Week 2 (8W) IA-1 Capacity Mgmt

The pairing option is permitted

Read Capacity Analysis Decision Tree Individual Assignment document Capacity Analysis Decision Tree Individual Assignment document – Alternative Formats

You may need to watch the Capacity Analysis Decision Tree video clip in the Strategic Capacity Management folder.

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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 FY0, 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 is unused.

Marketing has provided three vehicle demand scenarios with associated probabilities as follows:

Demand FY3 FY4 FY5 FY6 FY7 Probability

Low 10,000 10,500 11,000 11,500 12,000 0.25

Moderate 15,000 16,000 17,000 18,000 19,000 0.50

High 20,000 24,000 26,000 28,000 30,000 0.25

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 FY0 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 money in the long-term project could be a potential flaw (that is why we do it again in Q(3)). Based on the critics, if you are a manager of this company, are you going to adopt this or not? Explain it critically and succinctly.

3. According to the financial history, the company uses 5% annual interest rate for a dollar. Based on this time value of money, recalculate your choice in the problem 1 again. See if there is any change in your answer. (I ask you to calculate the Net Present Value, and evaluate your alternative again. You can use the NPV function in Excel).

To determine the optimal production capacity for TMMC, we need to calculate the expected profit for each of the production capacities and choose the one with the highest expected value. The expected profit is calculated as the sum of the product of the profit for each demand scenario and its probability.

Production capacity of 10,000 units:

Low demand: 10,000 x ($37,000 – $28,000) = $90,000,000

Moderate demand: 10,000 x ($37,000 – $28,000) = $90,000,000

High demand: 10,000 x ($37,000 – $28,000) = $90,000,000

Expected profit: (0.25 x $90,000,000) + (0.5 x $90,000,000) + (0.25 x $90,000,000) = $90,000,000

Production capacity of 15,000 units:

Low demand: 10,000 x ($37,000 – $28,000) = $90,000,000

Moderate demand: 15,000 x ($37,000 – $28,000) = $135,000,000

High demand: 15,000 x ($37,000 – $28,000) = $135,000,000

Expected profit: (0.25 x $90,000,000) + (0.5 x $135,000,000) + (0.25 x $135,000,000) = $117,500,000

Production capacity of 20,000 units:

Low demand: 10,000 x ($37,000 – $28,000) = $90,000,000

Moderate demand: 16,000 x ($37,000 – $28,000) = $144,000,000

High demand: 20,000 x ($37,000 – $28,000) = $180,000,000

Expected profit: (0.25 x $90,000,000) + (0.5 x $144,000,000) + (0.25 x $180,000,000) = $135,000,000

Production capacity of 25,000 units:

Low demand: 12,000 x ($37,000 – $28,000) = $108,000,000

Moderate demand: 18,000 x ($37,000 – $28,000) = $162,000,000

High demand: 25,000 x ($37,000 – $28,000) = $225,000,000

Expected profit: (0.25 x $108,000,000) + (0.5 x $162,000,000) + (0.25 x $225,000,000) = $162,000,000

Production capacity of 30,000 units:

Low demand: 12,000 x ($37,000 – $28,000) = $108,000,000

Moderate demand: 19,000 x ($37,000 – $28,000) = $171,000,000

High demand: 30,000 x ($37,000 – $28,000) = $240,000,000

Expected profit: (0.25 x $108,000,000) + (0.5 x $171,000,000) + (0.