EMAW is a small manufacturer of servers that currently builds its entire product in Santa Clara, California. As the market for servers has grown dramatically, the Santa Clara plant has reached capacity of 10,000 servers per year. EMAW is considering two options to increase its capacity. The first option is to add 10,000 units of capacity to the Santa Clara plant at an annualized fixed cost of $10 million plus $500 labor per server. The second option is to have Willie, an independent assembler, manufactures servers for EMAW at a cost of $2,000 for each server (excluding raw materials cost). Raw materials cost $8,000 per server, and EMAW sells each server for $15,000.
EMAW must make this decision for a two-year time horizon. During each year, demand for EMAW servers has an 80 percent chance of increasing 50 percent from the year before and a 20 percent chance of remaining the same as the year before. Willie’s prices may change as well. They are fixed for the first year but have a 50 percent chance of increasing 20 percent in the second year and a 50 percent chance of remaining where they are. EMAW will use a decision tree to determine whether they should add capacity to its Santa Clara plant (Option 1) or if it should outsource to Willie (Option 2).
what is the total probability of that demand increases in year 1, remains the same in year 2, and goes up in the second year?
how much is the incremental profit of Option 1 (adding capacity to Santa Clara) under scenario in question above?
how much is the final expected incremental profit of Option 1?
How much is the final expected incremental profit in Option 2?