Operations and Supply Chain Management 9th edition
9th Edition
ISBN: 9781119320975
Author: Roberta S. Russell, Bernard W. Taylor III
Publisher: WILEY
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Textbook Question
Chapter 12, Problem 11Q
In the chapter examples for time series methods, the starting
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Consider the following actual and forecast demand levels for Big Mac hamburgers at a local McDonald's restaurant:
Day Actual Demand Forecast Demand
Monday 90.00 90.00
Tuesday 73.00 90.00
Wednesday 66.00 85.75
Thursday 50.00 80.81
Friday - ?
The forecast for Monday was derived by observing Monday's demand level and setting Monday's forecast level equal to this demand level. Subsequent forecasts were derived by using exponential smoothing with a smoothing constant of 0.25. Using this exponential smoothing method, the forecast for Big Mac demand for Friday is _____ Big Macs (round your response to one decimal place).
Harlen Industries has a simple forecasting model: Take the actual demand for the same month last year and divide that by the number of fractional weeks in that month. This gives the average weekly demand for that month. This weekly average is used as the weekly forecast for the same month this year. This technique was used to forecast eight weeks for this year, which are shown in the following tables along with the actual demand that occurred.
WEEK
FORECAST DEMAND
ACTUAL DEMAND
1
140
137
2
140
133
3
140
150
4
140
160
5
140
180
6
150
170
7
150
185
8
150
205
Compute the MAD of forecast errors.
Note: Round your answers to 2 decimal places.
Using the RSFE, compute the tracking signal.
Note: Negative values should be indicated by a minus sign. Round your answer to 2 decimal places.
Based on your answers to parts a and b, comment on Harlen’s method of forecasting.
multiple choice
The forecast should be considered poor.
The forecast should be…
Harlen Industries has a simple forecasting model: Take the actual demand for the same month last year and divide that by the number
of fractional weeks in that month. This gives the average weekly demand for that month. This weekly average is used as the weekly
forecast for the same month this year. This technique was used to forecast eighnt weeks for this year, which are shown below along
with the actual demand that occurred.
The following eight weeks show the forecast (based on last year) and the demand that actually occurred:
ITT
FORECAST
ACTUAL
WEEK
DEMAND
DEMAND
130
1
127
2
130
123
3
146
149
4
144
159
5
146
179
156
169
150
184
145
205
a. Compute the MAD of forecast errors. (Round your answers to 2 decimal places.)
Week
MAD
1
2
4
7
b. Using the RSFE, compute the tracking signal. (Round your answers to 2 decimal places. Negative values should be Indicated by a
mlnus sign.)
Tracking
Week
Signal
1
2
4
7
8
c. Based on your answers to parts a and b, comment on Harlen's method of…
Chapter 12 Solutions
Operations and Supply Chain Management 9th edition
Ch. 12 - List some of the operations and functions in a...Ch. 12 - What is the difference between quantitative...Ch. 12 - Describe the difference between short- and...Ch. 12 - Prob. 4QCh. 12 - Why is accurate forecasting so important to...Ch. 12 - Discuss the relationship between forecasting and...Ch. 12 - Prob. 7QCh. 12 - Describe the Delphi method for forecasting.Ch. 12 - What is the difference between a trend and a cycle...Ch. 12 - How is the moving average method similar to...
Ch. 12 - In the chapter examples for time series methods,...Ch. 12 - What effect on the exponential smoothing model...Ch. 12 - How does adjusted exponential smoothing differ...Ch. 12 - What determines the choice of the smoothing...Ch. 12 - How does the linear trend line forecasting model...Ch. 12 - Of the time series models presented in this...Ch. 12 - What advantages does adjusted exponential...Ch. 12 - Describe how a forecast is monitored to detect...Ch. 12 - Explain the relationship between the use of a...Ch. 12 - Selecting from MAD, MAPD, MSE, E, and E, which...Ch. 12 - What is the difference between linear and multiple...Ch. 12 - Define the different components (y, x, a, and b)...Ch. 12 - A company that produces video equipment, including...Ch. 12 - The Hartley-Davis motorcycle dealer in the...Ch. 12 - The manager of the I-85 Carpet Outlet needs to be...Ch. 12 - The LawnPlus Fertilizer Company distributes...Ch. 12 - Graph the demand data in Problem 12.3. Can you...Ch. 12 - The chairperson of the department of management at...Ch. 12 - The manager of the Excom Service Station wants to...Ch. 12 - The Intrepid mutual fund of growth stocks has had...Ch. 12 - The Oceanside Hotel is adjacent to City Coliseum,...Ch. 12 - Mary Hernandez has invested in a stock mutual fund...Ch. 12 - Globetron manufactures components for use in small...Ch. 12 - The Bee Line Caf is well known for its popular...Ch. 12 - For the demand data in Problem 12.11, develop a...Ch. 12 - Develop a seasonally adjusted forecast for the...Ch. 12 - Backstreets Pizza delivery service has randomly...Ch. 12 - The Willow River Mining Company mines and ships...Ch. 12 - The Great Northwest Outdoor Company is a catalog...Ch. 12 - Townside Food Vending operates vending machines in...Ch. 12 - The town aquatic center has an indoor pool that...Ch. 12 - Develop an adjusted exponential smoothing forecast...Ch. 12 - During the past five months the emergency room at...Ch. 12 - At its craft store and through its website, the...Ch. 12 - A group of business students at Tech organized a...Ch. 12 - Temco Industries has developed a forecasting model...Ch. 12 - Monitor the forecast in Problem 12.23 for bias...Ch. 12 - Develop a statistical control chart for the...Ch. 12 - Monitor the adjusted exponential smoothing...Ch. 12 - Develop an exponential smoothing forecast with =...
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Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, operations-management and related others by exploring similar questions and additional content below.Similar questions
- 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?arrow_forwardThe 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.arrow_forwardThe 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_forward
- 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?arrow_forwardThe 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?arrow_forwardThe 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?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_forwardUnder what conditions might a firm use multiple forecasting methods?arrow_forwardThe file P13_19.xlsx contains the weekly sales of a particular brand of paper towels at a supermarket for a one-year period. a. Using a span of 3, forecast the sales of this product for the next 10 weeks with the moving averages method. How well does this method with span 3 forecast the known observations in this series? b. Repeat part a with a span of 10. c. Which of these two spans appears to be more appropriate? Justify your choice.arrow_forward
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