1. 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

2. The Example Two – Stage Manufacturing Process
The question: how do we allocate capacity to the facilities?
SUV Assembly
Sedan Assembly
Product Finishing
SUVs
Sedans

3. 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

4. 1. Design based on best forecast
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

5. 2. Best forecast +/- 15%
Calculations based on deterministic forecast of course unrealistic
We need to recognize uncertainty
For example +/- 15% overall

6. 2. Results for +/- 15% Uncertainty
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 = Million

7. 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?
In bad times consumers buy less and cheaper
Overall number of units down
Proportion skewed toward cheaper vehicles
Conversely, in expansive times

8. 3. Assumed Asymmetry 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

9. 3. Effect on Production
Counter intuitively, units sold drops during expansion period!
Sales of SUVs limited by capacity constraint
Demand for sedans drops!

10. 3. Effect on Profits
Negative correlation in demand increases losses compared to situation without this effect
Expected value now 88.25

11. 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

12. 4. Effect of Cutting Capacity
Net effect of cutting size of a profitable business is to cut profits
Expected Profits drop to 78.8
Not a good plan

13. 5. Flexibility to Allocate Capacity
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%)
Why is this good?
Allows tracking demand

14. 5. Value of Flexibility Increases profits
Expected Value = >
Net Value of flexibility = 6.25 Million

15. 5. VARG Comparisons Asymmetric demand, with and w/o flexibility
Policy “reduces downside, increases upside”
Flexible Design
Base Case

16. 5. Benefit-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)
= [ ] / 2.5 = 3.5

17. Take-aways from presentation
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