A car company is planning the introduction of a new electric car. There are two options for production. One is to produce the electric car at the company’s existing plant in Illinois, sharing production with its other products that are currently being produced there. If the sales of the electric car are moderate, this will work out well as there is significant capacity to produce all of the products there. However, if sales of the electric car are strong, this option would necessitate adding a 3rd shift, which would lead to significantly higher costs.

Another option is to build a new plant in Ohio. The new plant would have sufficient capacity to meet whatever level of demand for the new car. However, if sales of the new car not strong, the plant would be underutilized and less efficient.

Since this is a new product, sales are hard to predict. The forecast indicates there is a 60% chance of strong sales (annual sales of 100,000), and 40% chance of moderate sales (annual sales of 50,000). The average revenue per electric car sold is $30k.

Production costs for the new car are dependent on sales. This is indicated in the data below.

                                                Moderate Sales                         Strong Sales

            Shared Site in IL          $16k                                        $24k

            Dedicated Site in OH    $22k                                        $20k

The annual cost, including construction and all fixed costs, for the Ohio plant is $400 million regardless of sales volume. The annual cost, including construction and all fixed costs, for the Illinois plant is $200 million regardless of sales volume.

Considering fixed costs, production costs and sales volume, construct a decision tree to determine which production option maximizes the expected annual profit.

(Decision Tree)