Develop an appropriate forecast model for bookstoremanagement to use to forecast computer demand for thenext fall semester and indicate how accurate it appearsto be. What other forecasts might be useful to the book-store in managing its supply chain?
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Develop an appropriate forecast model for bookstoremanagement to use to forecast computer demand for thenext fall semester and indicate how accurate it appearsto be. What other forecasts might be useful to the book-store in managing its supply chain?
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- Under what conditions might a firm use multiple forecasting methods?The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
- The file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?
- The file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?The file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?Qualitative forecasts and causal forecasts are not particularly useful as inputs to inventory and scheduling decisions. Why is this statement true?
- Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 5 months. The forecasts and actual sales are as follows: Month 1 2 3 4 5 6 sales 77 75 78 76 74 71 Forecast1 75 72 81 75 75 73 Forecast2 70 73 79 74 75 72 a. Compute the MAD, MSE and MAPE for each forecast. Does either forecast seem to be superior? Explain. (Round off your numbers to two decimal places, e.g., 2.674 → 2.67) b. Compute 2s control limits for each forecast and draw a control chart. Are the forecast errors with in control limits? Round off your numbers to two decimal places.What should be our forecast accuracy target if there is a high degree of volatility in customer orders and long lead times? We have a new chief sales officer who is proposing that we should forecast in dollars, not in units/cases. I have never heard of anyone forecasting in dollars. It is true that dollarized forecasts can help Sales in knowing precisely what sales target they should be hitting. But, is it the best practice?All forecasts are subject to error. Do you think topmanagers would be concerned about the effectson the firm if sales revenues or unit costs, forexample, turned out to be different from the forecasted level? How could you provide informationon the effects of such errors?