Chapter 9– Capacity Planning
& Facility Location
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Define capacity planning and location analysis
Describe relationship between capacity planning and
location, and their importance
Explain the steps involved in capacity planning and
location analysis
Describe the decision support tools used for capacity
planning
Identify key factors in location analysis
Describe the decision support tools used for location
analysis
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Capacity planning
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Capacity is the maximum output rate of a facility
Capacity planning is the process of establishing the
output rate that can be achieved at a facility:
 Capacity is usually purchased in “chunks”
 Strategic issues: how much and when to spend
capital for additional facility & equipment
 Tactical issues: workforce & inventory levels, &
day-to-day use of equipment
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Measuring Capacity Examples
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There is no one best way to measure capacity
Output measures like kegs per day are easier to understand
With multiple products, inputs measures work better
Type of Business
Input Measures of
Capacity
Output Measures
of Capacity
Car manufacturer
Labor hours
Cars per shift
Hospital
Available beds
Patients per month
Pizza parlor
Labor hours
Pizzas per day
Retail store
Floor space in
square feet
Revenue per foot
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Measuring Available Capacity
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Design capacity:
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Maximum output rate under ideal conditions
A bakery can make 30 custom cakes per day
when pushed at holiday time
Effective capacity:
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Maximum output rate under normal (realistic)
conditions
On the average this bakery can make 20
custom cakes per day
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Measuring Effectiveness of
Capacity Use
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Measures how much of the available
capacity is actually being used:
actual output rate
100%
Utiliz atio
n
capacity
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Measures effectiveness
Use either effective or design capacity in
denominator
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Example of Computing Capacity Utilization: A bakery’s
design capacity and effective capacity are 30 and 20 cakes per day,
respectively. Currently the bakery is producing 28 cakes per day.
What is the bakery’s capacity utilization relative to both design and
effective capacity?
Utiliz atio
n effective 
Utiliz atio
n design
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actual output
28
(100%)  (100%)  140%
e ffe ctivecapacity
20
actual output
28

(100%)  (100%)  93%
de sign capacity
30
The current utilization is only slightly below its design
capacity and considerably above its effective capacity
The bakery can only operate at this level for a short period
of time
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Capacity Considerations
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The Best Operating Level is the output that results in
the lowest average unit cost
Economies of Scale:
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Where the cost per unit of output drops as volume of output
increases
Spread the fixed costs of buildings & equipment over multiple
units, allow bulk purchasing & handling of material
Diseconomies of Scale:
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Where the cost per unit rises as volume increases
Often caused by congestion (overwhelming the process with too
much work-in-process) and scheduling complexity
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Best Operating Level and Size
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Alternative 1: Purchase one large facility, requiring one large
initial investment
Alternative 2: Add capacity incrementally in smaller chunks as
needed
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Other Capacity Considerations
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Focused factories:
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Plant within a plant (PWP):
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Small, specialized facilities with limited
objectives
Segmenting larger operations into smaller
operating units with focused objectives
Subcontractor networks:
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Outsource non-core items to free up
capacity for what you do well
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Making Capacity Planning
Decisions
The three-step procedure for capacity
planning decisions:
1. Identify Capacity Requirements
2. Develop Capacity Alternatives
3. Evaluate Capacity Alternatives
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Identifying capacity
requirements
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Forecasting Capacity:
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Capacity cushions
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Long-term capacity requirements based on future demand
Identifying future demand based on forecasting
Forecasting, at this level, relies on qualitative forecast models
 Executive opinion
 Delphi method
Forecast and capacity decisions must include strategic implications
Plan to underutilize capacity to provide flexibility
Strategic Implications
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How much capacity a competitor might have
Potential for overcapacity in industry is a possible hazard
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Developing & Evaluating Capacity
Alternatives
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Capacity alternatives include
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Could do nothing,
expand large now (may included capacity
cushion), or
expand small now with option to add later
Use decision support aids to evaluate
decisions (decision tree: most popular)
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Decision trees
Diagramming technique which uses
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Decision (square) nodes– points in time when
decisions are made. Decision alternatives
branches of the tree from the decision nodes.
Pruning of the tree (decision has to be made)
here.
Chance (circular) nodes – where different
possible outcomes (with different probabilities)
emanate. No decisions made here.
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Decision tree diagrams
Decision trees developed by
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Drawing from left to right
Use squares to indicate decision points
Use circles to indicate chance events
Write the probability of each chance by the
chance (sum of associated chances = 100%)
Write each alternative outcome in the right
margin
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Example Using Decision Trees: A restaurant owner has
determined that she needs to expand her facility. The alternatives
are to expand large now and risk smaller demand, or expand on a
smaller scale now knowing that she might need to expand again in
three years. Which alternative would be most attractive? (see notes)
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Evaluating the Decision Tree
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Decision tree analysis utilizes expected value
analysis (EVA)
EVA is a weighted average of the chance events
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Sum of (Probability of occurrence * value of the chance
event outcome)
Refer to previous slide
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At decision point 2, choose to expand to maximize
profits ($200,000 > $150,000)
Calculate expected value of small expansion:
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EVsmall = 0.30($80,000) + 0.70($200,000) = $164,000
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Evaluating the Decision
Tree con’t
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Calculate expected value of large expansion:
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EVlarge = 0.30($50,000) + 0.70($300,000) =
$225,000
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At decision point 1, compare alternatives &
choose the large expansion to maximize the
expected profit:
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$225,000 > $164,000
Choose large expansion despite the fact that
there is a 30% chance it’s the worst decision:
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Take the calculated risk!
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Location Analysis
Facility location is the process of identifying
the best geographic location for a service or
production facility.
Factors affecting location Decisions are:
Proximity to source of supply:
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Reduce transportation costs of perishable or bulky raw
materials
Proximity to customers:
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High population areas, close to JIT partners
Proximity to labor:
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Local wage rates, attitude toward unions, availability
of special skills (silicon valley)
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Other Location Factors
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Community considerations:
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Site considerations:
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Local zoning & taxes, access to utilities, etc.
Quality-of-life issues:
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Local community’s attitude toward the facility (prisons,
utility plants, etc.)
Climate, cultural attractions, commuting time, etc.
Other considerations:
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Options for future expansion, local competition, etc.
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Globalization –
Should Firm Go Global?
Globalization is the process of locating facilities
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around the world
Potential advantages:
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Potential disadvantages:
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Inside track to foreign markets, avoid trade barriers, gain access
to cheaper labor
Political risks may increase, loss of control of proprietary
technology, local infrastructure (roads & utilities) may be
inadequate, high inflation
Other issues to consider:
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Language barriers, different laws & regulations, different
business cultures
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Making Location Decisions
Analysis should follow 3 step process:
1.
2.
3.
Identify dominant location factors
Develop location alternatives
Evaluate locations alternatives
Procedures for evaluation location alternatives
include
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Factor rating method
Load-distance model
Center of gravity approach
Break-even analysis
Transportation method
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Factor Rating Example
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A Load-Distance Model Example: Matrix Manufacturing is
considering where to locate its warehouse in order to service its four
Ohio stores located in Cleveland, Cincinnati, Columbus, Dayton. Two
sites are being considered; Mansfield and Springfield, Ohio. Use the
load-distance model to make the decision.
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Calculate the rectilinear distance: dAB  30  10  40  15  45 miles
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Multiply by the number of loads between each site and the four cities
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Calculating the Load-Distance Score
for Springfield vs. Mansfield
Computing the Load-Distance Score for Springfield
 City
Load
Distance
ld
Cleveland
15
20.5
307.5
Columbus
10
4.5
45
Cincinnati
12
7.5
90
Dayton
4
3.5
14
Total
Load-Distance Score(456.5)
Computing the Load-Distance Score for Mansfield
City
Load
Distance
ld
Cleveland
15
8
120
Columbus
10
8
80
Cincinnati
12
20
240
Dayton
4
16
64
Total
Load-Distance Score(504)
The load-distance score for Mansfield is higher than for
Springfield. The warehouse should be located in Springfield.
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The Center of Gravity Approach
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This approach requires that the analyst find the center of
gravity of the geographic area being considered
Computing the Center of Gravity for Matrix Manufacturing
Location
Cleveland
Columbus
Cincinnati
Dayton
Coordinates
Load
(X,Y)
(11,22)
(10,7)
(4,1)
(3,6)
(li)
15
10
12
4
41
Total
lixi
165
165
165
165
325
liyi
330
70
12
24
436
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Computing the Center of Gravity for Matrix Manufacturing
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l X 325
l Y 436
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X 

 7.9 ; Y 

 10.6
l
41
 lto the41C.G. that
Is there another possible 
warehouse location closer
i
i
i
c.g.
i
c.g.
i
i
should be considered?? Why?
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Break-Even Analysis
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Break-even analysis computes the amount of goods required
to be sold to just cover costs
Break-even analysis includes fixed and variable costs
Break-even analysis can be used for location analysis
especially when the costs of each location are known
Step 1: For each location, determine the fixed and
variable costs
Step 2: Plot the total costs for each location on one graph
Step 3: Identify ranges of output for which each location
has the lowest total cost
Step 4: Solve algebraically for the break-even points
over the identified ranges
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Break-Even Analysis
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Remember the break even equations used for calculation total
cost of each location and for calculating the breakeven
quantity Q.
 Total cost = F + cQ
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Total revenue = pQ
Break-even is where Total Revenue = Total Cost
Q = break-even quantity
p = price/unit
c = variable cost/unit
F = fixed cost
Q = F/(p-c)
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Example using Break-even Analysis: Clean-Clothes
Cleaners is considering four possible sites for its new
operation. They expect to clean 10,000 garments. The
table and graph below are used for the analysis.
Example 9.6 Using Break-Even Analysis
Location Fixed Cost Variable Cost Total Cost
A $350,000 $ 5(10,000) $400,000
B $170,000 $25(10,000) $420,000
C $100,000 $40(10,000) $500,000
D $250,000 $20(10,000) $450,000
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The Transportation Method
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Can be used to solve specific location problems
Is discussed in detail in the supplement to this text
Could be used to evaluate the cost impact of
adding potential location sites to the network of
existing facilities
Could also be used to evaluate adding multiple
new sites or completely redesigning the network
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Chapter 9 Highlights
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Capacity planning is deciding on the maximum output rate of a facility
Location analysis is deciding on the best location for a facility
Capacity planning and location analysis decision are often made
simultaneously because the location of the facility is usually related to its
capacity.
In capacity planning and location analyses, managers must follow three-step
process. The steps are assessing needs, developing alternatives, and
evaluating alternatives.
To choose between capacity planning alternatives managers may use decision
trees.
Key factors in location analysis included proximity to customers, suppliers,
source of labor, community attitude, and quality of life issues .
Factor rating is a tool that helps managers evaluate qualitative factors. The
load-distance model and center of gravity approach evaluate the location
decision based on distance. Break-even analysis is used to evaluate location
decisions based on cost values. The transportation method is an excellent
tool for evaluating the cost impact of adding sites to the network of current
facilities.
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