Nigel S., Chambers S., Johnson R. Operations Management
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Air traffic controllers have one of the most stressful jobs in
the world. They are responsible for the lives of thousands
of passengers who fly every day in and out of the world’s
airports. Over the last 15 years, the number of planes in the
sky has doubled, leading to congestion at many airports
and putting air traffic controllers under increasing pressure.
The controllers battle to maintain ‘separation standards’
that set the distance between planes as they land and take
off. Sheer volume pushes the air traffic controllers’ skills to
the limit. Jim Courtney, an air traffic controller at LaGuardia
airport in New York, says: ‘There are half a dozen moments
of sheer terror in each year when you wish you did some-
thing else for a living.’
New York – the world’s busiest airspace
The busiest airspace in the world is above New York.
Around 7,500 planes arrive and depart each day at New
York’s three airports, John F. Kennedy, LaGuardia and
Newark. The three airports form a triangle around New York
and are just 15 miles from each other. This requires careful
coordination of traffic patterns, approach and take-off routes,
using predetermined invisible corridors in the sky to keep
the planes away from each other. If the wind changes, all
three airports work together to change the flight paths.
Sophisticated technology fitted to most of the bigger
planes creates a safety zone around the aircraft so that
when two aircraft get near to each other their computers
negotiate which is going to take action to avoid the other
and then alerts the pilot who changes course. Smaller
aircraft, without radar, rely upon vision and the notion of
‘little plane, big sky’.
During its passage into or out of an airport, each plane
will pass through the hands of about eight different con-
trollers. The airspace is divided into sectors controlled by
different teams of air traffic controllers. Tower controllers at
each airport control planes landing and taking off together
with ground controllers who manage the movement of
the planes on the ground around the airport. The TRACON
(Terminal Radar Approach Control) controllers oversee the
surrounding airspace. Each New York air traffic controller
handles about 100 landings and take-offs an hour, about
one every 45 seconds.
TRACON controllers
The 60 TRACON controllers manage different sectors of
airspace, with planes being handed over from one con-
troller to the next. Each controller handles about 15 planes
at a time, yet they never see them. All they see is a blip on
a two-dimensional radar screen, which shows their aircraft
type, altitude, speed and destination. The aircraft, however,
Case study
Air traffic control – a world-class juggling act
are in three-dimensional airspace, flying at different altitudes
and in various directions. The job of the approach con-
trollers is to funnel planes from different directions into an
orderly queue before handing each one over to the tower
controllers for landing.
Tower controllers
The tower controllers are responsible for coordinating
landing and taking off. Newark is New York’s busiest air-
port. During the early morning rush periods, there can be
40 planes an hour coming into land, with about 60 want-
ing to take off. As a result there can be queues of up to
25 planes waiting to depart.
At LaGuardia, there are two runways that cross each
other, one used for take-off and the other for landing. At
peak times, air traffic controllers have to ‘shoot the gap’ –
to get planes to take off in between the stream of landing
aircraft, sometimes less than 60 seconds apart. Allowing
planes to start their take-off as other planes are landing,
using ‘anticipated separation’, keeps traffic moving and
helps deal with increasing volumes of traffic. At peak times,
controllers have to shoot the gap 80 times an hour.
Most airports handle a mixture of large and small
planes, and tower controllers need to be able to calculate
safe take-off intervals in an instant. They have to take into
account aircraft type and capabilities in order to ensure
that appropriate separations can be kept. The faster
planes need to be given more space in front of them than
the slower planes. Wake turbulence – mini-hurricanes which
trail downstream of a plane’s wing tips – is another major
factor in determining how closely planes can follow each
other. The larger the plane and the slower the plane, the
greater the turbulence.
Error-free control is particularly important where people
are being processed, as is the case for these air traffic
controllers
Source: Arup
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Besides the usual ‘large’ planes, controllers have to
manage the small aircraft, business helicopters, traffic
spotter planes and the many sightseeing planes flying over
Manhattan, or up the Hudson towards the Statue of Liberty.
The tower controllers have to control the movement of over
2,000 helicopters and light aircraft that fly through New
York’s airspace every day, being sure to keep them out of
the airspace around each airport used by the arriving and
departing aircraft.
Ground controllers
As an aircraft lands, it is handed over to the ground
controllers who are responsible for navigating it through
the maze of interconnecting taxiways found at most
international airports. Some airport layouts mean that
planes, having landed, have to cross over the runway
where other planes are taking off in order to get to the
terminal. All this needs careful coordination by the ground
controllers.
Some pilots may be unfamiliar with airport layouts and
need careful coaxing. Worse still is poor visibility, fog or
low cloud. At Kennedy airport, the ground radar does not
show aircraft type, so the controllers have to rely upon
memory and constant checking of aircraft position by
radio to ensure they know where each aircraft is at any
time.
Stress
Dealing continually with so many aircraft movements means
that controllers have but a split second to analyse and
react to every situation, yet they need to be right 100 per
cent of the time. Any small error or lapse in concentration
can have catastrophic consequences. They can’t afford
to lose track of a single aircraft, because it may stray into
someone else’s airspace and into the path of another air-
craft. If the computer projects that two planes are about to
fly closer than three miles, the Conflict Alert buzzer sounds
and the controllers have just seconds to make the right
decision and then transmit it to the pilots. Sometimes prob-
lems arise in the planes themselves, such as an aircraft
running short of fuel. Emergency landing procedures cover
such eventualities. At Kennedy airport, they have about one
such incident each day. As one controller remarked, ‘It’s like
an enhanced video game, except you only have one life.’
Questions
1 What does ‘planning and control’ mean to air traffic
controllers?
2 What are the differing problems faced by TRACON,
tower and ground controllers?
3 What sequencing rules do you think the tower
controllers use?
Chapter 10 The nature of planning and control
295
These problems and applications will help to improve your analysis of operations. You
can find more practice problems as well as worked examples and guided solutions on
MyOMLab at
www.myomlab.com.
Re-read the ‘operations management in practice’ at the beginning of the chapter, ‘Joanne manages the
schedule’, and also the short case on Air France. What are the differences and what are the similarities between
the planning and control tasks in these two operations?
A specialist sandwich retailer must order sandwiches at least 8 hours before they are delivered. When they
arrive in the shop, they are immediately displayed in a temperature-controlled cabinet. The average time that
the sandwiches spend in the cabinet is 6 hours. What is the P:D ratio for this retail operation?
It is the start of the week and Marie, Willy and Silvie have three jobs to complete. The three of them can work on
these jobs in any order. Job A requires 4 hours of Marie’s time, 5 hours of Willy’s time and 3 hours of Silvie’s
time. Job B requires 2 hours of Marie’s time, 8 hours of Willy’s time and 7 hours of Silvie’s time. Job C requires
10 hours of Marie’s time, 4 hours of Willy’s time and 5 hours of Silvie’s time. Devise a schedule for Marie, Willy
and Sylvie that details when they will be working on each job. (Assume that they work 7 hours per day.)
For the example above, what is the loading on Marie, Willy and Silvie? If all the jobs have to be finished within
2 days, how much extra time must each of them work?
Step 1 – Make a list of all the jobs you have to do in the next week. Include in this list jobs relating to your work
and/or study, jobs relating to your domestic life, in fact all the things you have to do.
5
4
3
2
1
Problems and applications
➔
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Step 2 – Prioritize all these jobs on a ‘most important’ to ‘least important’ basis.
Step 3 – Draw up an outline schedule of exactly when you will do each of these jobs.
Step 4 – At the end of the week compare what your schedule said you would do with what you actually have
done. If there is a discrepancy, why did it occur?
Step 5 – Draw up you own list of planning and control rules from your experience in this exercise in personal
planning and control.
From your own experience of making appointments at your general practitioner’s surgery, or by visiting whoever
provides you with primary medical care, reflect on how patients are scheduled to see a doctor or nurse.
(a) What do you think planning and control objectives are for a general practitioner’s surgery?
(b) How could your own medical practice be improved?
6
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Goldratt, E.Y. and Cox, J. (1984) The Goal, North River Press.
Don’t read this if you like good novels but do read it if you
want an enjoyable way of understanding some of the com-
plexities of scheduling. It particularly applies to the drum,
buffer, rope concept described in this chapter and it also
sets the scene for the discussion of OPT in Chapter 14.
Kehoe, D.F. and Boughton, N.J. (2001) New paradigms in
planning and control across manufacturing supply chains
– the utilization of Internet technologies, International
Journal of Operations and Production Management, vol. 21,
issue 5/6, 582–93.
Vollmann, T., Berry, W., Whybark, D.C. and Jacobs, F.R.
(2004) Manufacturing Planning and Control Systems for Supply
Chain Management: The Definitive Guide for Professionals,
McGraw-Hill Higher Education. The latest version of the
‘bible’ of manufacturing planning and control.
Selected further reading
www.bpic.co.uk/ Some useful information on general planning and control topics.
www.apics.org. The American professional and education body that has its roots in planning and control activities.
www.opsman.org Lots of useful stuff.
Useful web sites
Now that you have finished reading this chapter, why not visit MyOMLab at
www.myomlab.com where you’ll find more learning resources to help you
make the most of your studies and get a better grade?
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Introduction
Providing the capability to satisfy current and future demand is
a fundamental responsibility of operations management. Get the
balance between capacity and demand right and the operation
can satisfy its customers cost-effectively. Get it wrong and it
will fail to satisfy demand, and have excessive costs. Capacity
planning and control is also sometimes referred to as aggregate
planning and control. This is because, at this level of the planning
and control, demand and capacity calculations are usually
performed on an aggregated basis which does not discriminate
between the different products and services that an operation
might produce. The essence of the task is to reconcile, at a
general and aggregated level, the supply of capacity with the
level of demand which it must satisfy (see Figure 11.1). This
chapter also has a supplement that deals with analytical queuing
models, one way of considering capacity planning and control,
especially in some service operations.
Chapter 11
Capacity planning
and control
Key questions
➤ What is capacity planning and
control?
➤ How are demand and capacity
measured?
➤ What are the alternative ways of
coping with demand fluctuation?
➤ How can operations plan and
control their capacity level?
➤ How can queuing theory be used to
plan capacity?
Figure 11.1 This chapter covers capacity planning and control
Check and improve your understanding of this chapter using self assessment
questions and a personalised study plan, audio and video downloads, and an
eBook – all at www.myomlab.com.
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Britvic is amongst Europe’s leading soft-drink
manufacturers, a major player in a market consuming
nearly ten billion litres a year. Annually, Britvic bottles,
distributes and sells over 1 billion litres of ready-to-drink
soft drinks in around 400 different flavours, shapes and
sizes, including brands such as Pepsi, Tango, Robinsons,
Aqua Libra, Purdey’s and J2O. Every year, Britvic
produce enough cans of soft drinks to stretch three
times around the world, so it has to be a high-volume
and high-speed business. Its six UK factories contain
factory lines producing up to 1,500 cans a minute, with
distribution organized on a giant scale. At the centre of
its distribution network is a National Distribution Centre
(NDC) located at Lutterworth, UK. It is designed to
operate 24 hours a day throughout the year, handling
up to 620 truckloads of soft drinks daily and, together
with a national network of 12 depots, it has to ensure
that 250,000 outlets in the UK receive their orders on
time. Designed and built in collaboration with Wincanton,
a specialist supply chain solutions company, which
now manages Britvic’s NDC, it is capable of holding
up to 140 million cans in its 50,000-pallet ‘High Bay’
warehouse. All information, from initial order to final
delivery, is held electronically. Loads are scanned at
Britvic factories and fed into the ‘Business Planning
and Control System’ that creates a schedule of
receipts. This information is then fed to the Warehouse
Management System and when hauliers arrive at the
NDC, data are passed over to the Movement Control
System that controls the retrieval of pallets from the
High Bay.
Over the year Britvic distribute over 100 million
cases. However, the demand pattern for soft drinks is
seasonal, with short-term changes caused by both
weather and marketing campaigns. Furthermore,
Britvic’s service policy of responding whenever
customers want them to deliver has a dramatic impact
on the NDC and its capacity planning. ‘Our busiest
periods are during the summer and in the run-up to
Christmas, where we expect over 200 trailers in and
out each day – that equates to about 3 million cases
per week. In the quiet periods, especially after
Christmas, we have less than a million cases per week’
(Distribution Manager).
Not only is demand on the NDC seasonal in a
general sense, it can vary from 2,000 pallets one day,
to 6,000 the next, as a result of short-term weather
patterns and variable order patterns from large
customers (supermarkets). Given the lack of space
in the High Bay, it is not possible to simply stock up
for the busy periods, so flexibility and efficiency are
the keys to success.
The NDC uses a number of methods to cope with
demand fluctuation. Most importantly is the use and
development of technology both within the NDC and out
in Britvic’s supply chain. High levels of throughput and
the ability to respond quickly to demand fluctuations
depend on the use of integrated information technology
linked to automated ‘High Bay’ handling technology.
‘Without the automation this plant simply couldn’t
function. You realize how much you need this system
when it breaks down! The other day, multiple errors
in the system meant that in the space of 6 hours
we went from being ahead to having 50 loads waiting to
be processed. That equates to 1,350 pallets or nearly
4 million cans.’
Human resource management is also key in managing
capacity. Every morning the shift manager receives
orders for the day, although further orders can be placed
at any time during the day. The order information allows
the multi-skilled workforce to be allocated effectively.
The daily meetings also allow any problems to be
addressed and dealt with before they become critical.
Finally, by outsourcing the NDC management to
Wincanton, the site is able to second employees from
other Wincanton-owned sites when demand is high.
‘Our other sites around the country have different peaks
and troughs throughout the year which helps us utilize
employee numbers.’
Operations in practice Britvic – delivering drinks to demand
1
Source: Wincanton
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What is capacity management?
The most common use of the word capacity is in the static, physical sense of the fixed
volume of a container, or the space in a building. This meaning of the word is also sometimes
used by operations managers. For example, a pharmaceutical manufacturer may invest in
new 1,000-litre capacity reactor vessels, a property company purchases a 500-vehicle capacity
city-centre car park, and a ‘multiplex’ cinema is built with 10 screens and a total capacity of
2,500 seats. Although these capacity measures describe the scale of these operations, they do
not reflect the processing capacities of these investments. To do this we must incorporate a
time dimension appropriate to the use of assets. So the pharmaceutical company will be con-
cerned with the level of output that can be achieved using the 1,000-litre reactor vessel. If a
batch of standard products can be produced every hour, the planned processing capacity
could be as high as 24,000 litres per day. If the reaction takes four hours, and two hours are used
for cleaning between batches, the vessel may only produce 4,000 litres per day. Similarly, the
car park may be fully occupied by office workers during the working day, ‘processing’ only
500 cars per day. Alternatively, it may be used for shoppers staying on average only one hour,
and theatre-goers occupying spaces for three hours in the evening. The processing capacity
would then be up to 5,000 cars per day. Thus the definition of the capacity of an operation is
the maximum level of value-added activity over a period of time that the process can achieve
under normal operating conditions.
Capacity constraints
Many organizations operate at below their maximum processing capacity, either because there
is insufficient demand completely to ‘fill’ their capacity, or as a deliberate policy, so that the
operation can respond quickly to every new order. Often, though, organizations find themselves
with some parts of their operation operating below their capacity while other parts are at their
capacity ‘ceiling’. It is the parts of the operation that are operating at their capacity ‘ceiling’
which are the capacity constraint for the whole operation. It is these parts of the operation
that are pushed to their capacity ceiling that act as the constraint on the whole operation. For
example, a retail superstore might offer a gift-wrapping service which at normal times can
cope with all requests for its services without delaying customers unduly. At Christmas, how-
ever, the demand for gift wrapping might increase proportionally far more than the overall
increase in custom for the store as a whole. Unless extra resources are provided to increase
the capacity of this micro-operation, it could constrain the capacity of the whole store.
Planning and controlling capacity
Capacity planning and control is the task of setting the effective capacity of the operation
so that it can respond to the demands placed upon it. This usually means deciding how
the operation should react to fluctuations in demand. We have faced this issue before in
Chapter 6 where we examined long-term changes in demand and the alternative capacity
strategies for dealing with the changes. These strategies were concerned with introducing
(or deleting) major increments of physical capacity. We called this task long-term capacity
strategy. In this chapter we are treating the shorter timescale where capacity decisions are
being made largely within the constraints of the physical capacity limits set by the operation’s
long-term capacity strategy.
Medium- and short-term capacity
Having established long-term capacity, operations managers must decide how to adjust the
capacity of the operation in the medium term. This usually involves an assessment of the
demand forecasts over a period of 2–18 months ahead, during which time planned output
Capacity
Capacity constraint
Long-term capacity
strategy
Medium term capacity
planning and control
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can be varied, for example, by changing the number of hours the equipment is used. In
practice, however, few forecasts are accurate, and most operations also need to respond
to changes in demand which occur over a shorter timescale. Hotels and restaurants have
unexpected and apparently random changes in demand from night to night, but also know
from experience that certain days are on average busier than others. So operations managers
also have to make short-term capacity adjustments, which enable them to flex output for
a short period, either on a predicted basis (for example, bank checkouts are always busy at
lunchtimes) or at short notice (for example, a sunny warm day at a theme park).
Aggregate demand and capacity
The important characteristic of capacity planning and control, as we are treating it here, is that
it is concerned with setting capacity levels over the medium and short terms in aggregated
terms. That is, it is making overall, broad capacity decisions, but is not concerned with all
of the detail of the individual products and services offered. This is what ‘aggregated’
means – different products and services are bundled together in order to get a broad view
of demand and capacity. This may mean some degree of approximation, especially if the
mix of products or services being produced varies significantly (as we shall see later in this
chapter). Nevertheless, as a first step in planning and control, aggregation is necessary. For
example, a hotel might think of demand and capacity in terms of ‘room nights per month’,
which ignores the number of guests in each room and their individual requirements, but
is a good first approximation. A woollen knitwear factory might measure demand and
capacity in the number of units (garments) it is capable of making per month, ignoring size,
colour or style variations. Aluminium producers could use tonnes per month, ignoring types
of alloy, gauge and batch size variation. The ultimate aggregation measure is money. For
example, retail stores, which sell an exceptionally wide variety of products, use revenue
per month, ignoring variation in spend, number of items bought, the gross margin of each
item and the number of items per customer transaction. If all this seems very approximate,
remember that most operations have sufficient experience of dealing with aggregated data
to find it useful.
The objectives of capacity planning and control
The decisions taken by operations managers in devising their capacity plans will affect
several different aspects of performance:
● Costs will be affected by the balance between capacity and demand (or output level if
that is different). Capacity levels in excess of demand could mean under-utilization of
capacity and therefore high unit cost.
● Revenues will also be affected by the balance between capacity and demand, but in the
opposite way. Capacity levels equal to or higher than demand at any point in time will
ensure that all demand is satisfied and no revenue lost.
● Working capital will be affected if an operation decides to build up finished goods
inventory prior to demand. This might allow demand to be satisfied, but the organization
will have to fund the inventory until it can be sold.
● Quality of goods or services might be affected by a capacity plan which involved large
fluctuations in capacity levels, by hiring temporary staff for example. The new staff and
the disruption to the routine working of the operation could increase the probability of
errors being made.
● Speed of response to customer demand could be enhanced, either by the build-up of
inventories (allowing customers to be satisfied directly from the inventory rather than
having to wait for items to be manufactured) or by the deliberate provision of surplus
capacity to avoid queuing.
● Dependability of supply will also be affected by how close demand levels are to capacity.
The closer demand gets to the operation’s capacity ceiling, the less able it is to cope with
any unexpected disruptions and the less dependable its deliveries of goods and services
could be.
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Short-term capacity
planning and control
Aggregate planning and
control
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Figure 11.2 The steps in capacity planning and control
● Flexibility, especially volume flexibility, will be enhanced by surplus capacity. If demand
and capacity are in balance, the operation will not be able to respond to any unexpected
increase in demand.
The steps of capacity planning and control
The sequence of capacity planning and control decisions which need to be taken by operations
managers is illustrated in Figure 11.2. Typically, operations managers are faced with a forecast
of demand which is unlikely to be either certain or constant. They will also have some idea of
their own ability to meet this demand. Nevertheless, before any further decisions are taken, they
must have quantitative data on both capacity and demand. So the first step will be to measure the
aggregate demand and capacity levels for the planning period. The second step will be to identify
the alternative capacity plans which could be adopted in response to the demand fluctuations.
The third step will be to choose the most appropriate capacity plan for their circumstances.
Measuring demand and capacity
Forecasting demand fluctuations
Although demand forecasting is usually the responsibility of the sales and/or marketing
functions, it is a very important input into the capacity planning and control decision, and
so is of interest to operations managers. After all, without an estimate of future demand it is
not possible to plan effectively for future events, only to react to them. It is therefore import-
ant to understand the basis and rationale for these demand forecasts. (See the supplement on
forecasting at the end of Chapter 6.) As far as capacity planning and control is concerned,
there are three requirements from a demand forecast.
It is expressed in terms which are useful for capacity planning and control
If forecasts are expressed only in money terms and give no indication of the demands that
will be placed on an operation’s capacity, they will need to be translated into realistic expecta-
tions of demand, expressed in the same units as the capacity (for example, machine hours per
year, operatives required, space, etc.).
Forecasting is a key
input to capacity
planning and control
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It is as accurate as possible
In capacity planning and control, the accuracy of a forecast is important because, whereas
demand can change instantaneously, there is a lag between deciding to change capacity and
the change taking effect. Thus many operations managers are faced with a dilemma. In order
to attempt to meet demand, they must often decide output in advance, based on a forecast
which might change before the demand occurs, or worse, prove not to reflect actual demand
at all.
It gives an indication of relative uncertainty
Decisions to operate extra hours and recruit extra staff are usually based on forecast levels
of demand, which could in practice differ considerably from actual demand, leading to
unnecessary costs or unsatisfactory customer service. For example, a forecast of demand
levels in a supermarket may show initially slow business that builds up to a lunchtime rush.
After this, demand slows, only to build up again for the early evening rush, and it finally
falls again at the end of trading. The supermarket manager can use this forecast to adjust
(say) checkout capacity throughout the day. But although this may be an accurate average
demand forecast, no single day will exactly conform to this pattern. Of equal importance is
an estimate of how much actual demand could differ from the average. This can be found by
examining demand statistics to build up a distribution of demand at each point in the day.
The importance of this is that the manager now has an understanding of when it will be
important to have reserve staff, perhaps filling shelves, but on call to staff the checkouts
should demand warrant it. Generally, the advantage of probabilistic forecasts such as this is
that it allows operations managers to make a judgement between possible plans that would
virtually guarantee the operation’s ability to meet actual demand, and plans that minimize
costs. Ideally, this judgement should be influenced by the nature of the way the business
wins orders: price-sensitive markets may require a risk-avoiding cost minimization plan that
does not always satisfy peak demand, whereas markets that value responsiveness and service
quality may justify a more generous provision of operational capacity.
Seasonality of demand
In many organizations, capacity planning and control is concerned largely with coping with
seasonal demand fluctuations. Almost all products and services have some demand seasonality
and some also have supply seasonality, usually where the inputs are seasonal agricultural
products – for example, in processing frozen vegetables. These fluctuations in demand or
supply may be reasonably forecastable, but some are usually also affected by unexpected
variations in the weather and by changing economic conditions. Figure 11.3 gives some
examples of seasonality, and the short case ‘Producing while the sun shines’ discusses the
sometimes unexpected link between weather conditions and demand levels.
Consider the four different types of operation described previously: a wool knitwear
factor, a city hotel, a supermarket and an aluminium producer. Their demand patterns are
shown in Figure 11.4. The woollen knitwear business and the city hotel both have seasonal
sales demand patterns, but for different reasons: the woollen knitwear business because of
climatic patterns (cold winters, warm summers) and the hotel because of demand from
business people, who take vacations from work at Christmas and in the summer. The retail
supermarket is a little less seasonal, but is affected by pre-vacation peaks and reduced sales
during vacation periods. The aluminium producer shows virtually no seasonality, but is
showing a steady growth in sales over the forecast period.
Weekly and daily demand fluctuations
Seasonality of demand occurs over a year, but similar predictable variations in demand can
also occur for some products and services on a shorter cycle. The daily and weekly demand
patterns of a supermarket will fluctuate, with some degree of predictability. Demand might
be low in the morning, higher in the afternoon, with peaks at lunchtime and after work in
the evening. Demand might be low on Monday and Tuesday, build up during the latter part
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Demand seasonality
Supply seasonality
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of the week and reach a peak on Friday and Saturday. Banks, public offices, telephone sales
organizations and electricity utilities all have weekly and daily, or even hourly, demand
patterns which require capacity adjustment. The extent to which an operation will have
to cope with very short-term demand fluctuations is partly determined by how long its
customers are prepared to wait for their products or services. An operation whose customers
are incapable of, or unwilling to, wait will have to plan for very short-term demand fluctu-
ations. Emergency services, for example, will need to understand the hourly variation in the
demand for their services and plan capacity accordingly.
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Figure 11.3 Many types of operation have to cope with seasonal demand
Figure 11.4 Aggregate demand fluctuations for four organizations
Source: Corbis
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