DYNAMIC STRATEGIC PLANNING - Massachusetts Institute of

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Transcript DYNAMIC STRATEGIC PLANNING - Massachusetts Institute of

Production Flexibility

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

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

The question: how do we allocate
capacity to the facilities?
SUVs
SUV Assembly
Product Finishing
Sedan Assembly
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Sedans
Richard de Neufville
Production Flexibility
©
Slide 2 of 17
Basic Data


$40 million fixed cost
Variable cost for each facility
– $300 / unit for SUV
– $200 / unit for sedans
– $800 / unit for shared finishing

Gross Margins for each product

– $ 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

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
©
Slide 4 of 17
2. Best forecast +/- 15%

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Calculations based on deterministic forecast
of course unrealistic
We need to recognize uncertainty
For example +/- 15% overall
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

Overall Expected Value = 98.75 Million
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Richard de Neufville
Production Flexibility
©
Slide 6 of 17
3. Asymmetric Variation in Products

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

– Overall number of units down
– Proportion skewed toward cheaper vehicles

Conversely, in expansive times
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
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Scenarios
Expected
30000
30000
60000
0.50
Optimistic
45000
25000
70000
0.25
Richard de Neufville
Production Flexibility
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
SUV
Sedan
Joint
Capacity
30000
30000
60000
Pessimistic
15000
30000
45000
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Production
Expected
Optimistic
30000
30000
30000
25000
60000
55000
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
 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
©
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
SUV
Sedan
Joint
Capacity
27000
27000
54000
Pessimistic
15000
27000
42000
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Production
Expected
Optimistic
27000
27000
27000
25000
54000
52000
Average
24000
26500
50500
Richard de Neufville
Production Flexibility
©
Slide 11 of 17
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
©
Slide 12 of 17
5. Flexibility to Allocate Capacity

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Idea: expand capacity of SUV and Sedan
facilities without expanding finishing plant
This is an unbalanced design:
– SUV and Sedan together will never operate at
capacity (in this case, less than 60/70 ~ 86%)

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Why is this good?
Allows tracking demand
Facility
SUV
Sedan
Joint
Capacity
35000
35000
60000
Pessimistic
15000
35000
50000
Engineering Systems Analysis for Design
Massachusetts Institute of Technology
Production
Expected
Optimistic
30000
35000
30000
25000
60000
60000
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
©
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
©
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
©
Slide 17 of 17