The Vintage Restaurant is located on Captiva Island, a resort community located near Fort Meyers, Florida. The restaurant, which is owned and operated by Karen Payne, has just completed its third year of operation. During this time, Karen has sought to establish a reputation for the restaurant as a high-quality dining establishment that specializes in fresh seafood. The efforts made by Karen and her staff have proved successful, and her restaurant has become one of the best and fastest-growing restaurants on the island.
Karen has concluded that.in order to plan better for the growth of the restaurant in the future, it is necessary to develop a system that will enable her to forecast food and beverage sales by month for up to I year in advance. Karen has available data on the total food and beverage sales that were realized during the previous 3 years of operation. These data are provided below.
Food and Beverage Sales for the Vintage Restaurant ($ 1,000s)
Perform an analysis of the sales data for the Vintage Restaurant. Prepare a report for Karen that summarizes your findings, forecasts, and recommendations. Include information on the following:
1.A graph of the time series.
2.An analysis of the seasonality of the data. Include the seasonal indexes for each month, and comment on the high seasonal and low seasonal sales months. Do the seasonal indexes make intuitive sense? Discuss.
3.Forecast sales for January through December of the fourth year.
4.Assume that January sales for the fourth year turned out to be $295,000. What was your forecast error? If this is a large error, Karen may be puzzled as to why there is such a difference between your forecast and the actual sales value. What can you do to resolve her uncertainty in the forecasting procedure?
5.Develop recommendations as to when the system that you have developed should be updated to account for new sales data that will occur.
6.Include any detailed calculations of your analysis in the appendix of your report.
The solution illustrates the graph of the time series, data seasonality, and data forecasting. The step-by-step guide on how to do this is described in an spreadsheet file.