1. Hybrid Approach to Option Valuation
Richard de Neufville
Professor of Systems Engineering and of
Civil and Environmental Engineering
MIT

2. Outline R & D creates options R & D Evaluation in Auto Industry
Parts of R & D Process
Details of Ford Case
Hybrid Evaluation Strategy and Results
Summary

3. Linear Systems are Common
Many Systems feature “linear” development
They proceed naturally through phases
Example: Oil Development
Acquire Lease
Explore
Test wells
Exploitation
Example: New Products
Basic Research
Applied Research
Development
Production

4. Linear Systems Create Options
Completing 1st step gives “right, but not obligation” to do 2nd; and so on down line
R & D in particular creates options
HOWEVER, optionality of R & D has usually been ignored – projects evaluated by NPV
This means: value of being able to cancel project if appropriate has been ignored
In short that
R & D HAS BEEN UNDERVALUED

5. Types of R & D
Traditionally, R & D organizations divide their portfolio of into categories
In Auto Industry
Tier 1: General Research
Tier 2: Future Vehicle Work
Tier 3: Current Vehicle Work
Major Development Effort
In US Department of Defense
Categories: 6.1, 6.2, etc…
Evaluation Criteria for parts may differ…

6. R & D Evaluation in US Auto Industry
Traditional Process
Net Present Value Process
Assumes Development Process carried on through production
possibility of stopping project not in analysis
However, successful prototype production is option for full scale
Is this right? How should Ford evaluate elements of its research portfolio?
This was object of Neely’s research

7. Neely’s Hybrid Approach
Basic idea: Divide the valuation into 2 parts
Use different approach for distinct needs
Financial “options analysis” for market element
uses volatility of stock price to reflection of uncertainty in sales and thus value of product
Decision analysis for technical risks,
Judgment is appropriate -- not volatility
“Render onto Caesar what is Caesar’s… unto God what is God’s”

8. Structure of Investment Choices
Decision 1
Uncertainty
Decision 2
Contingent
Invest?
Resolution
Implement?
Results
Results
Promise
High Benefits
-Cost(1) -Cost(2)
Implement
Stop Project
0.5
-Cost(1)
Invest
Implement
Results
Poor
Low Benefits
-Cost(1)-Cost(2)
Stop Project
0.5
-Cost(1)
Do Not Invest

9. Detailed view of Probabilities, Decisions
Initial
Technical
Benefit
Market
Implementation
Time
Investment
Uncertainty
Uncertainty
Uncertainty
Decision
Choice
(Endogenous)
(Endogenous)
(Exogenous)
-R&D Costs - Implement Cost
+ Revenues
Implement
High Demand
Stop
Phd
-R&D Costs
Implement
-R&D Costs - Implement Cost
+ Revenues
High Benefits
Medium Demand
Stop
Pmd
-R&D Costs
Phb
Implement
-R&D Costs - Implement Cost
+ Revenues
Low Demand
R&D Success
Stop
Pld
-R&D Costs Ps
Medium Benefits
Yes
Similar to High Value Branch
Pmb
Low Benefits
Invest?
Similar to High Value Branch
R&D Fails
Plb
-R&D Costs No
1-Ps

10. Structure of Hybrid Analysis
Risk-neutral treatment of exogenous uncertainties, that is, those due to market
Discount at risk-free rate
Some market-priced asset needed to represent value of project – Neely took the stock price for Ford, assuming it correlated with sales of cars
Direct treatment of endogenous uncertainties, that is, those due to project
Discount at risk-appropriate rate, for example at CAPM

11. Details of Ford Case
Neely collaborated with Materials section of Ford R & D
First table illustrates description of projects
Second table, the data for the projects
Note estimates of probabilities of success
~ 0.8 for Tier 3, Current Vehicle Focus
~ 0.5 for Tier 2, Future Vehicles
~ 0.3 for Tier 1, General Research
Full data sets appended to presentation

12. R & D Project Descriptions
Sample R & D Project Descriptions:
Code
Project
Area
Class
Money Benefits
Other Benefits A
Vehicle Systems
Design
Warranty & Testing
Model B
Engine
Prototype Elimination
Weight Savings C
Power- train
Component Reduction H
Manufac- turing
Process
Productivity Increase NA J
Product

13. R & D Project Data Sample R & D Project Data: Code Costs $, millions
Benefits
$, millions
P (Success)
Annual R&D
Implement A
1.0
0.25 40
0.8 B 42 H
0.4
1.00 12 J 1
0.9

14. Results of Hybrid Analysis
Next slide gives:
Value of Each Project, by NPV and Hybrid Analysis
Also ranking of projects by each method
Note that:
When valued as options, the R & D projects always had higher value. This is because, once one recognizes the possibility of canceling projects, one discards negatives that lower value
The rank order is not the same for both methods.
Thus the use of NPV not only gives wrong values systematically biased downward, but recommends some projects in wrong order!

15. Valuation of Projects by NPV and Hybrid

16. Higher Uncertainty  Higher Value
Graph clearly illustrates this basic principle

17. Neely’s Guide for Use of Hybrid Method
High
Decision
Analysis +
Financial
Options
Financial Options
Exogenous
Market Related
Uncertainties
Decision Analysis
NPV
Low
Endogenous
Project Specific
Uncertainties
Low
High

18. Summary
The Hybrid Method is a Feasible way of Valuing Real Options in Systems
It has the great advantage of combining
Market effects on project (provided a good proxy variable can be found)
Technical uncertainties
It is far from theoretically pure – a “rough and ready” valuation that has the merit of being plausibly better than feasible alternatives
More research needed!

19. References
de Neufville, R. and Neely, J. (2001) “Hybrid Real Options Valuation of Risky Project Development Projects,” International Journal of Technology, Policy and Management, Vol. 1, No. 1, pp 29 – 46.
Neely, J. (1998) “Improving the Valuation of Research and Development: A Composite of Real Options, Decision Analysis and Benefit Valuation Frameworks,” Ph.D. dissertation, MIT, Cambridge, MA.

20. Some Appendix Tables follow …

21. Complete Description of Projects

22. Complete Data for Projects