C207 Task 2 Jones

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C207

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Jan 9, 2024

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Task 2: DECISION TREE 1 Decision Tree Jocelyn Jones Western Governors University
Task 2: DECISION TREE 2 Table of Contents A1. BUSINESS QUESTION 3 B1. RELEVANT DATA VALUES 3 C. DECISION TREE ANALYSIS 3 C1. DECISION TREE DIAGRAM 3 C2. JUSTIFICATION 4 D. SUMMARIZATION OF ANALYSIS 4 D1. EXPLAIN THE ROLE OF PROBABILITIES AND DEMAND FOR EACH BRANCH 4 D2. EXPLAIN HOW EV FOR EACH NODE IS DETERMINED BASED ON PAYOFFS 5 D3. DISCUSS ONE LIMITATION OF EACH OF THE FOLLOWING 5 E1. RECOMMENDATION 6
Task 2: DECISION TREE 3 Decision Tree A1. BUSINESS QUESTION Should MPC continue with maintaining its current drug line, make changes to its existing drug line for new applications, or take advantage of the new FDA approvals and develop a different drug line in order to maximize their profits? The above question is what MPC needs to determine and by using decision tree analysis, MPC will be able to determine the right course of action. B1. RELEVANT DATA VALUES See attached Excel Spreadsheet for more information. C. DECISION TREE ANALYSIS C1. DECISION TREE DIAGRAM
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Task 2: DECISION TREE 4 See attached Excel Spreadsheet for more information. C2. JUSTIFICATION Utilizing decision tree analysis is appropriate based on the type of data provided and business need presented in this case scenario. Since this scenario is presented with three different options, each having two pathways with specific data sets, using decision tree analytics allows for each option to be presented in the most uniform way, and allows for all possible options and outcomes to be easily compared. Therefore, the business can justify its business decisions based on profitability by using this type of analysis. D. SUMMARIZATION OF ANALYSIS D1. EXPLAIN THE ROLE OF PROBABILITIES AND DEMAND FOR EACH BRANCH MPC has three options, or alternatives, to decide upon. Each of these alternatives has two branches to consider, one being a favorable market and one being an unfavorable one. Each alternative also must consider the estimated probability of success and demand for the product in both favorable and unfavorable markets. For example, the first alternative, creating a new drug line, has a successful probability of 71% and a demand of 4341 units in a favorable market. Conversely, that same alternative has a 29% chance of success with a demand of 1205 in an unfavorable market. Typically, the higher the demand the better the probability of success. As stated above the first alternative has almost three times the amount of demand in a favorable market as opposed to the demand in an unfavorable one. Therefore, the success rate of a favorable market is in turn almost two-thirds higher. This holds true for the other two alternatives as well. When comparing all the options the best course of action is to consider each probability and demand for each option, otherwise if you just focus on the probabilities over demand then the option may not yield enough demand to make the investment worth it. The third option,
Task 2: DECISION TREE 5 continuing with the same drug line without making any changes, is a good example of this. This option has the highest favorable market probability at 81%, however, it also has the lowest unfavorable market probability at 19%. Both probabilities have the lowest demand for units, which makes this option the least desirable given that the return on investment will be the least profitable in either market. Alternatively, the other two options are very closely evaluated. However, when considering both the demand and probability of each market the first option of creating a new drug line has the highest expected value of the two. This is why the first option should be the decision that MPC makes. D2. EXPLAIN HOW EV FOR EACH NODE IS DETERMINED BASED ON PAYOFFS For each node, the profit per unit was multiplied by the estimated demand units for both the favorable and unfavorable markets. That produced the estimated payoff for each market, then you take that payoff and multiply that by the corresponding probability percentage for each market, and then add each of those together to the expected value for each node. For the node of “New Drug Line”, this equation would be the following: (($.63(4341)).71) + (($.63(1205)).29) = $2161.88EV. The EV, or expected value, means that MPC can expect to have an ending profit value of $2161.88. Each node would follow the same formula to produce their EV in order to better strategically compare the options MPC is faced with. D3. DISCUSS ONE LIMITATION OF EACH OF THE FOLLOWING Each type of decision analytics presents its own types of limitations. Using decision tree analysis is no exception. One type of limitation is in the type of data elements it uses. It does not utilize complex data, and if there are any changes to the data elements, however slight can change the outcome of the decision tree drastically. While the design of this type of analysis does make it
Task 2: DECISION TREE 6 user-friendly, it does not account for complex factors like research and development and market analysis which will affect the payoff outcomes. Additionally, another limitation is that this type of analysis is expensive. Each node on the tree will need to be thoroughly researched to determine unit demand and success probability in each market type. Without trusted data in each branch of each node, this type of analysis will not yield an effective result and therefore could cause considerable damage to the company if a decision was based on faulty, or inaccurately researched data. E1. RECOMMENDATION MPC should switch to a new drug line as this option has the highest expected value (EV) of the other options in the decision tree analysis. This option will allow MPC to fully maximize its profitability. The next favorable option would be to make changes to their current drug line for potential new applications, as this has the next highest gains on profits. There is a strong recommendation to not continue with the current drug line without making any adjustments as this option would have the lowest possible outcome on profits.
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