Chapter 14
Sales and Capacity Planning
Lecture Outline
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•
•
•
•
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The Sales and Operations Planning Process
Strategies for Adjusting Capacity
Strategies for Managing Demand
Quantitative Techniques for Aggregate Planning
Hierarchical Nature of Planning
Aggregate Planning for Services
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Sales and Operations Planning
• Determines resource capacity to meet demand over
an intermediate time horizon
• Aggregate refers to sales and operations planning for
product lines or families
• Sales and Operations planning (S&OP) matches supply
and demand
• Objectives
• Establish a company wide plan for allocating resources
• Develop an economic strategy for meeting demand
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Sales and Operations Planning Process
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Monthly S&OP Planning Process
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Meeting Demand Strategies
• Adjusting capacity
• Resources 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
• Level production
• Producing at a constant rate and using inventory to
absorb fluctuations in demand
• Chase demand
• Hiring and firing workers to match demand
• Peak demand
• Maintaining resources for high-demand levels
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Strategies for Adjusting Capacity
• Overtime and under-time
• Increase or decrease working hours
• Subcontracting
• Let outside companies complete the work
• Part-time workers
• Hire part-time workers to complete the work
• Backordering
• Provide the service or product at a later time period
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Level Production
Units
Demand
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 counter-cyclical
demand patterns
• Partnering with suppliers to reduce information
distortion along the supply chain
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Quantitative Techniques For AP
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Pure Strategies
Mixed Strategies
Linear Programming
Transportation Method
Other Quantitative Techniques
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Pure Strategies
QUARTER
SALES FORECAST (LB)
Spring
Summer
Fall
Winter
Hiring cost
Firing cost
Inventory carrying cost
Regular production cost per pound
Production per employee
Beginning work force
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80,000
50,000
120,000
150,000
= $100 per worker
= $500 per worker
= $0.50 pound per quarter
= $2.00
= 1,000 pounds per quarter
= 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
20,000
70,000
50,000
0
140,000
Cost of Level Production Strategy
(400,000 X $2.00) + (140,00 X $.50) = $870,000
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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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Level Production with Excel
Cost of level production
= inventory costs +
production costs
Input by user
=400,000/4
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Inventory at
end of summer
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Chase Demand with Excel
No. of workers
hired in fall
Workforce requirements
calculated by system
Production input by user;
production =demand
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Cost of chase
demand = hiring +
firing + production
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Mixed Strategy
• Combination of Level Production and Chase
Demand strategies
• Example policies
• no more than x% of workforce can be laid off in one
quarter
• inventory levels cannot exceed x dollars
• Some industries may shut down manufacturing
during the low demand season and schedule
employee vacations during that time
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General Linear Programming
(LP) Model
• LP gives an optimal solution, but demand and
costs must be linear
• Let
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•
•
•
•
Wt = workforce size for period t
Pt =units produced in period t
It =units in inventory at the end of period t
Ft =number of workers fired for period t
Ht = number of workers hired for period t
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LP MODEL
Minimize Z = $100 (H1 + H2 + H3 + H4)
+ $500 (F1 + F2 + F3 + F4)
+ $0.50 (I1 + I2 + I3 + I4)
+ $2 (P1 + P2 + P3 + P4)
Subject to
Demand
constraints
Production
constraints
Work force
constraints
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P1 - I1
I1 + P2 - I2
I2 + P3 - I3
I3 + P4 - I4
1000 W1
1000 W2
1000 W3
1000 W4
100 + H1 - F1
W1 + H2 - F2
W2 + H3 - F3
W3 + H4 - F4
= 80,000
= 50,000
= 120,000
= 150,000
= P1
= P2
= P3
= P4
= W1
= W2
= W3
= W4
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
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Setting up the Spreadsheet
Target cell;
cost of solution
goes here
Solver will put the
solution here
When model is complete, Solve
Cells where solution appears
Click here next
Demand Constraint
Production Constraint
Workforce Constraint
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Setting up the Spreadsheet
Click these boxes
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The LP Solution
Cost of optimal solution
Solution is a mix
of inventory, hiring
and firing
Optimal production plan
Extra report
options
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Level Production for Quantum
Cost of level production
Excel
calculates
these
Input by user
Level = 12,000/12 = 1,000
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Chase Demand for Quantum
No. workers
hired in Feb.
Cost of chase demand
Excel
calculates
these
Input by user
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LP Solution for Quantum
Optimal solution
Constraint
equations
in these
cells
Solver found
this solution
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Transportation Method
QUARTER
EXPECTED
DEMAND
REGULAR
CAPACITY
OVERTIME
CAPACITY
SUBCONTRACT
CAPACITY
1
2
3
4
900
1500
1600
3000
1000
1200
1300
1300
100
150
200
200
500
500
500
500
Regular production cost
Overtime production cost
Subcontracting cost
Inventory holding cost
Beginning inventory
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$20/unit
$25/unit
$28/unit
$3/unit-period
300 units
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Transportation Tableau
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Transportation Tableau
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Burruss’ Production Plan
REGULAR
SUBENDING
PERIOD DEMAND PRODUCTION OVERTIME CONTRACT INVENTORY
1
2
3
4
Total
900
1500
1600
3000
7000
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1000
1200
1300
1300
4800
100
150
200
200
650
0
250
500
500
1250
500
600
1000
0
2100
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Excel and Transportation Method
Period 2’s
ending
inventory
Regular production
for period 1
Cost of
solution
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Other Quantitative Techniques
• Linear decision rule (LDR)
• Search decision rule (SDR)
• Management coefficients model
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Hierarchical Nature of Planning
Production
Planning
Capacity
Planning
Resource
Level
Product lines or
families
Sales and
Operations
Plan
Resource
requirements
plan
Plants
Individual
products
Master
production
schedule
Rough-cut
capacity
plan
Critical
work
centers
Components
Material
requirements
plan
Capacity
requirements
plan
All work
centers
Manufacturing
operations
Shop
floor
schedule
Input/
output
control
Items
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Individual
machines
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Disaggregation
• Breaking an aggregate plan into more detailed
plans
• Create Master Production Schedule for Material
Requirements Planning
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Collaborative Planning
• Sharing information and synchronizing
production across supply chain
• Part of CPFR (collaborative planning,
forecasting, and replenishment)
• involves selecting products to be jointly managed,
creating a single forecast of customer demand, and
synchronizing production across supply chain
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Available-to-Promise (ATP)
• Quantity of items that can be promised to customer
• Difference between planned production and customer
orders already received
AT in period 1 = (On-hand quantity + MPS in period 1) –
(CO until the next period of planned production)
ATP in period n = (MPS in period n) –
(CO until the next period of planned production)
• Capable-to-promise
• quantity of items that can be produced and mad available at a
later date
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ATP
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ATP
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ATP
Take excess units from April
ATP in April = (10+100) – 70 = 40
ATP in May = 100 – 110 = -10
ATP in June = 100 – 50 = 50
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= 30
=0
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Rule Based ATP
Product
Request
Yes
Is the product
available at
this location?
No
Available-topromise
Yes
Is an alternative
product available
at this location?
No
Allocate
inventory
Yes
Is this product
available at a
different
location?
No
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Is an alternative
product available
at an alternate
location?
Yes
No
Allocate
inventory
Capable-topromise date
Is the customer
willing to wait for the
product?
No
Available-topromise
Yes
Revise master
schedule
Trigger production
Lose sale
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Aggregate Planning for Services
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Most services cannot 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
• Labor is usually the most constraining resource
for services
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Yield Management
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Yield Management
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Yield Management
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 + C o
75 + 70
Hotel should be overbooked by two rooms
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Copyright 2011 John Wiley & Sons, Inc.
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