George S T Shirts Case Analysis

Topics: Decision theory, Risk, Probability Pages: 3 (1138 words) Published: March 16, 2015
Case Background
George Lassiter makes t-shirts for special events such as concerts. The upcoming concert presents another opportunity for George to make and sell t-shirts; however the question is how many t-shirts to produce. There are two fundamental case questions that must be answered: 1. What are the possible financial outcomes if Lassiter orders 5,000 T-shirts? 7,500? 10,000? As shown in the Exhibit, a rather simple but detailed decision tree has been made which represents the various options for George. The financial outcomes for the three different amounts of t-shirts that he can provide are presented in tabular form, in the Appendix. Table 1 shows profit outcomes for ordering 5000 shirts, Table 2 shows profit outcomes for ordering 7500 shirts, and Table 3 shows profit outcomes for ordering 10,000 shirts. Another possible decision for George was to provide 15,000 t-shirts. In the case where demand was high and the percentage of fans who bought the shirts was 15%, George could earn high profits. Therefore, we considered the possibility of ordering 15,000 shirts in two batches – 5000 shirts and 10,000 shirts. Ordering two batches of 7500 shirts would also yield the same result, but with a slightly higher cost; therefore, this was ignored. The result for this case is shown in Table 4. 2. How many T-shirts should Lassiter order?

To come up with an answer for George’s dilemma, we made a decision tree listing all the possible decisions, chances, and outcomes. This included the 15,000 shirts option as well. After rolling back the decision tree, the highest Expected Monetary Value (EMV) came out to be $26,574 for the ‘Order 10,000 shirts’ decision. It should be noted that while there was an equal likelihood of 80,000 and 20,000 grandstand seats, George felt that there was a very slightly higher probability of 80,000 seats for this concert. This intuition has been reflected in the tree diagram with probabilities for the higher extreme and lower extreme as 30%...
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