Aggregate Planning
OPIM 3104
Instructor: Jose Cruz
OPIM 204 – Aggregate Planning
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Lecture Outline
•
•
•
•
Aggregate Planning Process
Strategies for Adjusting Capacity
Strategies for Managing Demand
Quantitative Techniques for Aggregate
Production Planning
• Aggregate Planning for Services
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Aggregate Planning
• Determine the resource capacity needed to
meet demand over an intermediate time
horizon
– Aggregate refers to product lines or families
– Aggregate planning matches supply and demand
• Objectives
– Establish a company wide game plan for allocating
resources
– Develop an economic strategy for meeting demand
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Aggregate Planning Process
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Meeting Demand Strategies
• Adjusting capacity
– Resources necessary to meet demand
are acquired and maintained over the
time horizon of the plan
– Minor variations in demand are handled
with overtime or under-time
• Managing demand
– Proactive demand management
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Strategies for Adjusting Capacity
• Overtime and under-time
• Level production
– Increasing or decreasing
working hours
– Producing at a constant rate• Subcontracting
and using inventory to
– Let outside companies
absorb fluctuations in
complete the work
demand
• Chase demand
– Hiring and firing workers to
match demand
• Peak demand
– Maintaining resources for
high-demand levels
• Part-time workers
– Hiring part time workers to
complete the work
• Backordering
– Providing the service or
product at a later time period
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Level Production
Demand
Units
Production
Time
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Chase Demand
Demand
Units
Production
Time
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Strategies for Managing Demand
• Shifting demand into
other time periods
– Incentives
– Sales promotions
– Advertising campaigns
• Offering products or
services with countercyclical demand patterns
• Partnering with suppliers
to reduce information
distortion along the
supply chain
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Quantitative Techniques For APP
•
•
•
•
•
Pure Strategies
Mixed Strategies
Linear Programming
Transportation Method
Other Quantitative
Techniques
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Pure Strategies
Example:
QUARTER
Spring
Summer
Fall
Winter
SALES FORECAST (LB)
80,000
50,000
120,000
150,000
Hiring cost = $100 per worker
Firing cost = $500 per worker
Regular production cost per pound = $2.00
Inventory carrying cost = $0.50 pound per quarter
Production per employee = 1,000 pounds per quarter
Beginning work force = 100 workers
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Level Production Strategy
Level production
(50,000 + 120,000 + 150,000 + 80,000)
= 100,000 pounds
4
QUARTER
Spring
Summer
Fall
Winter
SALES
FORECAST
80,000
50,000
120,000
150,000
PRODUCTION
PLAN
INVENTORY
100,000
100,000
100,000
100,000
400,000
Cost of Level Production Strategy
(400,000 X $2.00) + (140,00 X $.50) = $870,000
20,000
70,000
50,000
0
140,000
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Chase Demand Strategy
QUARTER
SALES PRODUCTION
FORECAST
PLAN
Spring
Summer
Fall
Winter
80,000
50,000
120,000
150,000
80,000
50,000
120,000
150,000
WORKERS
NEEDED
80
50
120
150
WORKERS WORKERS
HIRED
FIRED
0
0
70
30
20
30
0
0
100
50
Cost of Chase Demand Strategy
(400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000
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Mixed Strategy
• Combination of Level Production and
Chase Demand strategies
• Examples of management policies
– no more than x% of the workforce can be
laid off in one quarter
– inventory levels cannot exceed x dollars
• Many industries may simply shut down
manufacturing during the low demand
season and schedule employee
vacations during that time
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Aggregate Planning for
Services
Most services can’t be inventoried
Demand for services is difficult to predict
Capacity is also difficult to predict
Service capacity must be provided at the
appropriate place and time
5. Labor is usually the most constraining
resource for services
1.
2.
3.
4.
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Yield Management
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Yield Management
Cu
P(n < x) 
Cu + Co
where
n = number of no-shows
x = number of rooms or seats overbooked
Cu = cost of underbooking; i.e., lost sale
Co = cost of overbooking; i.e., replacement cost
P = probability
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Yield Management
(cont.)
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Yield Management: Example
NO-SHOWS
PROBABILITY
P(N < X)
0
1
2
3
.15
.25
.30
.30
.00
.15
.40
.70
.517
Optimal probability of no-shows
Cu
75
P(n < x) 
=
= .517
Cu + Co
75 + 70
Hotel should be overbooked by two rooms
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