tim hw 4

Research & Development Problem:

Problem:

How can we determine whether Bill should fund a research team to cure Lyme’s disease?

Real problems that need to be solved:

· Should Bill fund a research team?

· If Bill funds a research team, should they produce the drugs themselves?

· How/where did Jackson Pharmaceuticals obtain their probability values?

Plan:

Information available to solve the problem:

· Lectures/Notes

· Textbook

· Internet

Analyses and steps that must be performed:

- Perform a decision analysis to model the dilemma

- Draw decision trees and diagrams

- Determine the pay offs/EMVs of each possible decision and draw conclusions through comparison

- Speculate how/where the probability values are determined

Execute:

Decision Analysis:

Basic Building blocks:

Influence Diagram:

Decision Tree:

Payoff or Expected Monetary Value associated with each choice (through folding back Decision Tree):

Yes to funding research, yes to producing themselves: $9.2 Million

Yes to funding research, no to producing themselves: $6 Million

No to funding research: $0

Conclusion:

Bill Mackenzie should definitely make the decision to fund a research team to cute Lyme’s disease, as well as producing the product themselves if they successfully find the cure. Reviewing the decision analysis payoffs, funding the research and producing the product themselves has an expected monetary value (EMV) of $9.2 million. Assuming both decisions run successfully, this yields a revenue of $60 million, recovering the $10 cost and yielding a profit of $50 million. Even funding the research and selling the license for producing the product to a chemical lab has an EMV of $6 million, and would yield a profit of $30 million accounting for the $10 million cost. Compared to the payoff of $0 in not funding the research, executing a successful R&D program would greater benefit the company. Shown in the decision analysis, the rewards of success greatly outweigh the consequences of the program if it were to fail.

Jackson Pharmaceuticals likely got their probability values through analyzing their own company’s past experience with R&D, as well as other data available on historical performance from similar companies in the industry. Compiling information on other companies who have tried curing a disease, or fixing a problem and their success rates can be used as a base for Jackson Pharmaceuticals to derive their own probability numbers, while taking into consideration their past performances and capabilities in R&D and production quality/consistency.

Drug X Product Development Problem:

Problem:

Should Pharma C, Inc. pursue the commercial development of compound X?

Real problems that need to be solved:

· Does the potential payoff outweigh the potential cost?

· What value should you place on the project when comparing it to competing projects?

Plan:

Information available to solve the problem:

· Lectures/Notes

· Textbook

· Internet

Analyses and steps that must be performed:

- Perform a decision analysis to model the dilemma

- Draw decision trees and diagrams

- Determine the pay offs/EMVs of each possible decision and draw conclusions through comparison

- Perform a sensitivity analysis on the results

- Identify the primary method of valuing projects such as this one against other competing projects

Execute:

Decision Analysis:

Basic Building blocks:

Influence Diagram:

Decision Tree:

Payoff or Expected Monetary Value associated with each choice (through folding back Decision Tree):

Yes to investing in R&D, and testing for approval: $51.25 Million

No to investing in R&D: $0

Sensitivity Analysis:

· Given a 20% perturbation in the probability of Successful Testing (0.60):

· P1 = 0.72

· Payoff of approving testing: $500(0.72)+(-$50)(0.28) = $346 Million

· Payoff of pursuing project: $346(0.25)+(-$25)(0.75) = 67.75 Million

· EMV increases by 16.5 Million

· P1 = 0.48

· Payoff of approving testing: $500(0.48)+(-$50)(0.52) = $214 Million

· Payoff of pursuing project: $214(0.25)+(-$25)(0.75) = 34.75 Million

· EMV decreases by 16.5 Million

· Given a 20% perturbation in the probability of Compound Effectiveness (0.25):

· P1 = 0.30

· Payoff of pursuing project: $280(0.30)+(-$25)(0.70) = 66.5 Million

· EMV increases by 15.25 Million

· P1 = 0.20

· Payoff of pursuing project: $280(0.20)+(-$25)(0.80) = 36 Million

· EMV decreases by 15.25 Million

· Given a 20% perturbation in the probability of both Successful Testing (.60) and Compound Effectiveness (0.25):

· P1ST = 0.72, P1CE = 0.30

· Payoff of approving testing: $500(0.72)+(-$50)(0.28) = $346 Million

· Payoff of pursuing project: $346(0.30)+(-$25)(0.70) = 86.3 Million

· EMV increases by 35.05 Million

· P1ST = 0.48, P1CE = 0.20

· Payoff of approving testing: $500(0.48)+(-$50)(0.52) = $214 Million

· Payoff of pursuing project: $214(0.20)+(-$25)(0.80) = 22.8 Million

· EMV decreases by 28.45 Million

Conclusion:

Pharma C, Inc. should pursue the commercial development of compound X. It is evident in the Decision Analysis process that product development of Drug X will bring a high potential profit that outweighs its potential losses. The calculated expected monetary value takes both measures into account, as well as the probabilities of success and failure during the R&D and Testing procedures and yields a high payoff of $51.25 million.

Ultimately, in pursuing the development of Drug X, Pharma C, Inc. should continue to value the project against competing projects through its calculated payoff, or EMV. While expected profits can be useful in indicating which projects have the highest benefit potential, EMV considers the prospects of failure, the probabilities of different outcomes during operations and execution stages, as well as the costs of failure that may make certain projects less desirable compared to other competing projects. EMV can also be computed for various levels of decisions, which is useful in identifying where aspects of one project’s execution may bring more value than stages of a competing project.

Through valuing the project based on EMV, Pharma C, Inc. can also perform sensitivity analyses to allow the company to better understand the relationship between how probabilities of success or failure with each decision impact the EMV of the overall project. By being aware of which decisions are robust, and which ones are not, Pharma C can better evaluate and compare risk between projects, and perhaps look into researching determinants of those probabilities and how to improve success rates.

We see in the sensitivity analysis of Drug X development that the decision to pursue the project does not change despite a 20% perturbation in the probability of Successful Testing or Compound Effectiveness. The decision also remains the same for a 20% perturbation in both probabilities. The EMV remains very high despite decreases or increases in the input probabilities, making the decision to pursue less risky and more robust in the event that estimations were inaccurate. In addition, the sensitivity analysis indicates that perturbations in the estimated probability of Successful Testing impact the EMV more-so than perturbations in the probability of Compound Effectiveness. We can conclude that the testing stage and its success ultimately play more of a role in generating the expected monetary value for the project than the investment in R&D.