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Capella University Manufacturing Company Data Mining Questions

 

You are a business analyst for a small manufacturing company in a small town of 12,000 people along one of the Great Lakes. The company enjoys a 46 percent market share, strong profits, and happy shareholders (owners). In your last meeting, you were tasked with making a recommendation for a new product line of widgets that recreational boaters could use to enhance their boats. Money is no object, so you were only provided data by the manager of operations. The owners of the company have two objectives—grow the business by at least 18 percent for every new product and only start a project if there is at least an 85 percent probability that the new product line will sell for at least 33 percent over the cost of developing and producing the product.

Using the information provided in the Do We Go for It? document, linked in the Resources, create a decision-tree model and then craft an analysis based on your model in which you do the following:

  • Recommend for or against starting a new product line, explaining how you arrived at that recommendation.
  • Explain any bias that may exist within your model.
  • Identify additional methods to test, enhance, and support your recommendations.
  • Explain any warnings for the company’s decision makers.
  • Be sure to address the scoring guide criteria in your analysis and to include your model in the appendix.