Production Flexibility
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This shows how flexibility in the allocation
of production capacity can increase value
• Value comes from “over design” of capacity
• It is due to uncertainty in both
– Overall level of demand
– Relative demand of different products
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Example inspired by Jan van Mieghem,
development help from João Claro
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
©
Slide 1 of 17
The Example
Two – Stage Manufacturing Process
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The question: how do we allocate
capacity to the facilities?
SUVs
SUV Assembly
Product Finishing
Sedan Assembly
Sedans
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Page 1
©
Slide 2 of 17
Basic Data
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$40 million fixed cost
Variable cost for each facility
– $300 / unit for SUV
– $200 / unit for sedans
– $800 / unit for shared finishing
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Gross Margins for each product
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– $ 4000 / SUV
– $ 3000 / Sedan
For simplicity, all in present dollars
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
©
Slide 3 of 17
1. Design based on best forecast
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Assume forecast is 30,000 of each vehicles
Design is then 30 / 30 /60
– 30,000 for SUVs
– 30,000 for Sedans
– 60,000 for Finishing
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System value = Revenues – costs
= [30(4) + 30 (30)] – 40 –[30(.3) + 30(.2)]
=107 Million
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Page 2
©
Slide 4 of 17
2. Best forecast +/- 15%
Calculations based on deterministic forecast
of course unrealistic
We need to recognize uncertainty
For example +/- 15% overall
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SUV Demand Sedans Total Probability Demand Scenarios: Balanced Variation Pessimistic Expected Optimistic 25000 30000 35000 25000 30000 35000 50000 60000 70000 0.25 0.50 0.25 Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Mean 30000 30000 60000 ©
Slide 5 of 17
2. Results for +/- 15% Uncertainty
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Value calculated is less than with unrealistic
certainty. Why?
No gains for high scenario because of
production constraints
For low scenario:
– Revenue loss = 5(4 +3) = 35 Million
– This occurs 25% of time
– Net loss in expected value 8.75
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Overall Expected Value = 98.75 Million
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Page 3
©
Slide 6 of 17
3. Asymmetric Variation in Products
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Suppose, as often happens, that demand for
products is negatively correlated (if demand
for 1 goes up, demand for other goes down)
Why would this happen?
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In bad times consumers buy less and cheaper
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– Overall number of units down
– Proportion skewed toward cheaper vehicles
Conversely, in expansive times
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Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
©
Slide 7 of 17
3. Assumed Asymmetry
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Total demand up or down by 15% as before
But demand for SUV’s very sensitive
SUV shift partially counter-balanced by demand for
sedans
SUVs Demand Sedans Total Probability Pessimistic 15000 35000 50000 0.25 Scenarios Expected 30000 30000 60000 0.50 Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Optimistic 45000 25000 70000 0.25 Richard de Neufville
Production Flexibility
Page 4
Average 30000 30000 60000 ©
Slide 8 of 17
3. Effect on Production
• Counter intuitively, units sold drops during
expansion period!
– Sales of SUVs limited by capacity constraint
– Demand for sedans drops!
Facility Capacity SUV 30000 Sedan 30000 Joint 60000 Pessimistic 15000 30000 45000 Production Expected Optimistic 30000 30000 30000 25000 60000 55000 Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Average 26250 28750 55000 ©
Slide 9 of 17
3. Effect on Profits
• Negative correlation in demand increases
losses compared to situation without this
effect
z Expected value now 88.25
Investment Gross Margin Gross Profit Pessimistic 103 150 Expected 103 210 Optimistic 103 195 Average 103 191.25 47 107 92 88.25 Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Page 5
©
Slide 10 of 17
4. Cutting Capacity
• An intuitive reflex might be to cut size
since expected sales less than capacity
• What does this do?
• Not much good! Gap persists
Facility Capacity SUV 27000 Sedan 27000 Joint 54000 Pessimistic 15000 27000 42000 Production Expected Optimistic 27000 27000 27000 25000 54000 52000 Average 24000 26500 50500 Richard de Neufville
Production Flexibility
©
Slide 11 of 17
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
4. Effect of Cutting Capacity
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Net effect of cutting size of a profitable
business is to cut profits
Expected Profits drop to 78.8
Not a good plan
Investment Gross Margin Gross Profit Pessimistic
96.7 141 Expected 96.7 189 Optimistic 96.7 183 Average 96.7 175.50 44.3 92.3 86.3 78.8 Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Page 6
©
Slide 12 of 17
5. Flexibility to Allocate Capacity
Idea: expand capacity of SUV and Sedan
facilities without expanding finishing plant
This is an unbalanced design:
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– SUV and Sedan together will never operate at
capacity (in this case, less than 60/70 ~ 86%)
Why is this good?
Allows tracking demand
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Facility Capacity SUV 35000 Sedan 35000 Joint 60000 Pessimistic 15000 35000 50000 Production Expected Optimistic 30000 35000 30000 25000 60000 60000 Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Average 27500 30000 57500 ©
Slide 13 of 17
5. Value of Flexibility
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Increases profits
Expected Value = 94.5 > 88.25
Net Value of flexibility = 6.25 Million
Investment Gross Margin Gross Profit Pessimistic
105.5 165 Expected 105.5 210 Optimistic 105.50 215 Average 105.5 200 59.5 104.5 109.5 94.5 Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Page 7
©
Slide 14 of 17
5. VARG Comparisons
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Asymmetric demand, with and w/o flexibility
Policy “reduces downside, increases upside”
VARG for Capacity Allocation Plans
1.2
Cumulative Probability
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1
0.8
Flexible
Design
0.6
0.4
0.2
0
0.00
Base
Case
20.00
40.00
60.00
80.00
100.00
120.00
Outcomes, Millions
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
©
Slide 15 of 17
5. Benefit-Cost of Flexibility
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Cost of Flexibility
= Cost of Extra Capacity
= 5(0.3) + 5(0.2) = 2.5 million
Benefit – Cost of Flexibility
(remember, total value = net + cost)
= [6.25 + 2.5] / 2.5 = 3.5
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Page 8
©
Slide 16 of 17
Take-aways from presentation
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Flexible Capacity Allocation can be valuable
-- when demand for products (services) is
negatively correlated
Solution is counter-intuitive
Not a “balanced” design
Flexibility consists of having extra capacity
to absorb changes
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
Page 9
©
Slide 17 of 17