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Decision Analysis 
5th Apr 2014
Agenda 
1. Objective 
2. Literature Review 
3. Decision making 
 Overview 
 Decision making Environment 
 Decision Making Criteria 
4. Models 
5. Case 
6. References 
2
Objective 
How the Decision Analysis can help in 
decision making in the face of uncertainty 
3
Literature Review 
Decision analysis provides a framework and 
methodology for rational decision making 
when the outcomes are uncertain. 
4
WCB 
Worker’s Compensation Board of British 
Columbia, Canada 
Over 1,65,000 employers 
1.8 million workers 
Spends US$1 billion p.a. 
Objective – Improve service & Reduce cost 
5
WCB 
Applying Decision Analysis with decision trees WCB is now saving approximately US $4 
million per year while also enabling some injured workers return to work sooner 
Source: Ernest Urbanovich, Ella E. Young, Martin L. Puterman, Sidney O. Fattedad, (2003) Early Detection of High-Risk Claims at the 
Workers' Compensation Board of British Columbia. Interfaces 33(4):15-26. 
http://dx.doi.org/10.1287/inte.33.4.15.16372 6
Westinghouse 
Westinghouse Science and Technology 
Center 
R&D Arm to develop new technology 
Objective – Deliver high impact technology 
quickly & Reduce cost 
7
Westinghouse 
OR team developed a decision tree approach to analyzing any R&D proposal while 
considering its complete sequence of key decision points. 
A decision tree with a progression of decision nodes and intervening event nodes 
provided a natural way of depicting and analyzing such an R&D project. 
Source: Robert K. Perdue, William J. McAllister, Peter V. King, Bruce G. Berkey, (1999) Valuation of R and D Projects Using Options 
Pricing and Decision Analysis Models. Interfaces 29(6):57-74. 
http://dx.doi.org/10.1287/inte.29.6.57 
8
ConocoPhillips 
Conoco Inc. and Phillips Petroleum 
company 
3rd largest integrated energy co. in US 
Objective – Judicious Allocation of 
investment capital across a set of 
exploration projects 
9
Westinghouse 
In early 1990’s – Industry leader 
Source: Michael R. Walls, G. Thomas Morahan, James S. Dyer, (1995) Decision Analysis of Exploration Opportunities in the 
Onshore US at Phillips Petroleum Company. Interfaces 25(6):39-56. 
http://dx.doi.org/10.1287/inte.25.6.39 
10 
in application of OR 
methodology 
DISCOVERY – decision 
analysis s/w package 
• Evaluate exploration projects 
• Rank Projects 
• Budget Consideration
Should You Ask? 
Sir, why is my coursework 
marks so low? I deserve 
higher marks. Hehehe!
Which Mobile Phone should I buy? 
What are the things 
you consider before 
making a decision?
Whom should I marry? 
What are the things 
you consider before 
making a decision?
Decision 
A general approach to decision 
making that is suitable to a wide 
range of operations management 
decisions: 
14 
Capacity 
planning 
Product 
and service 
design 
Equipment 
selection 
Location 
planning
Decision Making Overview 
Decision Making 
Decision Environment Decision Criteria 
Certainty Nonprobabilistic 
Uncertainty Probabilistic 
15
The Decision Environment 
Decision Environment Certainty: The results of decision 
16 
Certainty 
Uncertainty 
alternatives are known 
Example: 
Must print 10,000 color brochures 
Offset press A: $2,000 fixed cost 
+ $.24 per page 
Offset press B: $3,000 fixed cost 
+ $.12 per page 
*
The Decision Environment 
17 
Decision Environment 
Certainty 
Uncertainty 
Uncertainty: The outcome that will occur 
after a choice is unknown 
Example: 
You must decide to buy an item now or wait. 
If you buy now the price is $2,000. If you 
wait the price may drop to $1,500 or rise to 
$2,200. There also may be a new model 
available later with better features. 
* 
(continued)
Decision Criteria 
Nonprobabilistic Decision Criteria: Decision Decision Criteria 
rules that can be applied if the probabilities of 
uncertain events are not known. 
18 
Nonprobabilistic 
Probabilistic 
* 
 maximax criterion 
 maximin criterion 
 minimax regret criterion
Decision Criteria 
19 
Decision Criteria 
Nonprobabilistic 
Probabilistic 
* 
Probabilistic Decision Criteria: Consider the 
probabilities of uncertain events and select 
an alternative to maximize the expected 
payoff of minimize the expected loss 
 maximize expected value 
 minimize expected opportunity loss 
(continued)
Step 1 
Identify 
possible 
future 
conditions 
or state of 
nature 
Develop a 
list of 
possible 
alternatives 
Determine 
the payoff 
associated 
with each 
alternative 
for every 
possible 
future 
condition 
Estimate 
the 
likelihood of 
each 
possible 
future 
conditions 
Evaluate 
alternatives 
based to 
some 
decision 
criterion, 
and select 
the best 
alternative 
Decision Making Process: 
Step 2 Step 3 Step 4 Step 5
21 
Decision Models 
Decision 
Models 
Payoff 
Matrix 
Decision 
Tree
Decision Illustration 
22 
Sunny wants to join WMP from IIM Lucknow, Noida Campus. 
She is hopeful that if after completion of course she will get better opportunity and 
her salary will be INR 50,00,000, if the economy is good. If the economy is average, 
she will get a salary of Rs. 40,00,000. If economy is bad she will get Rs. 30,00,000. The 
fee for course is approx. Rs. 8,10,000. Also she estimates that there would be some 
incidental expenses of Rs. 2,90,000 on commuting etc. 
In case she does not enroll for the course she will get increment on her current salary 
of Rs. 20,00,000 @ 30%, 20% or 10% incase of economy is good, average or bad 
during the duration of the course. The probability of economy to be good or bad is 
30% each and to be average is 40%
23 
Payoff Table 
A payoff table provides alternatives, 
states of nature, and payoffs 
Alternative 
(Action) 
Salary in INR 100,000 
Choice (Action) 
Good 
Economy 
Average 
Economy 
Bad 
Economy 
Join 39 29 19 
Not Join 26 24 22 
Probabilities 0.3 0.4 0.3
Decision Making - Criteria 
24 
• Maximax 
– An optimistic decision criteria 
• Maximin 
– A pessimistic decision criteria 
• Minimax Regret 
– Minimum of worst regrets 
• Expected Monetary Value (EMV) 
– The expected profit for taking action 
• Expected Opportunity Loss (EOL) 
– The expected opportunity loss for taking action. 
• Expected Profit Under Certainty (EPUC) 
– The expected opportunity loss from the best decision 
• Expected Value of Perfect Information (EVPI) 
– The expected opportunity loss from the best decision
25 
Decision Tree 
Decision Tree 
A Decision Tree is a chronological 
representation of the decision process. 
A Visual Representation of 
Alternatives, Payoffs, and 
Probabilities. 
25
Decision Tree 
• A Decision Tree is a chronological representation 
of the decision process. 
• The tree is composed of nodes and branches. 
A branch emanating from a state of 
nature (chance) node corresponds to a 
particular state of nature, and includes 
the probability of this state of nature. 
Decision 
node 
Chance 
node 
P(S2) 
P(S2) 
A branch emanating from a 
decision node corresponds to a 
decision alternative. It includes a 
cost or benefit value. 
26
Decision Tree 
50L 
40L 
25L 
26L 
24L 
22L 
29L 
24L 
0.3 
0.4 
0.3 
0.3 
0.4 
0.3 
29L 
11L 
Join WMP 
Decision Point 
Action 
Expected 
Value 
27
28 
Kaun Banega Crorepati 
You are a contestant on “Kaun Bangega Crorepati?” You already have answered the Rs. 
25L question correctly and now must decide if you would like to answer the Rs. 50L 
question. You can choose to walk away at this point with Rs. 25L in winnings or you may 
decide to answer the Rs. 50L question. If you answer the Rs. 50L question correctly, you 
can then choose to walk away with Rs. 50L in winnings or go on and try to answer the Rs. 
100L question. If you answer the Rs. 100L question correctly, the game is over and you 
win Rs. 100L. If you answer either question incorrectly, the game is over immediately and 
you take home “only” Rs. 3.2L. 
You have the “phone a friend” lifeline remaining. With this option, you may phone a 
friend to obtain advice on the correct answer to a question before giving your answer. You 
may use this option only once (i.e., you can use it on either the Rs. 50L question or the Rs. 
100L). Since some of your friends are smarter than you are, “phone a friend” significantly 
improves your odds for answering a question correctly. Without “phone a friend,” if you 
choose to answer the Rs. 50L question you have a 65% chance of answering correctly, 
and if you choose to answer the Rs. 100L question you have a 50% chance of answering 
correctly (the questions get progressively more difficult). With “phone a friend,” you have 
an 80% chance of answering the Rs. 50L question correctly and a 65% chance of 
answering the Rs. 100L question correctly.
29 
Kaun Banega Crorepati 
Crt 50% 
Incrt 50% 
w/o Life 
Crt 65% 
Incrt 35% 
Crt 50% 
Incrt 50% 
Don’t Play 
100L 
3.2L 
50L 
3.2L 
100L 
3.2L 
100L 
3.2L 
50L 
3.2L 
25L 
Decision Point 
Decision Point 
Events 
Action
30 
44.10 
Kaun Banega Crorepati 
41.92 
44.10 
51.60 
66.12 
Crt 50% 
51.60 
Incrt 50% 
66.12 
51.60 
w/o Life 
Crt 65% 
Incrt 35% 
Crt 50% 
Incrt 50% 
Don’t Play 
100L 
3.2L 
50L 
51.6 
3.2L 
100L 
3.2L 
100L 
3.2L 
50L 
66.12 
3.2L 
25L 
Decision Point 
Events 
Action
31 
References 
Ernest Urbanovich, Ella E. Young, Martin L. Puterman, Sidney O. Fattedad, (2003) Early 
Detection of High-Risk Claims at the Workers' Compensation Board of British Columbia. 
Interfaces 33(4):15-26. 
http://dx.doi.org/10.1287/inte.33.4.15.16372 
Robert K. Perdue, William J. McAllister, Peter V. King, Bruce G. Berkey, (1999) Valuation of R 
and D Projects Using Options Pricing and Decision Analysis Models. Interfaces 29(6):57-74. 
http://dx.doi.org/10.1287/inte.29.6.57 
Michael R. Walls, G. Thomas Morahan, James S. Dyer, (1995) Decision Analysis of Exploration 
Opportunities in the Onshore US at Phillips Petroleum Company. Interfaces 25(6):39-56. 
http://dx.doi.org/10.1287/inte.25.6.39
Annexure

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Decision Tree Analysis

  • 2. Agenda 1. Objective 2. Literature Review 3. Decision making  Overview  Decision making Environment  Decision Making Criteria 4. Models 5. Case 6. References 2
  • 3. Objective How the Decision Analysis can help in decision making in the face of uncertainty 3
  • 4. Literature Review Decision analysis provides a framework and methodology for rational decision making when the outcomes are uncertain. 4
  • 5. WCB Worker’s Compensation Board of British Columbia, Canada Over 1,65,000 employers 1.8 million workers Spends US$1 billion p.a. Objective – Improve service & Reduce cost 5
  • 6. WCB Applying Decision Analysis with decision trees WCB is now saving approximately US $4 million per year while also enabling some injured workers return to work sooner Source: Ernest Urbanovich, Ella E. Young, Martin L. Puterman, Sidney O. Fattedad, (2003) Early Detection of High-Risk Claims at the Workers' Compensation Board of British Columbia. Interfaces 33(4):15-26. http://dx.doi.org/10.1287/inte.33.4.15.16372 6
  • 7. Westinghouse Westinghouse Science and Technology Center R&D Arm to develop new technology Objective – Deliver high impact technology quickly & Reduce cost 7
  • 8. Westinghouse OR team developed a decision tree approach to analyzing any R&D proposal while considering its complete sequence of key decision points. A decision tree with a progression of decision nodes and intervening event nodes provided a natural way of depicting and analyzing such an R&D project. Source: Robert K. Perdue, William J. McAllister, Peter V. King, Bruce G. Berkey, (1999) Valuation of R and D Projects Using Options Pricing and Decision Analysis Models. Interfaces 29(6):57-74. http://dx.doi.org/10.1287/inte.29.6.57 8
  • 9. ConocoPhillips Conoco Inc. and Phillips Petroleum company 3rd largest integrated energy co. in US Objective – Judicious Allocation of investment capital across a set of exploration projects 9
  • 10. Westinghouse In early 1990’s – Industry leader Source: Michael R. Walls, G. Thomas Morahan, James S. Dyer, (1995) Decision Analysis of Exploration Opportunities in the Onshore US at Phillips Petroleum Company. Interfaces 25(6):39-56. http://dx.doi.org/10.1287/inte.25.6.39 10 in application of OR methodology DISCOVERY – decision analysis s/w package • Evaluate exploration projects • Rank Projects • Budget Consideration
  • 11. Should You Ask? Sir, why is my coursework marks so low? I deserve higher marks. Hehehe!
  • 12. Which Mobile Phone should I buy? What are the things you consider before making a decision?
  • 13. Whom should I marry? What are the things you consider before making a decision?
  • 14. Decision A general approach to decision making that is suitable to a wide range of operations management decisions: 14 Capacity planning Product and service design Equipment selection Location planning
  • 15. Decision Making Overview Decision Making Decision Environment Decision Criteria Certainty Nonprobabilistic Uncertainty Probabilistic 15
  • 16. The Decision Environment Decision Environment Certainty: The results of decision 16 Certainty Uncertainty alternatives are known Example: Must print 10,000 color brochures Offset press A: $2,000 fixed cost + $.24 per page Offset press B: $3,000 fixed cost + $.12 per page *
  • 17. The Decision Environment 17 Decision Environment Certainty Uncertainty Uncertainty: The outcome that will occur after a choice is unknown Example: You must decide to buy an item now or wait. If you buy now the price is $2,000. If you wait the price may drop to $1,500 or rise to $2,200. There also may be a new model available later with better features. * (continued)
  • 18. Decision Criteria Nonprobabilistic Decision Criteria: Decision Decision Criteria rules that can be applied if the probabilities of uncertain events are not known. 18 Nonprobabilistic Probabilistic *  maximax criterion  maximin criterion  minimax regret criterion
  • 19. Decision Criteria 19 Decision Criteria Nonprobabilistic Probabilistic * Probabilistic Decision Criteria: Consider the probabilities of uncertain events and select an alternative to maximize the expected payoff of minimize the expected loss  maximize expected value  minimize expected opportunity loss (continued)
  • 20. Step 1 Identify possible future conditions or state of nature Develop a list of possible alternatives Determine the payoff associated with each alternative for every possible future condition Estimate the likelihood of each possible future conditions Evaluate alternatives based to some decision criterion, and select the best alternative Decision Making Process: Step 2 Step 3 Step 4 Step 5
  • 21. 21 Decision Models Decision Models Payoff Matrix Decision Tree
  • 22. Decision Illustration 22 Sunny wants to join WMP from IIM Lucknow, Noida Campus. She is hopeful that if after completion of course she will get better opportunity and her salary will be INR 50,00,000, if the economy is good. If the economy is average, she will get a salary of Rs. 40,00,000. If economy is bad she will get Rs. 30,00,000. The fee for course is approx. Rs. 8,10,000. Also she estimates that there would be some incidental expenses of Rs. 2,90,000 on commuting etc. In case she does not enroll for the course she will get increment on her current salary of Rs. 20,00,000 @ 30%, 20% or 10% incase of economy is good, average or bad during the duration of the course. The probability of economy to be good or bad is 30% each and to be average is 40%
  • 23. 23 Payoff Table A payoff table provides alternatives, states of nature, and payoffs Alternative (Action) Salary in INR 100,000 Choice (Action) Good Economy Average Economy Bad Economy Join 39 29 19 Not Join 26 24 22 Probabilities 0.3 0.4 0.3
  • 24. Decision Making - Criteria 24 • Maximax – An optimistic decision criteria • Maximin – A pessimistic decision criteria • Minimax Regret – Minimum of worst regrets • Expected Monetary Value (EMV) – The expected profit for taking action • Expected Opportunity Loss (EOL) – The expected opportunity loss for taking action. • Expected Profit Under Certainty (EPUC) – The expected opportunity loss from the best decision • Expected Value of Perfect Information (EVPI) – The expected opportunity loss from the best decision
  • 25. 25 Decision Tree Decision Tree A Decision Tree is a chronological representation of the decision process. A Visual Representation of Alternatives, Payoffs, and Probabilities. 25
  • 26. Decision Tree • A Decision Tree is a chronological representation of the decision process. • The tree is composed of nodes and branches. A branch emanating from a state of nature (chance) node corresponds to a particular state of nature, and includes the probability of this state of nature. Decision node Chance node P(S2) P(S2) A branch emanating from a decision node corresponds to a decision alternative. It includes a cost or benefit value. 26
  • 27. Decision Tree 50L 40L 25L 26L 24L 22L 29L 24L 0.3 0.4 0.3 0.3 0.4 0.3 29L 11L Join WMP Decision Point Action Expected Value 27
  • 28. 28 Kaun Banega Crorepati You are a contestant on “Kaun Bangega Crorepati?” You already have answered the Rs. 25L question correctly and now must decide if you would like to answer the Rs. 50L question. You can choose to walk away at this point with Rs. 25L in winnings or you may decide to answer the Rs. 50L question. If you answer the Rs. 50L question correctly, you can then choose to walk away with Rs. 50L in winnings or go on and try to answer the Rs. 100L question. If you answer the Rs. 100L question correctly, the game is over and you win Rs. 100L. If you answer either question incorrectly, the game is over immediately and you take home “only” Rs. 3.2L. You have the “phone a friend” lifeline remaining. With this option, you may phone a friend to obtain advice on the correct answer to a question before giving your answer. You may use this option only once (i.e., you can use it on either the Rs. 50L question or the Rs. 100L). Since some of your friends are smarter than you are, “phone a friend” significantly improves your odds for answering a question correctly. Without “phone a friend,” if you choose to answer the Rs. 50L question you have a 65% chance of answering correctly, and if you choose to answer the Rs. 100L question you have a 50% chance of answering correctly (the questions get progressively more difficult). With “phone a friend,” you have an 80% chance of answering the Rs. 50L question correctly and a 65% chance of answering the Rs. 100L question correctly.
  • 29. 29 Kaun Banega Crorepati Crt 50% Incrt 50% w/o Life Crt 65% Incrt 35% Crt 50% Incrt 50% Don’t Play 100L 3.2L 50L 3.2L 100L 3.2L 100L 3.2L 50L 3.2L 25L Decision Point Decision Point Events Action
  • 30. 30 44.10 Kaun Banega Crorepati 41.92 44.10 51.60 66.12 Crt 50% 51.60 Incrt 50% 66.12 51.60 w/o Life Crt 65% Incrt 35% Crt 50% Incrt 50% Don’t Play 100L 3.2L 50L 51.6 3.2L 100L 3.2L 100L 3.2L 50L 66.12 3.2L 25L Decision Point Events Action
  • 31. 31 References Ernest Urbanovich, Ella E. Young, Martin L. Puterman, Sidney O. Fattedad, (2003) Early Detection of High-Risk Claims at the Workers' Compensation Board of British Columbia. Interfaces 33(4):15-26. http://dx.doi.org/10.1287/inte.33.4.15.16372 Robert K. Perdue, William J. McAllister, Peter V. King, Bruce G. Berkey, (1999) Valuation of R and D Projects Using Options Pricing and Decision Analysis Models. Interfaces 29(6):57-74. http://dx.doi.org/10.1287/inte.29.6.57 Michael R. Walls, G. Thomas Morahan, James S. Dyer, (1995) Decision Analysis of Exploration Opportunities in the Onshore US at Phillips Petroleum Company. Interfaces 25(6):39-56. http://dx.doi.org/10.1287/inte.25.6.39