then
the trend can more easily be separated from random movements. Decomposition analysis relies on
more sophisticated mathematical techniques, for which there are a number of software packages
available (these are often to be found in standard spreadsheet programs). The advantage of time
series analysis methods is that they are relatively easy and cheap to use. However, they are based on
the premise that the past can be used to predict the future, which may not prove to be the case.
»Causal analysis seeks to identify and model any cause and effect relationship between demand data
and some other variable. For example, sales might be related to spending on advertising. Sales of
some products are weather dependent; specifically, sales of ice cream and beer are temperaturedependent. Causal forecasting uses techniques such as linear regression, curvilinear regression and
multiple regression to establish relationships between demand and one or more variables, and
derive a model for their behaviour. The science of econometrics tries to model the behaviour of
entire national economies. Like decomposition analysis, causal analysis relies on computer software
packages (also often to be found in standard spreadsheet programs). Causal analysis methods are
based on the premise that past relationships will hold up in the future. They are more complex, and
hence more costly to use, than simple time series analysis. However, increasing levels of complexity
and sophistication do not always make for more accurate forecasts.
Qualitative methods use subjective techniques based on estimates and judgement to try to predict
future demand. There are a number of techniques, including:
»Market surveys: Data is collected from customers about their future buying intentions. In mass
consumer markets, this is likely to involve conducting a survey of a sample of customers. The
accuracy of any survey depends on many factors, including the design of the questionnaire, the use
of an appropriate sampling method, and the extent to which customers’ replies can be trusted.
Surveys can be costly and time-consuming.
»Delphi studies: These involve canvassing the opinions of a panel of experts, questioning them
independently about future trends. Their initial views are then collated and circulated anonymously
to all group members, who are then each invited to refine their opinions. The process continues until
a group consensus is reached. This can then be used to provide a guide to future demand.
»Scenario planning: This gives a structure to managers’ thinking about the future. The idea is that a
team of experts meet to construct a small number of likely future ‘scenarios’ that the organization
might face. Each scenario is based on different combinations of likely future situations. Future
demand is then assessed for each of the scenarios. The strength of this technique is that it requires
managers to think about how they would respond to a number of different possible futures.
In reality, organizations often use a number of different forecasting methods. Unfortunately, none of
them have a particularly good record of accurately predicting future demand. The longer the time
horizon of the forecast, the less accurate it is likely to turn out to be. Similarly, it is more difficult to
forecast in some business contexts and some markets are much more volatile than others. For
example, at the moment, some parts of the world have been experiencing very rapid rates of growth.
It is very difficult to know whether these rates can be sustained over longer periods of time. Thus,
organizations seeking to serve new and unfamiliar markets are faced with high levels of risk and
uncertainty. Nonetheless, any forecast is almost certainly better than none. Arguably, the mere act of
thinking about the future forces managers to consider how they might best respond to changes in
demand, no matter how volatile and rapid those changes might be. Although practising operations
managers will invariably call for better and more accurate forecasting, in an increasingly unstable
business environment this is easier said than done. It might therefore be better for managers to
concentrate more effort on devising ways of increasing flexibility in order to increase the
responsiveness of their operations.
TAKING IT FURTHER
HE MEASUREMENT OF CAPACITYIn the same way that capacity is difficult to define, it is also difficult
to measure. Only in operations producing standardized products using a repetitive process is the
measurement of capacity likely to be straightforward. There are essentially two approaches to
measuring capacity. One is to measure units of input of a process, the other to measure units of
output. So the capacity of a machine might be measured in terms of the number of machine hours
available to operate (input), or in terms of the number of items processed (output). Similarly, a
hospital might measure capacity in terms of the number of beds available (input), or in terms of the
number of inpatients treated.
Any operation will have a theoretical capacity. This is normally referred to as the design capacity, the
level of output that can be achieved by operating continuously at maximum rate. However, this level
of capacity is not likely to be achievable in reality, especially over an extended period of time. Even a
plant intended for 24 hours a day, seven days a week operation will need some down time to allow
for repair and maintenance to machinery. There may also be unavoidable operating time losses due
to machine changeovers, or to allow time for operators to change shifts. Effective capacity is the term
used to describe the capacity after deduction of planned stoppages. Actual output is that achieved
operating under normal working conditions. That is likely to be less than effective capacity due to
unplanned or avoidable stoppages due to machine breakdowns, absenteeism, quality problems,
material shortages, and so on. Actual output can be compared to design and effective capacity by
calculating the ratios:
Design capacity is the theoretical output that could be achieved by operating continuously
throughout a given period at maximum rate.
Effective capacity is the output achievable in a given period after deduction of output lost due to
planned stoppages. A food canning plant is capable of filling 100 cans per minute and is operated for
24 hours days, seven days a week. In a certain week, the record of lost production time and its causes
was as follows:
»Routine machine maintenance: 21 hours
»Product changeovers: 16 hours
»Shift changeovers: 9 hours
»Routine quality checks: 8 hours
»Machine breakdowns: 6 hours
»Labour shortages: 12 hours
»Quality problems: 7 hours
»Material shortages: 5 hours
Calculate the utilization and efficiency of the plant for this week.
design capacity = 168 hours per week = 1,008,000 cans per week
planned losses = 21 + 16 + 9 + 8 hours = 54 hours = 324,000 cans
avoidable losses = 6 + 12 + 7 + 5 hours = 30 hours = 180,000 cans
effective capacity = design capacity − planned losses = 168 − 54 = 114 hours
actual output = effective capacity − avoidable losses = 114 − 30 = 84 hours Calculation of capacity and
its use in the calculation of performance figures is often a topic of debate inside an organization.
Even if agreement can be reached within a single organization on how to do this, there is typically no
agreed or standard approach within its industry, let alone across industry sectors. This makes
comparisons very difficult. Any discussion of capacity needs to be approached with extreme caution
and a clear understanding of definitions and terminology established before any progress is likely to
be made.
While achieving a high level of utilization may seem desirable, low figures may not always be
indicative of poor performance. This might, for example, be caused by a lack of demand, rather than
machine breakdowns, labour unrest or materials shortages. Neither is it always sensible to seek to
operate at high levels of utilization. This might, for example, lead to necessary equipment
maintenance being ignored. It can also create pressure to carry excess inventory, especially in the
form of raw materials and excess labour, to avoid having to stop operations due to input shortages.
As discussed later in this chapter, in customer service operations, having insufficient excess capacity
can lead to unacceptably long waiting times for customers.
FORECASTING DEMAND
The challenge of managing capacity is one of matching supply and demand. It would obviously be
easier to arrange to provide for an appropriate level of capacity if future demand was known.
However, as this is usually not the case, organizations have to try to make some kind of forecast of
likely future demand. Forecasting future demand is important both in the longer term and the
shorter term. Longer-term forecasts are needed when considering the design of new products and
services and when planning future levels of capacity, for example by investing in new facilities and
equipment. Shorter-term forecasting is needed in order to manage existing capacity in the most
effective and efficient manner. There are many different forecasting techniques, the detailed
consideration of which is beyond the scope of this book. There are two basic approaches to
forecasting. One relies on quantitative methods, the other qualitative methods.
Forecasting is the act of predicting the likely level of future demand for products and services.
Forecasting methods can be either quantitative or qualitative.
Quantitative methods are either based on time series analysis or causal analysis.
»Time series analysis essentially involves extrapolating past data into the future. Analysts use
mathematical techniques to look for patterns in the data over time. At its simplest, this might involve
merely smoothing out random fluctuations in the data by averaging the data over a longer time
period using moving average calculations (e.g. for a month, a quarter, or even a year) or by using
exponential smoothing techniques. Sometimes no patterns can be found in the data using such
approaches, in which case it might be possible to decompose the data into up to four components:
trend, cyclical, seasonal and random. A trend is a gradual change in the data over time. Cyclical
movements are recurring patterns in the data occurring over a period of more than one year.
Seasonal movements are recurring patterns in the data occurring over a period of less than one year.
Random movements are irregular deviations in the data that cannot be predicted. The idea behind
decomposition analysis is that if cyclical and seasonal effects can be isolated and understood, then
the trend can more easily be separated from random movements. Decomposition analysis relies on
more sophisticated mathematical techniques, for which there are a number of software packages
available (these are often to be found in standard spreadsheet programs). The advantage of time
series analysis methods is that they are relatively easy and cheap to use. However, they are based on
the premise that the past can be used to predict the future, which may not prove to be the case.
»Causal analysis seeks to identify and model any cause and effect relationship between demand data
and some other variable. For example, sales might be related to spending on advertising. Sales of
some products are weather dependent; specifically, sales of ice cream and beer are temperaturedependent. Causal forecasting uses techniques such as linear regression, curvilinear regression and
multiple regression to establish relationships between demand and one or more variables, and
derive a model for their behaviour. The science of econometrics tries to model the behaviour of
entire national economies. Like decomposition analysis, causal analysis relies on computer software
packages (also often to be found in standard spreadsheet programs). Causal analysis methods are
based on the premise that past relationships will hold up in the future. They are more complex, and
hence more costly to use, than simple time series analysis. However, increasing levels of complexity
and sophistication do not always make for more accurate forecasts.
Qualitative methods use subjective techniques based on estimates and judgement to try to predict
future demand. There are a number of techniques, including:
»Market surveys: Data is collected from customers about their future buying intentions. In mass
consumer markets, this is likely to involve conducting a survey of a sample of customers. The
accuracy of any survey depends on many factors, including the design of the questionnaire, the use
of an appropriate sampling method, and the extent to which customers’ replies can be trusted.
Surveys can be costly and time-consuming.
»Delphi studies: These involve canvassing the opinions of a panel of experts, questioning them
independently about future trends. Their initial views are then collated and circulated anonymously
to all group members, who are then each invited to refine their opinions. The process continues until
a group consensus is reached. This can then be used to provide a guide to future demand.
»Scenario planning: This gives a structure to managers’ thinking about the future. The idea is that a
team of experts meet to construct a small number of likely future ‘scenarios’ that the organization
might face. Each scenario is based on different combinations of likely future situations. Future
demand is then assessed for each of the scenarios. The strength of this technique is that it requires
managers to think about how they would respond to a number of different possible futures.
In reality, organizations often use a number of different forecasting methods. Unfortunately, none of
them have a particularly good record of accurately predicting future demand. The longer the time
horizon of the forecast, the less accurate it is likely to turn out to be. Similarly, it is more difficult to
forecast in some business contexts and some markets are much more volatile than others. For
example, at the moment, some parts of the world have been experiencing very rapid rates of growth.
It is very difficult to know whether these rates can be sustained over longer periods of time. Thus,
organizations seeking to serve new and unfamiliar markets are faced with high levels of risk and
uncertainty. Nonetheless, any forecast is almost certainly better than none. Arguably, the mere act of
thinking about the future forces managers to consider how they might best respond to changes in
demand, no matter how volatile and rapid those changes might be. Although practising operations
managers will invariably call for better and more accurate forecasting, in an increasingly unstable
business environment this is easier said than done. It might therefore be better for managers to
concentrate more effort on devising ways of increasing flexibility in order to increase the
responsiveness of their operations.
TAKING IT FURTHER
Barnes, D. (2018) Operations management: an international perspective. London: Palgrave.