1. Midterm Exam - DSC-8240
Murugan Chellasamy

2. Cases
Cold Fusion
Prescribed Fire
GPC
Strenlar

3. Cold Fusion Objective Hierarchies Variables & Measures
Problem Structuring
Consequence Table
Influence Diagram
Decision Tree
Mathematical Model - NA
Solutions & Sensitivity
Cases

4. Cold Fusion - Objective Hierarchies

5. Cold Fusion - Variables & Measures
Decision Variables:
Good for the Society
Bad for the Society
Chance Variables
Bill Passed
Bill Rejected
High Political Value
Low Political Value
Fusion Works
Fusion Fails
Economically Feasible
Economically Infeasible
Consequence
Actually Helps Society
Does not make any difference

6. Cold Fusion - Consequence Table

7. Cold Fusion - Influence Diagram
High Political
Value
High/Low
Fusion
Works/Fails
Bill
Passed/Rejected
Good /Bad
For
Society
High Satisfaction

8. Cold Fusion - Decision Tree

9. Cold Fusion - Solutions & Sensitivity
I believe the fate of this bill will be determined by the relative publicity it can generate to help the politicians and the scientists. It would be very hard to determine the economic and social benefits derived from Cold Fusion. It could be very beneficial to the society but if it meant that we would have to stop using the existing sources of energy, it may cause severe economic strains. On the other hand it may help the economy but may create problems to the society by making destructive technology available at a cheaper cost. Even if the bill gets passed, it may not be feasible to use this technology to reap the desired benefits.

10. Prescribed Fire Objective Hierarchies Variables & Measures
Problem Structuring
Consequence Table
Influence Diagram
Decision Tree
Mathematical Model
Solutions & Sensitivity
Cases

11. Prescribed Fire - Objective Hierarchies

12. Prescribed Fire - Variables & Measures
Decision Variables:
Burn Slash
YUM
Chance Variables
Controlled Fire
Uncontrollable Fire - Escaped Fire
Uncontrollable Fire - Problems
Consequence
Cost Efficient Burn
Escaped Fire
Low Cost Burn
Medium Cost Burn
High Cost Burn

13. Prescribed Fire - Consequence Table

14. Prescribed Fire - Influence Diagram
Uncontrolled
Fire
Controlled
Fire
Low
High
Medium
Costs
Choose
Method
Cost Efficient
Burn

15. Prescribed Fire - Decision Tree

16. Prescribed Fire Solutions & Sensitivity
Given the scenario’s, YUM seems to be the most cost efficient method .

17. GPC Objective Hierarchies Variables & Measures Problem Structuring
Consequence Table
Influence Diagram
Decision Tree- NA
Mathematical Model
Solutions & Sensitivity
Cases

18. GPC - Objective Hierarchies

19. GPC - Variables & Measures
Decision Variables:
Product A
Product B
Product C
Chance Variables
Delay in production
Price
Sales
Market Share
Consequence
Increased Market Share
Lose Market Share
Increased Return
Reduced Margin

20. GPC - Consequence Table

21. GPC - Influence Diagram
Sales
Delay
Product
Maximize
Return
Choose
Product

22. GPC - Mathematical Model
Mathematical Models
EMVA delay = max (((0.3 * 5) + (0.7 * (-0.5))), ((0.5 * 3.5) + (0.5 * 1)))
EMVA no delay = max (((0.4 * 8) + (0.6 * 0)), ((0.5 * 4.5) + (0.5 * 1.5)))
EMVA = max (EMVA delay, EMVA no delay )
EMVB = (0.38 * 8) + (0.12 * 4) + (0.5 * 0)
EMVC = 1.0
EMV Optimal Decision = max( EMVA, EMVB, EMVC )

23. GPC - Solutions & Sensitivity
I was not able to get DPL to draw a decision tree. In any event, if we had more time and information we could have done more analysis. We could have used excel to set up a solver with constraints (upper and lower limits on probability) for products A & B to get a maximized return. We could also have set up a regression model with sales as the dependent variable with delay and price as independent variables to project profits with certain level of confidence. But, given the information we have, I would suggest we go with product B since we are a lot more certain about its out come. The decision will also be impacted by many other factors like the GPC’s financial strength and its position in the market etc.

24. Strenlar Objective Hierarchies Variables & Measures
Problem Structuring
Consequence Table
Influence Diagram
Decision Tree
Mathematical Model
Solutions & Sensitivity
Cases

25. Strenlar - Objective Hierarchies

26. Strenlar - Variables & Measures
Decision Variables:
Accept Offer
Reject Offer
Chance Variables
Financial/ Physical/ Emotional State
Peer & Social Pressure
Future
Consequence
Rich & Happy
Broke & Miserable
Self Esteem??

27. Strenlar - Consequence Table

28. Strenlar - Influence Diagram
Emotional
State
Financial
State
Physical
State
Accept/Reject
Offer
Maximize
Satisfaction

29. Strenlar - Decision Tree

30. Strenlar - Mathematical Model
The following diagram, done in Excel, accompanies the mathematical model used by Fred:
EMV Lawsuit = (0.6 * ((0.8 * 8,000) + (0.2 * (-200)))) + (0.4 * (-220))
EMVPI job = (0.8 * 2,443) + (0.2 * 343)
EMV lump sum = (0.8 * 1,252) + (0.2 * 500)
EMV Optimal decision = max ( EMV Lawsuit, EMVPI job, EMV lump sum )

31. Strenlar Solutions & Sensitivity
Fred’s position is unenviable. His decision will be influenced by how he feels about himself. I don’t think we can help him make a decision based on the financial outcomes. If Fred was a corporation, we could argue that he should reject the offer and take them to court since maximizing the value of the assets would be his only goal.