C207_Task 2_Final

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lOMoARcPSD|17574477 lOMoARcPSD|17574477 C207 Data Driven Decisions College of Business, Western Governors University August 27, 2023

lOMoARcPSD|17574477 A: Business Question A business question that could be asked based upon the scenario given is whether MPC would maximize profits by developing a new drug line, exploring new applications for their existing drug line, or doing nothing at all. B: Relevant Data Values The relevant data values for this decision tree analysis are present in the following table: Probability of Immediate Need Demand Units Low (Unfavorable market) High (Favorable market) Profit Per Unit LOW (Unfavorable Market HIGH (Favorable Market) ALTERNATIVES 0.31 0.69 0.65 1355 4133 NEW DRUG LINE 0.39 0.61 0.77 1911 5577 EXISTING DRUG W/CHANGES 0.23 0.77 0.87 258 657 NO CHANGES This data table represents the three alternatives presented in the stated business question. For each alternative, both demand units and probability are given along with the profit per unit. The demand units and probability are presented in both favorable and unfavorable markets. We utilize this information to calculate both the Payoff and Expected Value for each alternative. C1. Please see attached Excel spreadsheet for the completed decision tree analysis. C2. Justification Decision tree analysis are most useful when a company is doing risk assessment and wishes to make data driven decisions when there are multiple options to consider. A decision tree analysis is justified in this situation because it allows for comparison of all possible options in both favorable and unfavorable market conditions along with other market factors like demand and probability. “Decision trees use the weight of each risk and estimates to determine the potential impact for various alternatives.” (MindEdge Inc. 2022). In this scenario, MPC needs to make a decision that will keep them competitive in the market while maximizing their profits. The data revealed that by exploring some additional applications for their existing drug line, they would have an Expected Value of $3193.39, as opposed to Expected Values of $2126.68 for developing a new drug line, and $491.75 for leaving things as they are.

lOMoARcPSD|17574477 D1: Probabilities and Demand We utilize probability to determine likely outcome. Probability and demand are used to calculate the Payoff for each alternative, and the Payoff is subsequently used to calculate the Expected Value for each alternative. There is an unfavorable and favorable branch for every alternative. The first option to be considered by MPC is to develop a new drug line. The demand in the favorable market for this alternative is 4133 units per month, with a 69% probability. In the unfavorable market, the demand is 1355 units per month with a 31% probability. We normally associate higher demand with a greater probability of success, but this is not a guarantee. The success rate in the unfavorable market is fairly low, which could be considered a bit risky. The next option for MPC to consider is to explore additional applications for their existing drug line. In this alternative, the favorable market demand is at 5577 units per month with a 61% probability, and the unfavorable market demand is at 1911 units per month with a 39% probability. Although the probability is lower in the favorable market than what we see with the first option of creating a new drug line, there is less of a disparity between favorable vs unfavorable markets overall. This could translate into being a less risky option. MPC’s last alternative to choose from is to do nothing and keep things as they are. This option show a demand of 657 units per month with a 77% probability in the favorable market, and a demand of 258 units per month with a 23% probability in the unfavorable market. The unfavorable market is extremely risky with this alternative, which doesn’t make this a viable option for the company. D2: Expected Value and Payoff The first option to be considered by MPC is to develop a new drug line. The probability of immediate need in a favorable market is 69%, and 31% in an unfavorable market. We go on to calculate the Payoff by multiplying the demand in each state of nature by the profit per unit. We then determine the Expected Value by taking the favorable market payoff of $2686.45 and multiply it by the Probability of 69%, which results in $1853.65. We do the same for the unfavorable market payoff of $880 and its Probability of 31%, resulting in $273.03. By adding these two results ($1853.65 + $273.03) we get an Expected Value of $2126.68. The next option to be considered is to consider additional applications of MPC’s existing drug line. The probability of immediate need in a favorable market is 61%, and 39% in an unfavorable market. We go on to calculate the Payoff by multiplying the demand in each state of nature by the profit per unit. We then determine the Expected Value by taking the favorable market payoff of

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lOMoARcPSD|17574477 $4294.29 and multiply it by the Probability of 61%, which results in $2619.52. We do the same for the unfavorable market payoff of $1471.47 and its Probability of 39%, resulting in $573.87. By adding these two results ($2619.52+ $573.87) we get an Expected Value of $3193.39 The last option in our decision tree to be considered by MPC is to make no changes at all. The probability of immediate need in a favorable market is 77%, and 23% in an unfavorable market. We go on to calculate the Payoff by multiplying the demand in each state of nature by the profit per unit. We then determine the Expected Value by taking the favorable market payoff of $571.59 and multiply it by the Probability of 77%, which results in $440.12. We do the same for the unfavorable market payoff of $224.46 and its Probability of 23%, resulting in $51.63. By adding these two results ($440.12+ $51.63) we get an Expected Value of $491.75. D3: Limitations One limitation of the data contained in decisions trees is that it can be unstable. Although a company pays for market studies, there could be significant variation in the data obtained. Even small differences in data can impact the results, thereby affecting the decisions a company makes. A decision tree analysis isn’t always the best option. It is not appropriate for big data sets. Additionally, there is room for significant error when we choose to go with what appears to give us the biggest Expected Value. It could very well have the outcome we expect, however, the associated risks must also be considered. It may appear that the company would still be sustainable even after the projected loss, however, the company must translate the percentage of loss on paper into what it would actually mean in terms of its assets and operations. E. Recommendation After completing this decision tree analysis, the recommendation would be for MPC to explore new applications of its current drug line. This recommendation is based on an Expected Value of $3193.39 as opposed to an Expected Value of $2126.68 for the development of a new drug line, or $491.75 for making no changes at all. F. Sources MindEdge Inc. (2022): Data-Driven Decision Making

C207_Task 2_Final

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