OPERATIONS MANAGEMENT CUSTOM ACCESS
11th Edition
ISBN: 9780135622438
Author: KRAJEWSKI
Publisher: PEARSON EDUCATION (COLLEGE)
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Textbook Question
Chapter 8, Problem 17P
The manager of a utility company in the Texas panhandle wants to develop quarterly forecasts of power loads for the next year. The power loads are seasonal, and the data on the quarterly loads in megawatts (MW) for the last 4 years are as follows:
The manager estimates the total demand for the next year at 600 MW. Use the multiplicative seasonal method to develop the
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The manager of a utility company in the Texas panhandlewants to develop quarterly forecasts of power loads for the nextyear. The power loads are seasonal, and the data on the quar-terly loads in megawatts (MW) for the last 4 years are as follows:
The manager estimates the total demand for the next year at600 MW. Use the multiplicative seasonal method to developthe forecast for each quarter.
Answer the following question please
Consider the following time series data.
Month 1 2 3 4 5 6 7
Value 24 13 20 12 19 23 15
Compute MSE using the most recent value as the forecast for the next period. What is the forecast for month 8?
Compute MSE using the average of all the date available as the forecast for the next period. What is the forecast for month 8?
Which method appears to provide the better forecast?
Chapter 8 Solutions
OPERATIONS MANAGEMENT CUSTOM ACCESS
Ch. 8 - Figure 8.9 shows summer air visibility...Ch. 8 - Kay and Michael Passe publish What‘s...Ch. 8 - Demand for oil changes at Garcia’s Garage has...Ch. 8 - Prob. 2PCh. 8 - Ohio Swiss Milk Products manufactures and...Ch. 8 - A manufacturing firm has developed a skills test,...Ch. 8 - The materials handling manager of a manufacturing...Ch. 8 - Marianne Kramer, the owner of Handy Man Rentals,...Ch. 8 - Sales for the past 12 months at Computer Success...Ch. 8 - Bradley’s Copiers sells and repairs photocopy...
Ch. 8 - Consider the sales data for Computer Success given...Ch. 8 - A convenience store recently started to carry a...Ch. 8 - Community Federal Bank in Dothan, Alabama,...Ch. 8 - The number of heart surgeries performed at...Ch. 8 - The following data are for calculator sales in...Ch. 8 - Prob. 14PCh. 8 - Forrest and Dan make boxes of chocolates for which...Ch. 8 - The manager of Alaina’s Garden Center must make...Ch. 8 - The manager of a utility company in the Texas...Ch. 8 - Franklin Tooling, Inc., manufactures specialty...Ch. 8 - Create an Excel spreadsheet on your own that can...Ch. 8 - Prob. 20PCh. 8 - Using the data in Problem 20 and the Time-Series...Ch. 8 - Prob. 22PCh. 8 - Cannister, Inc., specializes in the manufacture of...Ch. 8 - The Midwest Computer Company serves a large number...Ch. 8 - A certain food item at P=0.20 (with a combination...Ch. 8 - Prob. 26PCh. 8 - Prob. 27PCh. 8 - A manufacturing firm seeks to develop a better...Ch. 8 - How much does the forecasting process at Deckers...Ch. 8 - Prob. 2VCCh. 8 - What factors make forecasting at Deckers...Ch. 8 - Prob. 4VCCh. 8 - Prob. 5VCCh. 8 - Comment on the forecasting system being used by...Ch. 8 - Develop your own forecast for bow rakes for each...
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- 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?arrow_forwardThe 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?arrow_forwardThe 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?arrow_forward
- 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?arrow_forwardThe following table shows predicted product demand using your particular forecasting method along with the actual demand that occurred: FORECAST ACTUAL 1,515 1,585 1,415 1,515 1,715 1,615 1,755 1,680 1,805 1,730 Compute the tracking signal of each period using the mean absolute deviation and running sum of forecast errors.arrow_forwardBased on the following equation for a moving average forecast, what would have been the three week moving average forecast for week 53 for Small Town Restaurant (see downloaded file for actual demand)? Provide two decimal places and use normal rounding. What happens if we increase the time periods in our moving average forecast to six weeks opposed to three? Group of answer choices It would be more accurate because it includes more data. There would be no change. It would be less sensitive to changes. It would be better at predicting a trend.arrow_forward
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