I have an assignment with no costs related to the problem. A new product coming out that has a median mileage of 36,500 and a deviation of 5000. How do I start creating a model when there are no costs?
a bit confused...
V
Answer:
You need to do some research! If there is a new product coming out, there must be an old product. You need to find out the details of the old product. Here are some questions to ask: 1. Can you construct a life cycle series of cash flows for the old and new product? 2. Since you have the statistical parameters of mean and standard deviation, would this be a good candidate for a Monte Carlo simulation? 3. Do you know the people who initiated the project? If so go and interview them with your questions. 4. Are there industry standard costs for your project?
This is the kind of real world situation that you will find yourself in repeatedly as an engineer or business analyst. You just need to beat the bushes to find the data that you need to make your analysis.
This is a little like real life. You have a project that only gives you a minimum amount of data. You have to come up with the rest of the data to make an analysis.
Let's see how we might get enough data to make an analysis. Suppose that our new product is a golf cart. It's life is based on the number of miles it is driven. When you do your research you find that there are 2 competitors that make golf carts that have a "moving life" of 25,000 miles and 30,000 miles respectively. The standard deviations are 5,000 in both cases. You also find the purchase costs to be $10,000 and $12,000. Now you must go back to your engineering and marketing department to decide on a price for your cart.
As you can see, it often takes a bit of research to start obtaining the necessary data to construct a model and make an analysis.
It is very important that you document everything. You want your analysis report to be show how you came up with every piece of data that you use. If someone (your boss) objects to your analysis, you can respond by asking, what data they would have used.
