Ch.12 Demand Planning Forecasting and Complete Test Bank 4e - Managing Operations Supply Chain 4e Complete Test Bank by Morgan Swink. DOCX document preview.
Chapter 12 Test Bank
Multiple Choice Questions
1. The primary difference between demand management and demand forecasting is:
A. Forecasting is only possible when quantitative data are available.
B. Demand management is proactive, while forecasting attempts to predict.
C. A firm cannot execute both approaches simultaneously.
D. One approach deals with uncertainty, while the other deals with known demand.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-02 Differentiate between demand planning, demand forecasting, and demand management activities.
Topic: Demand Planning: An Overview
2. Strategic demand planning would best be utilized:
A. To direct day-to-day operations in a manufacturing plant.
B. To determine plans for employee overtime.
C. To decide whether or not to close a manufacturing plant.
D. To determine plans for hiring or laying off employees.
E. All answers are correct.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-01 Explain the role of demand planning in operations management, in the firm, and in the supply chain.
Topic: Demand Planning: An Overview
3. The demand for housing is characterized by a regular pattern of increasing to a peak, then falling. When the demand reaches a low point, it then repeats the pattern. This pattern usually takes place over a three- to five-year period. This is an example of which type of demand pattern?
A. Autocorrelation
B. Seasonality and cycles
C. Step change
D. Trend
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures.
Topic: Demand Forecasting
4. Suppose your firm is about to launch a radically new product. The type of demand forecasting system you would most likely use is:
A. Regression.
B. Executive judgment.
C. Time series.
D. Moving average.
E. Exponential smoothing.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures.
Topic: Demand Forecasting
5. An office manager forecasts demand for office stationery by exponential smoothing, with alpha = 0.4. Actual demand two weeks ago (i.e., the week before last) was 12 boxes, but the forecast for that period was only 10. Actual demand last week was seven. What was the forecast for last week?
A. 10.8
B. 11.0
C. 11.2
D. 8.2
E. 8.8
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
6. For Platinum Nugget Hotel in Las Vegas, Saturday is the best day of the week for business. The gambling take for the hotel on Saturdays over the past four weeks was:
Week $Take
1. $250,000
2. $190,000
3. $300,000
4. $280,000
Using a moving average with n = 3 terms, what would be the forecast for week 5?
A. $256,667
B. $246,667
C. $255,000
D. $232,124
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
7. For Platinum Nugget Hotel in Las Vegas, Saturday is the best day of the week for business. The gambling take for the hotel on Saturdays over the past four weeks was:
Week $Take
1. $250,000
2. $190,000
3. $300,000
4. $280,000
Platinum Nugget uses a three-period weighted moving average to forecast demand, with a t = 0.6, at−1 = 0.3, and at−2 = 0.1. What is the forecast for week 5?
A. $232,000
B. $237,000
C. $277,000
D. $295,000
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
8. Alpha Company sold 2,000 widgets yesterday. It had forecasted sales of 1,900 units. Using exponential smoothing with a smoothing constant of 0.6, what is the forecast for today's sales of widgets?
A. 2,060
B. 1,940
C. 2,040
D. 1,960
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
9. Jones Company had sales of $100,000 last week. The company had forecasted that sales would be $120,000. Using exponential smoothing with a smoothing constant of 0.2, what is the forecast for this week's sales?
A. $124,000
B. $116,000
C. $104,000
D. $112,000
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
10. Over a six-month period, the demand for a product has been: June = 200, July = 210, August = 240, September = 240, October = 260, and November = 280. The three-month moving average forecast for December is:
A. 240.
B. 260.
C. 280.
D. 300.
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
11. Convex Computer Company makes many different forecasts. Which of the following forecasts is probably the least accurate?
A. Total number of computers (laptops and desktops) to be sold next month.
B. Total number of laptops to be sold next month.
C. Total number of desktops to be sold next year.
D. Total number of laptops with 2 gigabyte RAM, 80 gigabyte hard drive, and 16x DVD drive to be sold next year.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias.
Topic: Assessing the Performance of the Forecasting Process
12. A company has the information shown in the chart below regarding its forecast performance in the past three periods.
Period | Actual Demand | Forecast Demand | Error | Absolute Value of Error | ||
1 | 800 | 1,100 |
|
| 300 |
|
2 |
| 1,000 | 200 |
|
|
|
3 | 1,400 |
| −100 |
|
|
|
What is the mean absolute deviation (MAD)?
A. 200
B. 225
C. −66.67
D. 1,200
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias.
Topic: Assessing the Performance of the Forecasting Process
13. Given the data below, what is the bias of these forecasts?
Period | Actual Demand | Forecast Demand | Error | Absolute Value of Error | ||
1 | 800 | 1,100 |
|
| 300 |
|
2 |
| 1,000 | 200 |
|
|
|
3 | 1,400 |
| −100 |
|
|
|
A. Positive.
B. Negative.
C. There is no bias.
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias.
Topic: Assessing the Performance of the Forecasting Process
14. Designing postponable products has the potential to allow operations managers to:
A. Ignore forecasts.
B. Move from build-to-stock to assemble or make-to-order operations.
C. Influence the timing of demand.
D. All the items are correct.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-06 Explain how certain improvements to both product design and operations across the supply chain can make demand planning easier.
Topic: Improving the Constraints on Demand Planning
15. In recent years some companies have begun to work closely with their customers and/or suppliers by sharing information to develop demand plans and execute those plans. The procedure they are following is known as:
A. Coordinated foreplanning of requirements.
B. Joint planning of demand forecasts.
C. Collaborative planning, forecasting, and replenishment.
D. Conjoint analysis and forecasting.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-06 Explain how certain improvements to both product design and operations across the supply chain can make demand planning easier.
Topic: Improving the Constraints on Demand Planning
16. Assume that the forecast for the last period is FITt = 200 units, and recent experience suggests a likely sales increase of 10 units each period. Actual sales for the last period reached 230 units. Assuming a smoothing coefficient of α = 0.20 and a trend smoothing coefficient of β = 0.10, what is the BASE forecast for the next period?
A. 210
B. 206
C. 236
D. 226
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
17. Assume that the forecast for the last period is FITt = 200 units, and recent experience suggests a likely sales increase of 10 units each period. Actual sales for the last period reached 230 units. Assume a smoothing coefficient of α = 0.20 and a trend smoothing coefficient of β = 0.10. What is the ADJUSTED forecast for the next period?
A. 210.0
B. 210.6
C. 216.6
D. 216.0
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
18. Assume that the forecast for the last period is FITt = 200 units, and recent experience suggests a likely sales increase of 10 units each period. Actual sales for the last period reached 230 units. Assume a smoothing coefficient of α = 0.20 and a trend smoothing coefficient of β = 0.10. Demand in period t + 1 turned out to be 220. What is the adjusted forecast for period t + 2? (Choose the closest answer.)
A. 227.3
B. 215.9
C. 217.3
D. 221.3
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
19. Zanda Corp. has experienced demand in the last four years as shown below.
| Period (t) | Demand (dt) | t*dt | t2 |
| 1 | 20 | 20 | 1 |
| 2 | 30 | 60 | 4 |
| 3 | 32 | 96 | 9 |
| 4 | 38 | 152 | 16 |
Total | 10 | 120 | 328 | 30 |
Average | 2.5 | 30 |
|
|
What is the trend value (b) in the data? (Choose the closest answer.)
A. 5.6 units/period
B. 2.5 units/period
C. 2.87 units/period
D. −1.25 units/period
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
20. Refer to the data below for Zanda Corp. What is the linear regression forecast for period 5? (Choose the nearest number of whole units.)
| Period (t) | Demand (dt) | t*dt | t2 |
| 1 | 20 | 20 | 1 |
| 2 | 30 | 60 | 4 |
| 3 | 32 | 96 | 9 |
| 4 | 38 | 152 | 16 |
Total | 10 | 120 | 328 | 30 |
Average | 2.5 | 30 |
|
|
A. 44
B. 42
C. 34
D. 28
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
21. Jones Corp. has noticed that sales of its product seem to be related to a variable it calls Gamma. It has developed the data shown below.
| Gamma | Sales | Gamma × Sales | Gamma2 |
| 10 | 22 | 220 | 100 |
| 18 | 34 | 612 | 324 |
| 14 | 26 | 364 | 196 |
| 14 | 30 | 420 | 196 |
| 12 | 24 | 288 | 144 |
Total |
|
| 1,904 | 960 |
Average | 13.6 | 27.2 |
|
|
Develop a simple linear regression from the data and tell Jones what the sales forecast will be if Jones expects Gamma to be 16. (Round your forecast to the nearest number of whole units.)
A. 31
B. 33
C. 28
D. 34
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
22. Use the data below and the regression model.
| Gamma | Sales | Gamma × Sales | Gamma2 |
| 10 | 22 | 220 | 100 |
| 18 | 34 | 612 | 324 |
| 14 | 26 | 364 | 196 |
| 14 | 30 | 420 | 196 |
| 12 | 24 | 288 | 144 |
Total |
|
| 1,904 | 960 |
Average | 13.6 | 27.2 |
|
|
What is the sales forecast if Gamma is expected to be 21? (Round your forecast to the nearest number of whole units.)
A. 42
B. 36
C. 48
D. 39
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
23. A company uses actual demand data to develop its seasonal indices. It has the data shown below for each quarter of the previous two years.
Quarter | 1 | 2 | 3 | 4 | 1 | 2 | 3 | 4 |
Demand | 50 | 60 | 90 | 80 | 60 | 70 | 100 | 90 |
What is the seasonal index for Quarter 1?
A. 0.714
B. 0.750
C. 1.25
D. 0.732
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
24. Use the data below.
Quarter | 1 | 2 | 3 | 4 | 1 | 2 | 3 | 4 |
Demand | 50 | 60 | 90 | 80 | 60 | 70 | 100 | 90 |
A company has forecasted next year's demand to be 400. What is the seasonally adjusted forecast for Quarter 1? (Choose the closest answer.)
A. 75
B. 71
C. 125
D. 73
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
25. A company has the data shown in the chart below concerning its forecast performance over the past four time periods.
Period | Actual Demand | Forecast | Error | Absolute Value of Error | Absolute Percentage Error |
1 | 345 | 320 | 25 |
|
|
2 | 320 |
| 10 |
|
|
3 | 335 | 350 |
|
|
|
4 |
| 340 | −30 |
|
|
5 |
| 350 | 20 |
|
|
Complete the chart and compute the MAD.
A. 2
B. 20
C. 10
D. 100
Period | Actual Demand | Forecast | Error | Absolute Value of Error | Absolute Percentage Error |
1 | 345 | 320 | 25 | 25 | 25/345 = 7.25% |
2 | 320 | 310 | 10 | 10 | 10/320 = 3.13% |
3 | 335 | 350 | −15 | 15 | 15/335 = 4.48% |
4 | 310 | 340 | −30 | 30 | 30/310 = 9.68% |
5 | 370 | 350 | 20 | 20 | 20/370 = 5.41% |
|
|
| MFE = 10/5 = 2 | MAD = 100/5 = 20 | MAPE = 29.95%/5 = 5.99% |
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
26. Using the data below, determine the MAPE.
Period | Actual Demand | Forecast | Error | Absolute Value of Error | Absolute Percentage Error |
1 | 345 | 320 | 25 |
|
|
2 | 320 |
| 10 |
|
|
3 | 335 | 350 |
|
|
|
4 |
| 340 | −30 |
|
|
5 |
| 350 | 20 |
|
|
A. 5.0 percent
B. 7.25 percent
C. 5.99 percent
D. 5.41 percent
Period | Actual Demand | Forecast | Error | Absolute Value of Error | Absolute Percentage Error |
1 | 345 | 320 | 25 | 25 | 25/345 = 7.25% |
2 | 320 | 310 | 10 | 10 | 10/320 = 3.13% |
3 | 335 | 350 | −15 | 15 | 15/335 = 4.48% |
4 | 310 | 340 | −30 | 30 | 30/310 = 9.68% |
5 | 370 | 350 | 20 | 20 | 20/370 = 5.41% |
|
|
| MFE = 10/5 = 2 | MAD = 100/5 = 20 | MAPE = 29.95%/5 = 5.99% |
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias.
Topic: Assessing the Performance of the Forecasting Process
27. In examining the data below, the manager exclaimed that he was very happy to see no bias in the forecasts. How would you respond to the manager?
Period | Actual Demand | Forecast | Error | Absolute Value of Error | Absolute Percentage Error |
1 | 345 | 320 | 25 |
|
|
2 | 320 |
| 10 |
|
|
3 | 335 | 350 |
|
|
|
4 |
| 340 | −30 |
|
|
5 |
| 350 | 20 |
|
|
A. You are correct.
B. I'm sorry, but there is a slight negative bias.
C. I'm sorry, but there appears to be a slight positive bias.
D. There is no way to estimate bias with the given information.
Period | Actual Demand | Forecast | Error | Absolute Value of Error | Absolute Percentage Error |
1 | 345 | 320 | 25 | 25 | 25/345 = 7.25% |
2 | 320 | 310 | 10 | 10 | 10/320 = 3.13% |
3 | 335 | 350 | −15 | 15 | 15/335 = 4.48% |
4 | 310 | 340 | −30 | 30 | 30/310 = 9.68% |
5 | 370 | 350 | 20 | 20 | 20/370 = 5.41% |
|
|
| MFE = 10/5 = 2 | MAD = 100/5 = 20 | MAPE = 29.95%/5 = 5.99% |
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias.
Topic: Assessing the Performance of the Forecasting Process
28. Zanda Corp. has been testing the performance of two different forecasting models to see which it should adopt for use. It wants to choose the model that has the smaller standard deviation of the forecast errors. Zanda should compare which of the following to make its choice?
A. MAD of the two models
B. MAPE of the two models
C. RMSE of the two models
D. MFE of the two models
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias.
Topic: Assessing the Performance of the Forecasting Process
29. The tracking signal will suggest to a manager that:
A. Demand for an item is changing.
B. There is seasonality in demand.
C. A forecast mode's parameters may need adjustment.
D. All the answers are correct.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias.
Topic: Assessing the Performance of the Forecasting Process
30. A forecasting system that changes the value of the alpha parameter in response to the level of forecast error is known as:
A. A tracking signal.
B. A trend-enhanced exponential smoothing model.
C. A causal regression.
D. A time series model.
E. An adaptive model.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias.
Topic: Assessing the Performance of the Forecasting Process
31. Long-term/strategic demand planning is typically done using what units?
A. Total business unit sales
B. Total product family sales
C. Total product item sales
D. Sales at a given location
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-01 Explain the role of demand planning in operations management, in the firm, and in the supply chain.
Topic: Demand Planning: An Overview
32. What is the relationship between demand management and demand forecasting?
A. The two planning activities are managed independently.
B. Demand management plans are usually an input to demand forecasting.
C. Demand management is done by operations managers, while demand forecasting is done by marketing managers.
D. All the answers are correct.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-02 Differentiate between demand planning, demand forecasting, and demand management activities.
Topic: Demand Planning: An Overview
33. Which of the following factors should be considered when one designs a forecasting process?
A. Time horizon for planning.
B. Level of detail for planning.
C. Availability of data.
D. All the answers are correct.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures.
Topic: Demand Forecasting
34. A forecasting technique that seeks inputs from people who are in close contact with customers is known as:
A. Historical analogy.
B. Focused forecasting.
C. Grassroots forecasting.
D. Marketing research.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures.
Topic: Demand Forecasting
35. How does product design affect forecasting accuracy?
A. Postponable product designs remove the need to forecast demand for final product configurations.
B. A popular product design improves the demand volume and forecast.
C. Forecast accuracy is not related to product design.
D. None of the statements are true.
AACSB: Reflective thinking
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Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-06 Explain how certain improvements to both product design and operations across the supply chain can make demand planning easier.
Topic: Improving the Constraints on Demand Planning
36. A computer program that uses algorithms to learn by analyzing many different types of models applied to large amounts of data is called:
A. Historical analogy.
B. Focused forecasting.
C. Artificial intelligence.
D. Algorithmic modeling.
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures.
Topic: Demand Forecasting
37. Which of the following statements best describes demand forecasting?
A. The objective of forecasting is to develop the best statistical model.
B. Better forecasts usually come from combinations of inputs.
C. Executives usually make better forecasts than machines.
D. Forecasting and demand planning have little to do with each other.
AACSB: Reflective thinking
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Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures.
Topic: Demand Forecasting
38. Which of the following statements most accurately describes the outcome of using a simple moving average model to forecast demand that has a strong trend?
A. Using more periods in the moving average calculation will produce better forecasts.
B. Moving average models require less historical data than exponential smoothing models.
C. Moving averages must be weighted in order to accurately predict a trend.
D. Changes in forecasts produced by a moving average model will lag behind changes in demand.
AACSB: Reflective thinking
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Accessibility: Screen Reader Compatible
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures.
Topic: Demand Forecasting
39. Apply regression to the data shown below. The slope of the line estimated using the regression model is:
| Sales |
January | 100 |
February | 200 |
March | 150 |
April | 400 |
May | 300 |
June | 200 |
July | 250 |
August | 350 |
September | 400 |
October | 350 |
November | 400 |
December | 500 |
A. 50.0
B. 45.3
C. 27.3
D. 15.4
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
40. Apply regression to the data shown below. The forecast for next January's sales is:
| Sales |
January | 100 |
February | 200 |
March | 150 |
April | 400 |
May | 300 |
June | 200 |
July | 250 |
August | 350 |
September | 400 |
October | 350 |
November | 400 |
December | 500 |
A. 150.0
B. 477.3
C. 450.0
D. Not enough information is given to make a forecast
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
41. Using an exponential smoothing model, the forecast for next January’s sales is:
| Sales |
January | 100 |
February | 200 |
March | 150 |
April | 400 |
May | 300 |
June | 200 |
July | 250 |
August | 350 |
September | 400 |
October | 350 |
November | 400 |
December | 500 |
A. 150.0
B. 477.3
C. 450.0
D. Not enough information is given to make a forecast
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
42. Using the data shown below, the forecast for week 5 using a three-period moving average model is:
Week | 1 | 2 | 3 | 4 |
Sales | 165 | 140 | 115 | 200 |
A. 200
B. 155
C. 152
D. 158
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
43. Using the data shown below, the forecast for week 5 using an exponential smoothing model is:
Week | 1 | 2 | 3 | 4 |
Sales | 165 | 140 | 115 | 200 |
Forecast | 170 | 168 |
| 140.1 |
A. 164.1
B. 146.1
C. 200.1
D. Not enough information is given to produce a forecast
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
44. Increasing the value of alpha (α) in an exponential smoothing model would produce which of the following results?
A. Reduce the influence of more recent demands in computing future forecasts
B. Reduce the amount of data that needs to be stored to support the forecasting process
C. Increase the sensitivity of the forecast process to recent changes in demand
D. Reduce the ability of the forecast process to respond to seasonality in demand
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
45. Given a demand of 19 for the most recent period, use α = .2 and β =.4 to create a trend-enhanced smoothing-based forecast. Assume that FIT1 = 22 and T1 = 7.83. The correct answer is closest to:
A. 29.0
B. 21.4
C. 23.2
D. 31.3
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
46. The data below show the forecasted probability of rain on Election Day and the actual number of people who voted in the election for each of the past eight years in a given city. If tomorrow is Election Day and the weather forecast shows a 50 percent chance of rain, how many voters do you expect to turn out?
Years in the past | 8 | 7 | 6 | 5 | 4 | 3 | 2 | 1 |
probability of rain (%) | 10 | 15 | 0 | 80 | 15 | 25 | 0 | 90 |
Number of voters (100s) | 20 | 25 | 40 | 15 | 20 | 10 | 35 | 10 |
A. 28.3
B. 20.0
C. 17.4
D. 75.2
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
47. Demand planning for the intermediate term (tactical plans) would be done using dollar or unit sales for:
A. A business unit
B. An entire sales network
C. A product family in a region
D. A particular item at a given location
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-01 Explain the role of demand planning in operations management, in the firm, and in the supply chain.
Topic: Demand Planning: An Overview
48. Which of the following is not typically considered a component driver of demand?
A. Seasonality
B. Trend
C. Perturbation
D. Autocorrelation
AACSB: Reflective thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Remember
Difficulty: 1 Easy
Gradable: automatic
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures.
Topic: Demand Forecasting
49. The table below shows quarterly sales data over four years. A regression of sales on quarters yields this equation: Sales = 18.25 + 1.55 × Quarter number. Using the regression estimate as the base, what is the seasonal index for the fourth quarter? (Pick the answer that is closest to the correct number.)
| Year |
|
| |
Quarter | 1 | 2 | 3 | 4 |
1 | 15 | 26 | 17 | 24 |
2 | 17 | 29 | 20 | 24 |
3 | 15 | 24 | 13 | 22 |
4 | 25 | 30 | 23 | 30 |
A. 1.10
B. 1.23
C. 1.04
D. 0.81
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Analyze
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
50. The table below shows quarterly sales data over four years. Using the average demand as the base, what is the seasonal index for the third quarter (Pick the answer that is closest to the correct number.)
| Year |
|
| |
Quarter | 1 | 2 | 3 | 4 |
1 | 15 | 26 | 17 | 24 |
2 | 17 | 29 | 20 | 24 |
3 | 15 | 24 | 13 | 22 |
4 | 25 | 30 | 23 | 30 |
A. 0.92
B. 0.82
C. 0.99
D. 1.20
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Blooms: Apply
Difficulty: 3 Hard
Gradable: automatic
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models.
Topic: Demand Forecasting
51. The city of Dallas would like to control the amount of traffic on a major tollway. One way to manage the demand is by:
A. Rapid forecasting.
B. Dynamic pricing.
C. Signaling alternatives.
D. Opening and closing lanes.
AACSB: Analytical Thinking
Accessibility: Keyboard Navigation
Accessibility: Screen Reader Compatible
Blooms: Understand
Difficulty: 2 Medium
Gradable: automatic
Learning Objective: 12-02 Differentiate between demand planning, demand forecasting, and demand management activities.
Topic: Demand Management
Chapter 12 Test Bank - Static Summary
Category | # of Questions |
AACSB: Reflective thinking | 20 |
AACSB: Analytical Thinking | 31 |
Accessibility: Keyboard Navigation | 51 |
Accessibility: Screen Reader Compatible | 32 |
Blooms: Analyze | 11 |
Blooms: Apply | 19 |
Blooms: Remember | 9 |
Blooms: Understand | 12 |
Difficulty: 1 Easy | 9 |
Difficulty: 2 Medium | 13 |
Difficulty: 3 Hard | 29 |
Gradable: automatic | 51 |
Learning Objective: 12-01 Explain the role of demand planning in operations management, in the firm, and in the supply chain. | 3 |
Learning Objective: 12-02 Differentiate between demand planning, demand forecasting, and demand management activities. | 3 |
Learning Objective: 12-03 Describe various qualitative and quantitative demand forecasting procedures. | 8 |
Learning Objective: 12-04 Develop forecasts using moving average, exponential smoothing, and linear regression models. | 26 |
Learning Objective: 12-05 Evaluate and select forecasting models using various measures of accuracy and bias. | 8 |
Learning Objective: 12-06 Explain how certain improvements to both product design and operations across the supply chain can make demand planning easier. | 3 |
Topic: Assessing the Performance of the Forecasting Process | 8 |
Topic: Demand Forecasting | 34 |
Topic: Demand Management | 1 |
Topic: Demand Planning: An Overview | 5 |
Topic: Improving the Constraints on Demand Planning | 3 |
Document Information
Connected Book
Managing Operations Supply Chain 4e Complete Test Bank
By Morgan Swink