3 Capacity Planning

CAPACITY PLANNING

Introduction

Capacity can be defined as the maximum

output rate that can be achieved by a facility.

The facility may be an

entire organization,

a division, or

only one machine.

Introduction

Planning for capacity in a company is usually performed at two levels, each corresponding to either

strategic or

tactical decisions.

The first level of capacity decisions is strategic and long-term in nature.

This is where a company decides what investments in new facilities and equipment it should make.

Introduction

Because these decisions are strategic in nature, the company will have to live with them for a long time.

Also, they require large capital expenditures and will have a great impact on the companys ability to conduct business.

The second level of capacity decisions is more tactical in nature, focusing on short-term issues that include planning of workforce, inventories, and day-to-day use of machines.

Importance of Capacity Planning


Capacity planning is the process of establishing

the output rate that can be achieved by a

facility.

If a company does not plan its capacity correctly, it may find that it either does not have enough

output capability to meet customer demands or has too much capacity sitting idle.

In a bakery for example, not having enough capacity would mean not being able to produce

enough baked goods to meet sales.


The bakery would often run out of stock, and customers might start going somewhere else.

Also, the bakery would not be able to take advantage of the true demand available.

On the other hand, if there is too much capacity, the bakery would incur the cost of an unnecessarily large facility that is not being

used, as well as much higher operating costs than necessary.


Planning for capacity is important if a company wants to grow and take full

advantage of demand.

At the same time, capacity decisions are

complicated because they require long-term commitments of expensive resources, such

as large facilities.

Once these commitments have been made, it is

costly to change them.


Think about a business that purchases a larger facility in anticipation of an increase in demand,

only to find that the demand increase does

not occur.

It is then left with a huge expense, no return on its investment, and the need to

decide how to use a partially empty

facility.


Another issue that complicates capacity planning is the fact that capacity is usually

purchased in chunks rather than in smooth increments.

Facilities, such as buildings and equipment, are

acquired in large sizes, and it is virtually

impossible to achieve an exact match between current needs and needs based on

future demand.


Because of the uncertainty of future demand, the overriding capacity planning

decision becomes one of whether to

purchase a larger facility in anticipation of

greater demand or to expand in slightly

smaller but less efficient increments.

Each strategy has its advantages and disadvantages.

When To & How Much

When to increase capacity and how much to increase it are critical decisions.

Three basic strategies for the timing of capacity expansion are:

1. Capacity lead strategy .

2. Capacity lag strategy.

3. Average capacity strategy

(Smoothing with inventories)

Leading & Lagging Strategies

Average Capacity Strategy

1. Capacity Lead Strategy

Capacity is expanded in such a way that there is

always sufficient capacity to meet forecast demand.

Capacity is expanded in anticipation of demand growth.

This aggressive strategy is used to lure customers from competitors who are capacity

constrained or to gain a foothold in a rapidly

expanding market.

1. Capacity Lead Strategy

It also allows companies to respond to unexpected surges in demand and to provide

superior levels of service during peak demand periods.

2. Capacity Lag Strategy

Capacity is expanded in such a way that the demand is always equal to or greater than capacity.

Capacity is increased after an increase in demand has been documented.

This conservative strategy produces a higher return on investment but may lose customers in the process.

It is used in industries with standard products and cost-based or weak competition.

2. Capacity Lag Strategy

The strategy assumes that lost customers will return from competitors after capacity has

expanded.

3. Average Capacity Strategy

Capacity is increased in such a way that the

current capacity plus accumulated inventory can always supply demand.

Capacity is expanded to coincide with average expected demand.

This is a moderate strategy in which managers are certain they will be able to sell at

least some portion of expanded output, and

endure some periods of unmet demand.

3. Average Capacity Strategy

Approximately half of the time capacity leads

demand, and half of the time capacity lags demand.

Advantages/Disadvantages

Advantages Disadvantages

Capacity-leading Strategy

1. Always sufficient capacity to meet demand, therefore revenue is maximised and customers satisfied.

2. Most of the time there is a capacity cushion which can absorb extra demand if forecasts are pessimistic.

3. Any critical start-up problems with new plants are less likely to affect supply to customers.

1. Risks of greater (or even permanent) over-capacity if demand does not reach forecast levels.

2. Capital spending on plant early.



Capacity-lagging

Strategy

1. Always sufficient demand to keep the plants working at full capacity, therefore, unit costs are minimised.

2. Over-capacity problems are minimised if forecasts are optimistic.

3. Capital spending on the plants is delayed.

1. Insufficient capacity to meet demand fully, therefore, reduced revenue and dissatisfied customers.

2. No ability to exploit short-term increases in demand.

3. Under-supply position even worse if there are start-up problems with the new plants.



Smoothing-with-

inventories Strategy

1. All demand is satisfied, therefore, customers are satisfied and revenue maximised.

2. Utilisation of capacity is high and therefore costs are low.

3. Very short-term surges in demand can be met from inventories.

1. The cost of inventories in terms of working capital requirement can be high.

2. This is especially serious at a time when the company requires funds for its capital expansion.

3. Risks of product deterioration and obsolescence.

Measuring Capacity

Measuring Capacity

Although our definition of capacity seems

simple, there is no one way to measure it.

Different people have different

interpretations of what capacity means, and the units of measurement are often very

different.

Table shows some examples of how capacity might be measured by different organizations.

Measuring Capacity

Type Of Business Input Measures Of Capacity

Output Measures Of Capacity

Car Manufacturer Labour hours Cars per shift

Hospital Available beds per month

Number of patients

Pizza shop Worker hours per day No of pizzas per day

Retail store Floor space in sq feet Revenues per day

Electricity company Generator size Megawatts of electricity generated

Measuring Capacity

Note that each business can measure capacity

in different ways and that capacity can be measured using either inputs or outputs.

Output measures, such as the number of cars

per shift, are easier to understand.

However, they do not work well when a company produces many different kinds of

products.

Measuring Capacity

For example, if a television factory produces only one basic model, the weekly capacity could

be described as 2000 televisions.

A government office may have the capacity to print and post 500,000 tax forms per week.

In each case, an output capacity measure is the most appropriate measure because the output

from the operation does not vary in its nature.

Measuring Capacity

But when a much wider range of outputs places varying demands on the process, output

measures of capacity are less useful.

Here input capacity measures are frequently used to define capacity.

For example, the hospital measures its capacity

in terms of its input resources (say beds), because there is not a clear relationship

between the number of beds it has and the

number of patients it treats.

Measuring Available Capacity


Suppose that on the average we can make 20 cakes per day.

However, if we are really pushed, such as during holidays, maybe we can make 30 cakes per day.

Which of these is our true capacity?

We can make 30 cakes per day at a maximum, but we cannot keep up that pace for long.

Saying that 30 per day is our capacity would be misleading.


On the other hand, saying that 20 cakes per day is our capacity does not reflect the fact that

we can, if necessary, push our production to 30

cakes.

Through this example you can see that

different measures of capacity are useful because they provide different kinds of

information.


Following are two of the most common measures of capacity:-

1. Design capacity

2. Effective capacity

1. Design capacity

Design capacity is the maximum output rate that can be achieved by a facility under ideal conditions.

In our example, this is 30 cakes/day. Design capacity can be sustained only for a

relatively short period of time. A company achieves this output rate by using

many temporary measures, such as overtime, over-staffing, maximum use of equipment, and subcontracting.

2. Effective capacity

Effective capacity is the maximum output rate that can be sustained under normal conditions.

These conditions include realistic work schedules and breaks, regular staff levels, scheduled machine maintenance, and none of the temporary measures that are used to achieve design capacity.

Effective capacity is usually lower than design capacity.

In our example, effective capacity is 20 cakes/day.

Measuring Effectiveness of

Capacity Use

Regardless of how much capacity we have, we

also need to measure how well we are utilizing it.

Capacity utilization simply tells us how much of

our capacity we are actually using.

Certainly there would be a big difference if we

were using 50%of our capacity, meaning our facilities, space, labour, and equipment, rather

than 90%.

Capacity Considerations

Capacity utilization can simply be computed as the ratio of actual output over capacity:

Utilization = actual output rate

capacity


However, since we have two capacity measures, we can measure utilization relative to either

design or effective capacity

Utilizationeffective =

Utilizationdesign =

actual output

effective capacity

actual output

design capacity

Example

In the bakery example, we have established that design capacity is 30 cakes per day and

effective capacity is 20 cakes per day. Currently,

the bakery is producing 27 cakes per day. What

is the bakerys capacity utilization relative to both design and effective capacity?

Expanding Capacity

When expanding capacity, management has to choose between one of the following two

alternatives:

1. Purchase one large facility, requiring

one large initial investment.

2. Add capacity incrementally in smaller

chunks as needed.

Expanding Capacity

One Step Expansion

Incremental Expansion

Time

Units

Expanding Capacity

The first alternative means that we would

have a large amount of excess

capacity in the beginning and that our initial costs would be high.

We would also run the risk that demand might

not materialize and we would be left with

unused overcapacity.

On the other hand, this alternative allows us to be prepared for higher demand in the future.

Expanding Capacity

Our best operating level is much higher with this alternative, enabling us to operate

more efficiently when meeting higher demand.

Our costs would be lower in the long run, since one large construction project typically costs less than many smaller construction projects due to startup costs.

Thus, alternative 1 provides greater rewards but is more risky.

Expanding Capacity

Alternative 2 is less risky but does not offer the same opportunities and flexibility.

It is up to management to weigh the risks

versus the rewards in selecting an alternative.


We have seen that changing capacity is not as simple as acquiring the right amount of

capacity to exactly match our needs.

The reason is that capacity is purchased in discrete chunks.

Also, capacity decisions are long term and strategic in nature.


Some of the important implications of capacity that a company needs to consider when

changing its capacity are:

1. Economies of Scale

2. Diseconomies of Scale

3. Focused Factories

4. Subcontractor Networks


Every production facility has a volume of output

that results in the lowest average unit cost.

This is called the facilitys best operating

level .

Figure illustrates how the average unit cost of output is affected by the volume produced.

You can see that as the number of units

produced is increased, the average cost per

unit drops.


Output Produced in Units

Ave

rage

Un

it C

ost

Economies of Scale Diseconomies of Scale

Best Operating Level


The reason is that when a large amount of goods is produced, the costs of production are

spread over that large volume.

These costs include the fixed costs of buildings and facilities, the costs of materials, and processing costs.

The more units are produced, the larger the number of units over which costs can be

spreadthat is, the greater the economies of scale .


The concept of economies of scale is very well known.

It basically states that the average cost of a unit produced is reduced when the amount of output is increased.

You use the concept of economies of scale in your daily life.

Suppose you decide to make cookies in your kitchen. Think about the cost per cookie if you make only five cookies.


There would be a great deal of effortgetting the ingredients, mixing the dough,

shaping the cookiesall for only five cookies.


What if you continued to increase the number of cookies you chose to produce?

For a while, making a few more cookies would not require much additional effort.

However, after a certain point there would be so much material that the kitchen would

become congested. You might have to get someone to help

because there was more work than one person could handle.


You might have to make cookies longer than

expected, and the cleanup job might be

much more difficult.

You would be experiencing diseconomies

of scale .

Diseconomies of scale occur at a point

beyond the best operating level, when the cost of each additional unit made

increases.


Operating a facility close to its best operating level is clearly important because of the impact

on costs.

However, we have to keep in mind that

different facility sizes have different

best operating levels.


In our cookie example, we can see that the number of cookies comfortably produced by

one person in a small kitchen would be much lower than the number produced by

three persons in a large kitchen.

Figure shows how best operating level varies between facilities of different sizes.


Output Produced in Units

Ave

rage

Un

it C

ost

Small

Medium

Large


The concept of the focused factory holds that a

production facility works best when it focuses

on a fairly limited set of production objectives.

This means, for example, that a firm should

not expect to excel in every aspect of manufacturing performance: cost, quality,

delivery speed and reliability, changes in

demand, and flexibility to adapt to new

products.


Rather, it should select a limited set of tasks that contribute the most to corporate

objectives.

For example, consider a company that competes on using the highest quality

component parts in its products.

Due to the high quality of parts, the company

may not be able to offer the final product at

the lowest price.


In this case, the company has made a trade-

off between quality and price.

Similarly, a company that competes on making each product individually based on

customer specifications will likely not be

able to compete on speed.

Here, the trade-off has been made between

flexibility and speed.


One way that large facilities with multiple products can address the issue of trade-offs is using the concept of plant-within-a-plant (PWP), introduced by well-known Harvard professor Wickham Skinner.

The PWP concept suggests that different areas of a facility be dedicated to different products with different competitive priorities.

These areas should be physically separated from one another and should even have their own separate workforce.


As the term suggests, there are multiple plants within one plant, allowing a company to

produce different products that compete on

different priorities.

For example, hospitals use PWP to achieve specialization or focus in a particular area, such

as the cardiac unit, radiology, surgery, or

pharmacy.


Another alternative to having a large production facility is to develop a large network of subcontractors and suppliers who perform a number of tasks.

This is one of the fastest-growing trends today.

Companies are realizing that to be successful in todays market, they need to focus on their core capabilitiesfor example, by hiring third parties or subcontractors to take over tasks that the company does not need to perform itself.


Companies such as American Airlines and Procter & Gamble have hired outside firms to manage noncritical inventories.

Also, many companies are contracting with suppliers to perform tasks that they used to perform themselves.

A good example is in the area of quality management.

Historically, companies performed quality checks on goods received from suppliers.


Today, suppliers and manufacturers work together to achieve the same quality standards,

and much of the quality checking of incoming

materials is performed at the suppliers site.

Another example can be seen in the auto

industry, where manufacturers are placing more responsibility on suppliers to perform

tasks such as design of packaging and

transportation of goods.


By placing more responsibility on

subcontractors and suppliers, a manufacturer can focus on tasks that are critical

to its success, such as product development

and design.

Making Capacity Planning Decisions

The three-step procedure for making capacity planning decisions is as follows

1. Identify Capacity Requirements

2. Develop Capacity Alternatives

3. Evaluate Capacity Alternatives


Long-term capacity requirements are identified

on the basis of forecasts of future demand.

Companies look for long-term patterns such as

trends when making forecasts.

However, long-term patterns are not enough at this stage.

Planning, building, and starting up a new facility

can take well over five years.

Much can happen during that time.


When the facilities are operational, they are

expected to be utilized for many years into the future.

During this time frame numerous changes

can occur in the economy, consumer base,

competition, technology, and demographic factors, as well as in

government regulation and political

events.


Following are the key steps performed while identifying the capacity requirements:

a)Forecasting Capacity

b)Capacity Cushions

c)Strategic Implications

1.a. Forecasting Capacity

Capacity requirements are identified on the basis of forecasts of future demand.

Forecasting at this level is performed using qualitative forecasting methods as already discussed.

Qualitative forecasting methods, such as executive opinion and the Delphi method , use subjective opinions of experts.

These experts may consider inputs from quantitative forecasting models that can numerically compute patterns such as trends.


However, because so many variables can influence demand at this level, the experts use their judgment to validate the quantitative

forecast or modify it based on their own knowledge.

One way to proceed with long-range demand forecasting at this stage is to first

forecast overall market demand.

Then the company can estimate its market share as a percentage of the total.


From that we can compute an estimate of

demand for our company for next few years

by multiplying the overall market demand with the percentage held by our company.

That forecast of demand can then be

translated into specific facility

requirements.

1.b. Capacity Cushions

Companies often add capacity cushions to their regular capacity requirements.

A capacity cushion is an amount of capacity added to the needed capacity in order to provide greater flexibility.

Capacity cushions can be helpful if demand is greater than expected.

Also, cushions can help the ability of a business to respond to customer needs for different products or different volumes.

1.b. Capacity Cushions

Finally, businesses that operate too close to their maximum capacity experience many costs

due to diseconomies of scale and may

also experience deteriorating quality.

1.c. Strategic Implications

Finally, a company needs to consider how much

capacity its competitors are likely to have.

Capacity is a strategic decision, and the position of

a company in the market relative to its competitors is very much determined by its

capacity.

At the same time, plans by all major competitors to increase capacity may signal the

potential for overcapacity in the industry.

1.c. Strategic Implications

Therefore, the decision as to how much capacity to add should be made carefully.


Once a company has identified its capacity

requirements for the future, the next step is to develop alternative ways to modify its

capacity.

One alternative is to do nothing and re-evaluate the situation in the future.

With this alternative, the company would not be able to meet any demands that exceed

current capacity levels.


Choosing this alternative and the time to re-

evaluate the companys needs is a strategic

decision.

The other alternatives require deciding whether to purchase one large facility now or

add capacity incrementally, as discussed earlier

in the slides.


Decision Trees

There are a number of tools that we can use to evaluate our capacity alternatives but the most popular of these tools is the decision tree.

Decision trees are useful whenever we have to evaluate interdependent decisions that must be made in sequence and when there is uncertainty about events.

For that reason, they are especially useful for evaluating capacity expansion alternatives given that future demand is uncertain.


Decision Trees

Remember that our main decision is whether to purchase a large facility or a small one with the

possibility of expansion later.

A decision tree is a diagram that models the

alternatives being considered and the possible

outcomes.

Decision trees help by giving structure to a

series of decisions and providing an objective

way of evaluating alternatives.


Decision Trees

Decision trees contain the following information:

1. Decision points. These are the points in time when decisions, such as whether or not to expand, are made. They are represented by squares, called nodes.

2. Decision alternatives. Buying a large facility and buying a small facility are two decision alternatives. They are represented by branches or arrows leaving a decision point.


Decision Trees

3. Chance events. These are events that could affect the value of a decision. For example, demand could be high or low. Each chance event has a probability or likelihood of occurring. For example, there may be a 60 percent chance of high demand and a 40 percent chance of low demand. Remember that the sum of the probabilities of all chances must add up to 100 percent. Chance events are branches or arrows leaving circular nodes.


Decision Trees

4. Outcomes. For each possible alternative an outcome is listed. In our example, that may be

expected profit for each alternative (expand

now or later) given each chance event (high

demand or low demand).

Decision Trees EXAMPLE

Mr ABC, the owner of XYZ Company, has determined that he needs to expand the facility.

The decision is whether to expand now with a

large facility, incurring additional costs and

taking the risk that demand will not materialize,

or expand now on a smaller scale, knowing that

he will have to consider expanding again in

three years.


He has estimated the following chances for demand:

The likelihood of demand being high is 0.70.

The likelihood of demand being low is 0.30.

He has also estimated profits for each alternative:

Large expansion has an estimated profitability of either $300,000 or $50,000, depending on whether

demand turns out to be high or low.


Small expansion has a profitability of $80,000, assuming that demand is low.

Small expansion with an occurrence of high demand would require considering whether to expand

further. If he expands at that point, his profitability is

expected to be $200,000. If he does not expand

further, profitability is expected to be $150,000.

Develop a decision tree to solve Mr ABCs problem.

Decision Trees SOLUTION

Procedure for Drawing a Decision Tree:

1. Draw a decision tree from left to right. Use

squares to indicate decisions and circles

to indicate chance events.

2. Write probability of each chance event in

parentheses.

3. Write out the outcome for each alternative in the right margin.

1

High Demand (0.7)

High Demand (0.7)

Low Demand (0.3)

Low Demand (0.3)

Expand

Dont Expand

$300,000

$50,000

$80,000

$200,000

$150,000

2


We drew the decision tree from left to right.

To evaluate it, we work backward, from right to

left, to determine the expected value (EV) .

EV is a weighted average of the chance events, where each chance event is given a probability

of occurrence.

We start with the profitability of each alternative, working backward and selecting the

most profitable alternative.


For example, at node 2 we should decide to expand further, because the profits from that

decision are higher ($200,000 versus $150,000).

EV of profits at that point is written below node 2.

This is the expected value if we decide on a small expansion and high demand occurs.

1

High Demand (0.7)

High Demand (0.7)

Low Demand (0.3)

Low Demand (0.3)

Expand

Dont Expand

$300,000

$50,000

$80,000

$200,000

$150,000

2

$200,000


To compute the expected value ( EV) of the small expansion, we evaluate it as a weighted

average of estimated profits given the

probability of occurrence of each chance event:

EVsmall expansion = 0.30($80,000) + 0.70($200,000)

= $164,000


Similarly for large expansion:

EVlarge expansion = 0.30($50,000) + 0.70($300,000)

= $225,000

The large expansion gives the higher expected value.

This means that Mr ABC should pursue a large expansion now.

Decision Trees Q 1

The owner of Hackers Computer Store is considering what to do with his business over

the next five years. Sales growth over the past

couple of years has been good, but sales could

grow substantially if a major electronics firm is

built in his area as proposed. Hackers owner sees three options. The first is to enlarge his

current store, the second is to locate at a new

site, and the third is to simply wait and do

nothing.

Decision Trees Q 1

The decision to expand or move would take little time, and, therefore, the store would not

lose revenue. If nothing were done the first year

and strong growth occurred, then the decision

to expand would be reconsidered. Waiting

longer than one year would allow competition

to move in and would make expansion no

longer feasible.

Decision Trees Q 1

The assumptions and conditions are as follows: a) Strong growth as a result of the increased population

of computer fanatics from the new electronics firm has a 55 percent probability.

b) Strong growth with a new site would give annual returns of $195,000 per year. Weak growth with a new site would mean annual returns of $115,000.

c) Strong growth with an expansion would give annual returns of $190,000 per year. Weak growth with an expansion would mean annual returns of $100,000.

d) At the existing store with no changes, there would be returns of $170,000 per year if there is strong growth and $105,000 per year if growth is weak.

Decision Trees Q 1

e) Expansion at the current site would cost $87,000.

f) The move to the new site would cost $210,000.

g) If growth is strong and the existing site is enlarged

during the second year, the cost would still be

$87,000.

h) Operating costs for all options are equal

Develop a decision tree to solve this problem.

1

2

Move

Expand

Do Nothing

Strong Growth (0.55)



Weak Growth (0.45)

Weak Growth (0.45)

Weak Growth (0.45)

Expand

Do Nothing

R - MC

R - MC

R - EC

R - EC

R - EC

R

R

R (Revenue)

MC (Move Cost)

EC (Expand Cost)

Decision Trees Q 1

ALTERNATIVE REVENUE $ COST $ VALUE $

Move to new location, strong growth 195,000 5 = 975000 210,000 765,000

Move to new location, weak growth

Expand store, strong growth

Expand store, weak growth

Do nothing now, strong growth, expand next year

Do nothing now, strong growth, do not expand next year

Do nothing now, weak growth

Decision Trees Q 1

ALTERNATIVE REVENUE $ COST $ VALUE $

Move to new location, strong growth 195,000 5 = 975000 210,000 765,000

Move to new location, weak growth 115,000 5 = 575000 210,000 365,000

Expand store, strong growth 190,000 5 = 950000 87,000 863,000

Expand store, weak growth 100,000 5 = 500000 87,000 413,000

Do nothing now, strong growth, expand next year

170,000 1 + 190,000 4

87,000 843,000

Do nothing now, strong growth, do not expand next year

170,000 5 = 850000 0 850,000

Do nothing now, weak growth 105,000 5 = 525000 0 525,000

= 930000

1

2

Move

Expand

Do Nothing




Weak Growth (0.45)

Weak Growth (0.45)

Weak Growth (0.45)

Expand

Do Nothing

765,000

365,000

863,000

413,000

843,000

850,000

525,000

R (Revenue)

MC (Move Cost)

EC (Expand Cost)

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3 Capacity Planning