Subject: Decision Analysis task 3
I have reviewed the figures and have made a recommendation based on my findings. It is my determination that given the data, we should purchase new equipment.
Let’s analyze the data. The data below reflects the outcome of reconditioning old equipment, purchasing new equipment, and outsourcing. Below is an insert from POM for Windows an operations management tool used to determine best decisions in business operations.
There are two types of costs to consider, fixed and variable. Based upon the information given the relationship between cost and revenues are linear. In order to use the cost volume and breakeven analysis tool, variable costs must be constant. Here we have constant costs but different scenarios which qualify it to be used by this tool. Using this tool, I created inputs for reconditioning new equipment, buying new equipment, and outsourcing. The figures for fixed and variable costs were used from company research. It was determined that at 1,000 units the variable costs could be determined and that it would be a good place to set our volume for analysis. The total fixed costs for reconditioning is $50,000 with one million dollars spent in variable costs for a total cost of $1.5 million. To purchase new equipment, the fixed costs are $200,000 and the variable costs are half of the cost of reconditioning the old equipment at $500,000 for a total cost of $700,000. Finally, to outsource, while there would be no initial or fixed costs, the variable cost would be $3 million, twice as much as it would costs to recondition the old equipment and 4 times as much as simply buying new equipment. According to the data presented to me, Shuzworld will save the most money by buying new equipment. While the fixed costs are more, the variable costs don’t compare to that of reconditioning or outsourcing. Below is a copy of the crossover chart showing where each one has its financial advantage over the other.
I chose the decision analysis tool breakeven cost volume analysis because the tool allowed for ease of use and also had parameters set up to account for the different types of costs and the number of options. In this case, we had 2 costs, fixed and variable, and 3 different options, reconstructing old equipment, purchasing new equipment, and outsourcing. This decision analysis tool allowed for us to construct a crossover chart which showed the points at which the costs of the options demonstrated an advantage over the other. When looking at the point of breakeven, the breakeven in reconstructing vs buy is at 350 units and a cost of $350,000. Recondition vs outsource brings us to a breakeven of 25 units and $75,000. Buy new vs. outsource gives us a breakeven of 80 units for a cost of $240,000. Recondition vs. buy gives us the lowest breakeven point which means that we start making profit at 350 units. The crossover chart tells us at which point we should switch to something else.
Problem: Opening new stores can be a very daunting task. Using previous sales trends to develop futuristic sales goals is a process known as forecasting. The first forecasting method used below is using the least squares method. The least squares method of forecasting attempts to project future sales using a straight line regression series. This method uses x and y intercepts and the changes in the series is referred to as the slope. Just as changes in a line can be determined by its slope, so can a sale forecast using the least squares method. The numbers presented are listed as follows.
Quarter | Sales |
2Q 2007 | 90K |
3Q 2007 | 95K |
4Q 2007 | 98K |
1Q 2008 | 96K |
2Q 2008 | 102K |
3Q 2008 | 99K |
4Q 2008 | 118K |
1Q 2009 | 109K |
2Q 2009 | 124K |
Using POM for Windows, I computed the data, and below is the output. I chose the least squares method because it was required to satisfy the objectives of this task.
In this interpretation, “x” refers to the time series which are being