I do not understand question 1.

Strategic Capacity Analysis Decision Tree Use for Production Capacity Determination at Toyota Motor Manufacturing of Canada (TMMC) This exercise illustrates how determination of an "optimal" production capacity option can be made from among several possible options based on the probability of their occurrence and the provided payoffs of events that influence these options. If you are not familiar with the decision tree analysis, you are strongly encouraged to study the voice recorded PPT and read the text book. The concept of the expected value is so important to solve problem. It is FYO, and TMMC has decided to produce the new Lexus RX 330 line, with the first unit deliverable in FY3. Toyota must now determine the amount of annual production capacity it should build. Toyota's goal is to maximize the profit from this line over the five years from FY3- FY7. These vehicles will sell for an average of $37,000 and incur a unit production cost of $28,000. 10,000 units of annual production capacity can be built for $50M (M=million) with additional blocks of 5,000 units of annual capacity each costing $15M. Each block of 5,000 units of capacity will also cost $5M per year to maintain, even if the capacity unused. Marketing has provided three vehicle demand scenarios with associated probabilities as follows: FY4 FY6 FY7 Demand Low Moderate High FY3 10,000 15,000 20,000 10,500 16,000 24,000 FY5 11,000 17,000 26,000 11,500 18,000 12,000 19.000 30,000 Probability 0.25 0.50 0.25 28,000 Assume that the number of units actually sold each year will be the lesser of the demand and the production capacity. 1. Should TMMC in FYO decide to build a facility with a production capacity of 10,000, 15,000, 20,000, 25,000, or 30,000 cars? Mathematically justify your answer based on the information provided. 2. What are the flaws or limitations in this analysis? Provide at least three. This is to evaluate your level of understanding on the method in terms of the theoretical background, assumptions and managerial insights. Do not say that the forecasting is not accurate or the data is not accurate or sufficient etc. (any forecasting is not accurate!). For example, no consideration of time value of