Business Forecasting Case Study

Business Forecasting Business Forecasting Case Study Case I: Sue and Bill Golden have decided to open a restaurant in a city in the Midwest. They have spent over a year researching the area and visiting medium- to high-price restaurants. They definitely believe that there is room for another restaurant and have found a good site that is available at a good price. In addition, they have contacts with a number of first-class chefs and believe that they can attract one of them to their new restaurant. Their inquiries with local bankers have convinced them that financing will be readily available, given their own financial resources and their expertise in the restaurant business. The only thing still troubling the Goldens is the atmosphere or motif for their restaurant. They have already conducted a series of three focus groups with area residents who eat out regularly, and no consensus on this matter emerged. They have talked about the matter considerably between themselves but now believe some other opinions would be valuable. After reading about some of the techniques used in judgmental forecasting, they believe some of them might help them decide on the atmosphere for their new restaurant. They have identified a number of their friends and associates in other cities who would be willing to help them but are not certain how to utilize their talents. QUESTIONS 1. What method would you suggest to the Goldens in utilizing the expertise of their friends to decide on the atmosphere and motif for their new restaurant? 2. Are there any other methods they have overlooked in trying to research this matter? If yes, explain how they would have done it. Business Forecasting Case II: Julie Ruth, the president of Alomega Food Stores, collected monthly sales data for her company along with several other variables she thought might be related to sales. She attempted to use various forecasting procedures available in Minitab in an effort to produce meaningful forecasts of monthly sales. Julie developed a multiple regression model that explained almost 91% of the monthly sales variable variance. She felt good about this model but was especially sensitive to the negative comments made by Jackson Tilson, her production manager, during a recent meeting. Tilson said, “I’ve been trying to keep my mouth shut during this meeting, but this is really too much. I think we’re wasting a lot of people’s time with all this data collection and fooling around with computers. All you have to do is talk with our people on the floor and with the grocery store managers to understand what’s going on. I’ve seen this happen around here before, and here we go again. Some of you people need to turn off your computers, get out of your fancy offices, and talk with a few real people.” Julie decided that office politics dictated that she heed Jackson’s advice. She consulted with several people, including Tilson, to determine their opinions of how to forecast sales for January 2007. A large majority felt that using the sales figure for the previous January would provide the best prediction. Likewise, the forecast for February 2007 should be based on the sales figure for February 2006. Based on this input, Julie developed a naive forecasting model: 𝑌” !”# = 𝑌!$## that used last year’s monthly value to predict this year’s monthly value. The sales for the years from 2003 to 2006 are given in the table below: Business Forecasting QUESTIONS 1. How accurate is Julie’s naive forecasting model? 2. Julie is considering combining forecasts. Should she use a simple average or weighted average approach to combining the forecasts?

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