Nigel S., Chambers S., Johnson R. Operations Management
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E-business and m-business
The use of internet-based technology, either to support existing business processes or to
create entirely new business opportunities, has come to be known as e-business. The most
obvious impact has been on those operations and business processes that are concerned with
the buying and selling activity (e-commerce). The Internet provided a whole new channel for
communicating with customers. The advantage of Internet selling was that it increased both
reach (the number of customers who could be reached and the number of items they could
be presented with) and richness (the amount of detail which could be provided concerning
both the items on sale and customers’ behaviour in buying them). Traditionally, selling
involved a trade-off between reach and richness. The Internet effectively overcame this trade-
off. However, the Internet had equally powerful implications for the ongoing provision of
services. Figure 8.3 illustrates the relative cost to a retail bank of providing its services using
different channels of communication. With cost savings of this magnitude, internet-based
services have become the preferred medium for many operations.
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Table 8.1 illustrates just a
few of the applications of e-business to operations management.
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Table 8.1 Some applications of e-business to operations management
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Organizational tasks
Design
Purchasing
Supplier
development
Human resource
management
Production
Marketing/sales
and customer
service
Warehousing
E-business tools and systems
WWW-integrated CAD, Hyperlinks, 3D navigation,
Internet for data and information exchange
EDI, Internet purchasing, EFT
WWW-assisted supplier selection, communication
using Internet (e-mails), research on suppliers and
products with WWW and intelligent agents
E-mails, interactive web sites, WWW-based
multimedia applications
B2B e-business, MRP, ERP, SAP, BAAN,
Peoplesoft, IBM e-business (web-integrated)
B2B e-business, Internet ordering, web site for
the company, electronic funds transfer, online
TPS, bar-coding system, ERP, WWW-integrated
inventory management, Internet delivery of
products and services
EDI, EFT, WWW-integrated inventory management
E-business applications and/or contributions
Customer feedback, research on customer
requirements, product design, quality function
deployment, data mining and warehousing
Ordering, fund transfer, supplier selection
Partnership, supplier development
E-recruiting, benefit selection and management,
training and education using WWW
Production planning and control, scheduling,
inventory management, quality control
Product promotion, new sales channels,
direct savings, reduced cycle time, customer
services, Internet sales, selection of distribution
channels, transportation, scheduling,
third-party logistics
Inventory management, forecasting, scheduling
of work force
Figure 8.3 Average transaction cost for bank ‘technologies’
E-business
E-commerce
Reach
Richness
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Mobile business (M-business) is any transaction, involving the transfer of ownership or
rights to use goods and services, which is initiated and/or completed by using mobile access
to computer-mediated networks with the help of an electronic device
7
.’ Or, more generally,
the ability to conduct commerce using a mobile device (e.g. a mobile phone, a PDA or a
laptop) while on the move. Just look at the cards and other personal information that you
carry around; almost all the information can be carried on a mobile telephone: credit cards,
membership cards, cash, pre-paid transport or parking fees, and so on. There are two main
benefits from m-commerce, selling a product or service, for example, micro-payments,
location-based m-commerce and improving productivity, for example by supplying mobile
workers with up-to-date information in order to deliver an effective service, or allowing
mobile workers who are gathering time-critical information (reports, photographs, etc.) to
capture and transmit it.
Although e- and m-business are rather large topics to review effectively in four questions, it
is possible to summarize their impact. What do they do? Allow internal and external sharing of
business information. How do they do it? By connecting individual computers, computer-based
operating systems and mobile devices through area networks and wireless telecommunications
networks by means of internet-based technology. What advantages do they give? Connectivity!
It allows communication between business and personal activities. What constraints do they
impose? Same as for the Internet, plus some extra security concerns for m-business.
Decision support systems (DSSs) and expert systems (ESs)
A decision support system is one which provides information with the direct objective of aid-
ing or supporting managerial decision-making. It does this by storing relevant information,
processing it and presenting it in such a way as to be appropriate to the decision being made.
In this way, it supports managers by helping them to understand the nature of decisions and
their consequences, but it does not actually make the decision itself. Often DSSs are used for
‘what if ’ analyses which explore the (often financial) consequences of changing operations
practice. Expert systems take the idea of DSSs one stage further in that they attempt to ‘solve’
problems that would normally be solved by humans. The key part of an ES is its ‘inference
engine’ which performs the reasoning or formal logic on the rules that have been defined
as governing the decision. These rules are called the ‘knowledge base’ of the ES (which is why
ESs are also called knowledge-based systems). There have been many attempts to utilize the
idea of an ES in operations management. Table 8.2 illustrates some of the decision areas
and questions which have been treated. However, although authorities agree that ESs will
become far more important in the future of operations management, not all applications
so far have been totally successful. Return to our four questions. What do they do? Provide
information to assist decision-making (DSS) or make operational decisions (ES). How do
they do it? Use data storage, models and presentation formats to structure information and
present consequences of decisions (DSS) and by mimicking human decision-making using
data, knowledge bases and an inference engine (ES). What benefits do they give? Speed and
sophistication of decision-making (DSS) and can take routine decision-making out of human
hands (ES). What constraints do they impose? Can be expensive to model human decision-
making, can lead to ‘over-analysis’ and is dependent on quality of data and models.
Automatic identification technologies
Back in 1973 the Universal Product Code or bar code was developed that enabled a part or
product type to be identified when read by a bar code scanner. Now bar codes are used to
speed up checkout operations in most large supermarkets. However, they also have a role
to play in many of the stages in the supply chain that delivers products into retail outlets.
During manufacture and in warehouses bar codes are used to keep track of products passing
through processes. But bar codes do have some disadvantages. It is sometimes difficult to align
the item so that the bar code can be read conveniently, items can only be scanned one by one,
most significantly, the bar code only identifies the type of item not a specific item itself. That
is, the code identifies that an item is, say, a can of one type of drink rather than one specific
M-business
Decision support system
Expert systems
Bar code
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can. Yet these drawbacks can be overcome through the use of radio frequency identification
(RFID). Here an electronic product code (ePC) that is a unique number, 96 bits long, is
embedded in a memory chip or smart tag. These tags are put on individual items so that
each item has its own unique identifying code. At various points during its manufacture,
distribution, storage and sale each smart tag can be scanned by a wireless radio frequency
‘reader’. This can transmit the item’s embedded identify code to a network such as the Internet
(see Figure 8.4). RFID could help operations save significant amounts of money in lost, stolen
or wasted products by helping manufacturers, distribution companies and retailers to pinpoint
exactly where every item is in the supply chain. So, for example, if a product had to be recalled
because of a health-risk scare, the exact location of every potentially dangerous product
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Table 8.2 Examples of the application of expert systems in operations management
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Decision area Typical issues Some current applications
Capacity planning What is a reasonable size for a facility? PEP, CAPLAN
What is the workforce size for our
operation system?
Facility location Where is the best geographic site to locate FADES
the operation?
Facility layout How should we arrange equipment in our CRAFT, CORELAP,
facility site? WORKPLACE DESIGNER
Aggregate planning What should be the output rates and staffing PATRIARCH, CAPLANLITE
levels for this quarter?
Product design Does the design of the product fit the firm’s XCON, CDX
capability to produce it?
Scheduling Which customers or jobs should receive top ISIS, MARS
priority?
Quality management How do we best achieve our quality goals? PL DEFT
Is the process capable of meeting the
specifications?
Inventory control How much inventory do we need in our store? IVAN, LOGIX, RIM
How should we control it?
Maintenance Where do we have a problem in our DELTA/CATS
equipment? What kind of measures should
we take to control or remove this problem?
Some hospitals now
use RFID technology to
improve patients’ safety.
Patients are given an arm
band with an RFID chip.
This contains all data on
the patient’s health
history, required
medication, allergies and
so on. It helps to prevent
patients being given
inappropriate treatment.
Radio-frequency
identification (RFID)
Source: Rex Features
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could be immediately identified. Shoppers could easily scan products to learn more about
its characteristics and features while they are in the store; waiting at checkout counters could
be eliminated because items will be scanned automatically by readers; the bill could even be
automatically debited from your personal account as you leave the store. There are also
potential benefits in tracking products after they leave the store. Data on how customers use
products could be collected automatically and accurate recycling of waste materials would be
made considerably easier. However, there are significant issues regarding customer privacy
in extending data capture from products beyond the checkout.
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Figure 8.4 Using radio-frequency identification for control of operations processes
The idea of Auto-ID opens up many ethical issues. People see its potential and its dangers
in very different ways. Take the following two statements.
‘We are on the brink of a revolution of “smart products” that will interconnect everyday
objects, consumers and manufacturers in a dynamic cycle of world commerce. ...The
vision of the Auto-ID centre is to create a universal environment in which computers
understand the world without help from human beings.’
‘Supermarket cards and other retail surveillance devices are merely the opening volley
of the marketers’ war against consumers. If consumers fail to oppose these practices
now our long-term prospects may look like something from a dystopian science-fiction
novel. . . . though many Auto-ID proponents appear focused on inventory and supply
chain efficiency, others are developing financial and consumer applications that, if
adopted, will have chilling effects on consumers’ ability to escape the oppressive
surveillance of manufacturers, retailers, and marketers. Of course, government and law
enforcement will be quick to use the technology to keep tabs on citizens as well.’
It is this last issue which particularly scares some civil liberties activists. Keeping track
of items within a supply chain is a relatively uncontentious issue. Keeping track of items
when those items are identified with a particular individual going about their everyday
lives, is far more problematic. So, beyond the checkout for every arguably beneficial
application there is also potential for misuse. For example, smart tags could drastically
reduce theft because items could automatically report when they are stolen, their tags
serving as a homing device pinpoint their exact location. But, similar technology could be
used to trace any citizen, honest or not.
Critical commentary
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Customer-processing technology
Although, customer-processing operations were once seen as ‘low-technology’, now pro-
cess technology is very much in evidence in many services. In any airline flight, for example,
e-ticket reservation technology, check-in technology, the aircraft and its in-flight entertain-
ment, all play vital parts in service delivery. Increasingly, the human element of service is
being reduced with customer-processing technology being used to give an acceptable level
of service while significantly reducing costs. Two types of customer-processing technologies
are used to do this: those that you interact with yourself and those that are operated by an
intermediary.
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The first milking machines were introduced to grateful
farmers over 100 years ago. Until recently, however, they
could not operate without a human hand to attach the
devices to the cows. This problem has been overcome
by a consortium in the Netherlands which includes the
Dutch government and several private firms. They hope
that the ‘robot milkmaid’ will do away with the farmers’
early morning ritual of milking. Each machine can milk
between 60 and 100 cows a day and ‘processes’ the
cows through a number of stages. Computer-controlled
gates activated by transmitters around the cows’ necks
allow the cows to enter. The machine then checks their
health, connects them to the milking machine and feeds
them while they are being milked. If illness is detected
in any cow, or if the machine for some reason fails to
Short case
Customers are not always
human
9
connect the milking cups to the cow after five attempts,
automatic gates divert it into a special pen where the
farmer can inspect it later. Finally, the machine ushers the
cows out of the system. It also self-cleans periodically
and can detect and reject any impure milk. Rather than
herding all the cows in a ‘batch’ to the milking machine
twice a day, the system relies on the cows being able
to find their own way to the machine. Cows, it would
appear, are creatures of habit. Once they have been
shown the way to the machine a few times, they go
there of their own volition because they know that it will
relieve the discomfort in their udders, which grow heavier
as they fill up. The cows may make the journey to the
machine three or more times per day (see Fig. 8.5).
Farmers also appear to be as much creatures of habit
as their cows, however. Mr Riekes Uneken of Assen,
the Dutch farmer who bought the very first robot milking
machine, admitted, ‘I have a bleeper if things go wrong.
But I still like to get up early in the morning. I just like to
see what goes on.’
Figure 8.5 Cows are also customers
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Technology involving customer interaction
Cars, direct-dial telephones, Internet bookings and purchases, fitness equipment and auto-
matic teller machines (ATMs – cash machines) are all examples of technology with which the
customer interacts directly. In these cases, customers themselves are using active interaction
technology to create the service. On an airline flight, for example, the passenger may choose
to use the aircraft’s entertainment facilities. This is likely to be an individual screen and head-
phones which can be used to view movies or listen to audio entertainment. The passenger
might even make use of telecommunications equipment at the seat to book hotels or rent a
car. In these cases, the customer takes control of the technology. Some customer-processing
technology is passive interactive technology, for example being a ‘passenger’ in an aircraft,
mass transport systems, moving walkways and lifts, cinemas and theme parks. This technology
guides customers rather than the other way around. It ‘processes’ and controls customers by
constraining their actions in some way. This helps to reduce variety in the operation. Some
technology is ‘aware’ of customers but not the other way round, for example, security monitor-
ing technologies in shopping malls or at national frontier customs areas. The objective of
these hidden technologies is to track customers’ movements or transactions in an unobtrusive
way. Supermarkets, for example, can use bar-code scanner technologies (or RFID) to track
the movement of customers around the store and indicate the relationship between the
customers and their propensity to buy particular products.
The nature, benefits and constraints of interactive customer-processing technologies will
vary, but generally the four questions that we have been using to understand technologies can
be answered as follows. What do they do? Allow customers to control, or indirectly facilitate,
some aspect of service. How do they do it? Through interfacing directly or indirectly between
the functionality of the technology and the customer. What benefits do they give? Usually some
combination of greater customer control, availability of service, speed of response, range of
services and cost savings to the operation. What constraints do they impose? Active interaction
technologies can allow customers ‘visibility’ of operational systems so must be secure and
designed to facilitate navigation. Hidden technologies must be sensitive to customer privacy.
Interaction with technology through an intermediary
Book an airline flight on the Internet, and you are using direct customer-processing technology,
but call or visit a travel agent and they will do it for you. You are ‘using’ technology through
an intermediary. The benefits to the customer may be a more flexible service and the use of
specialist knowledge. An intermediary dealing with the complex airline systems may be able to
obtain better deals. In such cases, the customer may ‘navigate’ or guide the process but does not
Active interaction
technology
Passive interaction
technology
Hidden technologies
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Table 8.3 Types of customer processing technology
Type of interaction between the customers and the technology Examples
Active interaction with the technology Mobile phone services
Internet-based ordering
E-mail
Cash machines
Passive interaction with the technology Transport systems
Theme park rides
Automatic car wash
Hidden interaction with the technology Security cameras
Retail scanners
Credit card tracking
Interaction with the technology through an intermediary Call centre technology
Travel shop’s booking system
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‘drive’ it. The technology may even be arranged to help customers navigate the process. Other
examples of this kind of technology are the systems used in call centres, the customer support
enquiry lines used by utilities, and some tracking systems in parcel delivery services.
Again, the nature, benefits and constraints of intermediated customer-processing techno-
logies will vary, but generally the four questions can be answered as follows. What do they do?
Allow the operation to facilitate some aspect of service. How do they do it? Through interfacing
between the functionality of the technology and the customer using staff as intermediaries.
What benefits do they give? Allow greater sophistication of customer response, and cost savings
to the operation. What constraints do they impose? The technology is only as good as the staff
who are the intermediaries. Also, customer interaction can seem formulaic, for example as in
the ‘script’ screens used by call centres.
Customer training
If customers are to have direct contact with technology, they must have some idea of how
to operate it. Where customers have an active interaction with technology, the limitations
of their understanding of the technology can be the main constraint on its use. For example,
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It was back in 1996 when Kuniyoshi Konishi became
so frustrated by having to wait to get his hair cut and
then pay over 3,000 yen for the privilege, decided that
there must be a better way to offer this kind of service.
‘Why not,’ he said, ‘create a no-frills barber’s shop where
the customer could get a haircut in ten minutes at a
cost of 1,000 yen (B7)?’ He realized that a combination
of technology and process design could eliminate all
non-essential elements from the basic task of cutting hair.
How is this done? Well, first QB House’s barbers never
handle cash. Each shop has a ticket vending machine
that accepts 1,000 yen bills (and gives no change!) and
issues a ticket that the customer gives the barber in
exchange for the hair cut. Second, QB House does not
take reservations. The shops don’t even have telephones.
Therefore, no receptionist is needed, nor anyone to
schedule appointments. Third, QB House developed
a lighting system to indicate how long customers will
have to wait. Electronic sensors under each seat in the
waiting area and in each barber’s chair track how many
customers are waiting in the shop and different coloured
lights are displayed outside the shop. Green lights
indicate that there is no waiting, yellow lights indicate a
wait of about 5 minutes, and red lights indicate that the
wait may be around 15 minutes. This system can also
keep track of how long it takes for each customer to be
served. Fourth, QB has done away with the traditional
Japanese practice of shampooing their customers
after the haircut to remove any loose hairs. Instead,
the barbers use QB House’s own ‘air wash’ system
Short case
QB House speeds up the cut
10
where a vacuum cleaner hose is pulled down from the
ceiling and used to vacuum the customer’s hair clean.
The QB House system has proved so popular that its
shops (now over 200) can be found not only in Japan
but in many other South East Asian countries such as
Singapore, Malaysia and Thailand. Each year almost
4,000,000 customers experience QB House’s 10-minute
haircuts.
Source: Andy Maluche/Photographers Direct
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even some domestic technology such as video recorders cannot be used to their full potential
by most owners. Other customer-driven technologies can face the same problem, with the
important addition that if customers cannot use technologies such as ATMs, there are serious
commercial consequences for a bank’s customer service. Staff in manufacturing operations
may require several years of training before they are given control of the technology they
operate. Service operations may not have the same opportunity for customer training.
Walley and Amin
11
suggest that the ability of the operation to train its customers in the
use of its technology depends on three factors: complexity, repetition and the variety of tasks
performed by the customer. If services are complex, higher levels of ‘training’ may be needed,
for example, the technologies in theme parks and fast-food outlets rely on customers copy-
ing the behaviour of others. Frequency of use is important because the payback for the
‘investment’ in training will be greater if the customer uses the technology frequently. Also,
customers may, over time, forget how to use the technology, but regular repetition will rein-
force the training. Finally, training will be easier if the customer is presented with a low variety
of tasks. For example, vending machines tend to concentrate on one category of product, so
that the sequence of tasks required to operate the technology remains consistent.
Evaluating process technologies
The most common technology-related decision in which operations managers will be involved
is the choice between alternative technologies. It is an important decision because process
technology can have a significant effect on the operation’s long-term strategic capability;
no one wants to change expensive technologies too frequently. This means that the charac-
teristics of alternative technologies need to be evaluated so that they can be compared. Here
we use three sets of criteria for evaluation.
● Does the technology fit the processing task for which it is intended?
● How does the technology improve the operation’s performance?
● Does the technology give an acceptable financial return?
Does the process technology fit the processing task?
Different process technologies will be appropriate for different types of operations, not
just because they process different transformed resources, but also because they do so at
different levels of volume and variety. High-variety low-volume processes generally require
process technology that is general-purpose, because it can perform the wide range of pro-
cessing activities that high variety demands. High-volume low-variety processes can use
technology that is more dedicated to its narrower range of processing requirements. Within
the spectrum from general-purpose to dedicated-process technologies three dimensions in
particular tend to vary with volume and variety. Figure 8.6 illustrates these three dimensions
of process technology.
● Its degree of ‘automation’
● The capacity of the technology to process work, that is, its ‘scale’ or ‘scalability’
● The extent to which it is integrated with other technologies; that is, its degree of ‘coupling’
or ‘connectivity’.
The degree of automation of the technology
To some extent, all technology needs human intervention. It may be minimal, for example
the periodic maintenance interventions in a petrochemical refinery. Conversely, the person
who operates the technology may be the entire ‘brains’ of the process, for example the
surgeon using keyhole surgery techniques. The ratio of technological to human effort it
Customer-driven
technologies
Customer training
Technology
should reflect the
volume-variety
requirements of the
operation
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employs is sometimes called the capital intensity of the process technology. Generally
processes that have high variety and low volume will employ process technology with
lower degrees of automation than those with higher volume and lower variety. For example,
investment banks trade in highly complex and sophisticated financial ‘derivatives’, often
customized to the needs of individual clients, and each may be worth millions of dollars.
The back office of the bank has to process these deals to make sure that payments are made
on time, documents are exchanged, and so on. Much of this processing will be done using
relatively general-purpose technology such as spreadsheets. Skilled back-office staff are
making the decisions rather than the technology. Contrast this with higher-volume, low-
variety products, such as straightforward equity (stock) trades. Most of these products are
simple and straightforward and are processed in very high volume of several thousand per
day by ‘automated’ technology.
The scale or scalability of the technology
There is usually some discretion as to the scale of individual units of technology. For example,
the duplicating department of a large office complex may decide to invest in a single, very
large, fast copier, or alternatively in several smaller, slower copiers distributed around the
operation’s various processes. An airline may purchase one or two wide-bodied aircraft or a
larger number of smaller aircraft. The advantage of large-scale technologies is that they can
usually process items cheaper than small-scale technologies, but usually need high volume
and can cope only with low variety. By contrast, the virtues of smaller-scale technology are
often the nimbleness and flexibility that is suited to high-variety, lower-volume processing.
For example, four small machines can between them produce four different products simul-
taneously (albeit slowly), whereas a single large machine with four times the output can
produce only one product at a time (albeit faster). Small-scale technologies are also more robust.
Suppose the choice is between three small machines and one larger one. In the first case, if one
machine breaks down, a third of the capacity is lost, but in the second, capacity is reduced
to zero. The advantages of large-scale technologies are similar to those of large-capacity
increments discussed in Chapter 6.
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Figure 8.6 Different process technologies are important for different volume–variety
combinations
Capital intensity
Automation of technology
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The equivalent to scale for some types of information processing technology is scalability.
By scalability we mean the ability to shift to a different level of useful capacity quickly and
cost-effectively. Scalability is similar to absolute scale insomuch as it is influenced by the
same volume–variety characteristics. IT scalability relies on consistent IT platform architec-
ture and the high process standardization that is usually associated with high-volume and
low-variety operations.
The coupling/connectivity of the technology
Coupling means the linking together of separate activities within a single piece of process
technology to form an interconnected processing system. Tight coupling usually gives fast
process throughput. For example, in an automated manufacturing system products flow
quickly without delays between stages, and inventory will be lower – it can’t accumulate
when there are no ‘gaps’ between activities. Tight coupling also means that flow is simple
and predictable, making it easier to keep track of parts when they pass through fewer stages,
or information when it is automatically distributed to all parts of an information network.
However, closely coupled technology can be both expensive (each connection may require
capital costs) and vulnerable (a failure in one part of an interconnected system can affect
the whole system). The fully integrated manufacturing system constrains parts to flow in
a predetermined manner, making it difficult to accommodate products with very different
processing requirements. So, coupling is generally more suited to relatively low variety and
high volume. Higher variety processing generally requires a more open and unconstrained
level of coupling because different products and services will require a wider range of pro-
cessing activities.
How does the technology improve the operation’s performance?
In Chapters 2 and 3, we identified the five operations performance objectives. So a sensible
approach to evaluating the impact of any process technology on an operation is to assess how
it affects the quality, speed, dependability, flexibility and cost performance of the operation.
For example, consider a warehouse that stores spare parts which it packs and distributes to
its customers. It is considering investing in a new ‘retrieval and packing’ system which con-
verts sales orders into ‘retrieval lists’ and uses materials-handling equipment to automatically
pick up the goods from its shelves and bring them to the packing area. The market require-
ments evaluation for this warehouse might be as follows:
● Quality. The impact on quality could be the fact that the computerized system is not prone
to human error, which may previously have resulted in the wrong part being picked off
the shelves.
● Speed. The new system may be able to retrieve items from the shelves faster than human
operators can do safely.
● Dependability. This will depend on how reliable the new system is. If it is less likely to
break down than the operators in the old system were likely to be absent (through illness
etc.), then the new system may improve dependability of service.
● Flexibility. New service flexibility is not likely to be as good as the previous manual
system. For example, there will be a physical limit to the size of products able to be
retrieved by the automatic system, whereas people are capable of adapting to doing new
things in new ways. Mix flexibility will also be poorer than was previously the case, for
the same reason. Volume (and perhaps delivery) flexibility, however, could be better. The
new system can work for longer hours when demand is higher than expected or deadlines
are changed.
● Cost. The new system is certain to require fewer direct operatives to staff the warehouse,
but will need extra engineering and maintenance support. Overall, however, lower labour
costs are likely.
The scale or scalability
of technology
The coupling of
technology
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