A chain of pizza stores has had the following sales for take-out food over the last four evenings-Monday, Tuesday, Wednesday, and Thursday-of 29, 25, 35, and 30 pizzas, respectively. What would be their forecast for Friday using a naïve forecasting approach? Select one: a. 30 pizzas. b. 35 pizzas. c. 29.8 pizzas. d. 25 pizzas.
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- Under what conditions might a firm use multiple forecasting methods?At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.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 owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?Canton Supplies, Inc., is a service firm that employs approximately 100 people. Because of the necessity of meeting monthly cash obligations, the chief financial officer wants to develop a forecast of monthly cash requirements. Because of a recent change in equipment and operating policy, only the past seven months of data are considered relevant. The change in operations has had a great impact on cash flow. What forecasting model do you recommend? Use the Moving Average and Exponential Smoothing Excel templates or other Excel tools to help you answer this question. Cash Required Cash Required Month ($1,000) Month ($1,000) 1 186 5 233 2 219 6 241 3 216 7 204 4 270 Find the best number of months to use in a moving average forecast based on MSE. Do not round intermediate calculations. Round your answers to two decimal places. Number of months MSE 2 3 4 The model is the best. Find the best single exponential smoothing model by…As a supply chain manager for a company, you are tasked with forecasting the demand for a particular product. To assess the accuracy of your forecasting model, you decide to calculate the Mean Absolute Percent Error (MAPE) for the past seven months. Below is the data representing the actual demand and forecasted demand for each month: Month Actual Demand Forecasted Demand 1 1000 1100 2 900 1200 3 1300 1400 4 1100 700 5 2000 1700 6 1500 1200 7 1600 1500 What is the Mean Absolute Percent Error (MAPE) for the seven-month period? Question 1 options: a) 20.68% b) 17.66% c) 18.38% d) 19.44%
- It has been said that forecasting using exponential smoothing is like driving a car by looking in therear-view mirror. What are the conditions that would have to exist for driving a car that are analogous to the assumptions made when using exponential smoothing?2. What capability would an organization have to have to not need forecasts?3. When a new business is started, or a patent idea needs funding, venture capitalists or investmentbankers will want to see a business plan that includes forecast information related to a profit andloss statement. What type of forecasting information do you suppose would be required?4. Discuss how you would manage a poor forecast.5. Omar has heard from some of his customers that they will probably cut back on order sizes in thenext quarter. The company he works for has been reducing its sales force due to falling demand andhe worries that he could be next if his sales begin to fall off. Believing that he may be able to convince his customers not to cut…The following company sells two family of products. The company begins its roll-up forecast anticipating a need for 60 units of A1 and 75 units of A2 at a cost of $200 per unit and $350 per unit, respectively. In addition, they anticipate a need for 85 units of B1 and 90 units of B2 at a cost of $410 per unit and $525 per unit respectively. Complete the roll-up pyramid forecasting technique for MPC Inc. Fill all the blanks. Allow 1 decimal value.The past two years sales at ACSR Inc. were 3 million and 5 million. Their forecast team used a two-period moving average to forecast its sales this year. But the actual sales for this year were 5 million. Now, the forecast team wants to forecast its sales for next year by using exponential smoothing with alpha equals 0.6. What is the forecast using exponential smoothing with alpha = .6? 2. If we decide to use an alpha of .2 instead of .6, will we be ‘weighting the error from the previous period higher or the Forecast from the previous period higher? Explain briefly or show using math! (In this question I am asking if we change the alpha to a lower alpha, what will be the effect – what will we be ‘weighing’ as more important?)
- A manufacturing firm has developed a skills test, the scores from which can be used to predict workers’ production rating factors. Data on the test scores of various workers and their subsequent production ratings are shown.a. Using POM for Windows’ least squares-linear regression module, develop a relationship to forecast production ratings from test scores.b. If a worker’s test score was 80, what would be your forecast of the worker’s production rating?c. Comment on the strength of the relationship between the test scores and production ratings.The manager of a travel agency asked you to come up with a forecasting technique that will best fit to the actual demand for packaged tours. You have observed and recorded the actual demand for the last 10 periods. You also identified two possible techniques for consideration: 2-month moving averages (F1), and exponential smoothing (F2) with a smoothing constant of 0.25. Using Cumulative Forecasting Error (CFE) and Mean Absolute Deviation (MAD) as your performance measures you will determine the technique that will best fit to the actual demand data provided in the following table.STEP 1: Given start forecast values in period 3, compute forecast values from period 4 to 10. You are asked to provide the forecast values for period 6 and 10 for both techniques. 2-Month MA Exponential Period Demand F1 F2 1 115 -- -- 2 176 -- -- 3 97 146 129 4 141 5 98 6 132 7 114 8 129 9 107…A retail store records customer demand during each sales period. The data has been collected in the Microsoft Excel Online file below. Use the Microsoft Excel Online file below to develop three-period and four-period moving average forecasts and answer the following questions. Questions 1. What is the forecast for the 13th period based on the three-period moving average? Round your answer to two decimal places. 2. What is the MSE for the three-period moving average? Round your answer to two decimal places. 4. What is the forecast for the 13th period based on the four-period moving average? Round your answer to two decimal places. 5. What is the MSE for the four-period moving average? Round your answer to two decimal places. 7. Which forecast is the best based on the MSE value?
