Operations Management 6Th Canadian Edition By William

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Sample Test

Chapter 03

Demand Forecasting

True / False Questions

1. Since a primary goal of operations management is to match supply to demand, forecasts become a basic input to the decision process because they provide information on past demand.
FALSE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-01 Introduced forecasting; identify uses of demand forecastes; distinguish between forecasting time frames; describe common features of forecasts; list the elements of good forecast and steps of the forecasting process; and contrast different forecasting methods.
Topic: 03-01 Introduction

2. Forecasting techniques generally assume that the same causal system that existed in the past will continue to exist in the future.
TRUE

3. Forecasts are rarely perfect.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-01 Introduced forecasting; identify uses of demand forecastes; distinguish between forecasting time frames; describe common features of forecasts; list the elements of good forecast and steps of the forecasting process; and contrast different forecasting methods.
Topic: 03-02 Features Common to All Forecasts

4. Generally the responsibility for preparing demand forecasts for finished goods or services lies with operations rather than marketing or sales departments.
FALSE

5. Forecasts for groups of items tend to be less accurate than forecasts for individual items because forecasts for individual items are not subject to as many influencing factors.
FALSE

6. Organizations that are capable of responding quickly to changing requirements can use a shorter forecast horizon and therefore benefit from more accurate forecasts.
TRUE

7. Forecast accuracy tends to increase as the time horizon increases.
FALSE

8. The purpose of the forecast should be established first so that the level of detail, amount of resources, and accuracy level can be indicated.
TRUE

9. Time series techniques involve identification of explanatory variables that can be used to predict future demand.
FALSE

Accessibility: Keyboard Navigation
Difficulty: Hard
Learning Objective: 03-01 Introduced forecasting; identify uses of demand forecastes; distinguish between forecasting time frames; describe common features of forecasts; list the elements of good forecast and steps of the forecasting process; and contrast different forecasting methods.
Topic: 03-05 Approaches to Forecasting

10. A consumer survey is an easy and sure way to obtain direct input from existing customers.
FALSE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-06 Judgmental Methods

11. The Delphi approach involves the use of a series of questionnaires to achieve a consensus forecast.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-11 Expert Opinions

12. Forecasts based on time series (historical) data are referred to as associative forecasts.
FALSE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-03 Describe the components of a time series model; explain averaging techniques; and solve typical problems.
Topic: 03-05 Approaches to Forecasting

13. As a forecasting technique, the Delphi technique is useful for technological forecasting.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-11 Expert Opinions

14. One weakness of the Delphi method is that there is a high risk that one person’s opinion will prevail.
FALSE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-11 Expert Opinions

15. Forecasting techniques that are based on time series data assume that future values of the series will duplicate past values.
FALSE

16. The primary difference between irregular and random variations is the ability to attribute variations to a specific cause.
TRUE

17. Increasing the number of data points included in a moving average will result in a forecast that is smoother but less responsive to changes.
TRUE

18. The naive approach to forecasting requires a linear trend line.
FALSE

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-03 Describe the components of a time series model; explain averaging techniques; and solve typical problems.
Topic: 03-14 Naïve Methods

19. The naive forecast is limited in its application to series that reflect no trend or seasonality.
FALSE

20. The naive forecast can serve as a standard of comparison against which to judge the cost and accuracy of other techniques.
TRUE

21. A moving average forecast tends to be more responsive to changes in the data series when more data points are included in the average.
FALSE

22. In order to update a moving average forecast, the values of each data point in the average must be known.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Hard
Learning Objective: 03-03 Describe the components of a time series model; explain averaging techniques; and solve typical problems.
Topic: 03-15 Averaging Methods

23. A simple moving average assigns equal weight to each data point that is represented by the average.
TRUE

24. An advantage of a weighted moving average is that more recent experience is given more weight than less recent experience.
TRUE

25. Exponential smoothing is a form of weighted averaging.
TRUE

26. A smoothing constant of .1 will cause an exponential smoothing forecast to react more quickly to a sudden change than a value of .3 will.
FALSE

27. In exponential smoothing, an alpha of .30 will cause a forecast to react more quickly to a large error than will an alpha of .20.
TRUE

28. Trend-Adjusted Exponential Smoothing is also called double exponential smoothing.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-04 Describe trend forecasting and solve typical problems.
Topic: 03-18 Trend-Adjusted Exponential Smoothing

29. Trend adjusted exponential smoothing requires selection of two smoothing constants.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-04 Describe trend forecasting and solve typical problems.
Topic: 03-18 Trend-Adjusted Exponential Smoothing

30. An advantage of “trend adjusted exponential smoothing” over the “linear trend equation” is its ability to adjust over time to changes in the trend.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-04 Describe trend forecasting and solve typical problems.
Topic: 03-18 Trend-Adjusted Exponential Smoothing

31. A seasonal relative (or seasonal indexes) is expressed as a percentage of the average or trend in a time series.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-05 Describe seasonality forecasting and solve typical problems using both the centred moving average and annual average methods.
Topic: 03-19 Techniques for Seasonality

32. In order to compute seasonal relatives, the trend of past data must be computed or known.
TRUE

33. Removing the seasonal component from a data series (deseasonalizing) can be accomplished by dividing each data point by its appropriate seasonal relative.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Hard
Learning Objective: 03-05 Describe seasonality forecasting and solve typical problems using both the centred moving average and annual average methods.
Topic: 03-19 Techniques for Seasonality

34. Centred moving averages (CMA) is a better way to compute seasonal relatives than using a simple moving average if there is a linear trend in a time series.
TRUE

35. Correlation measures the strength and direction of a relationship between variables.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-06 Describe associated models (regression) and solve typical problems.
Topic: 03-23 Correlation Coefficient

36. Multiple regression procedures permit us to extend associative models to relationships that involve more than one predictor variable.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-06 Describe associated models (regression) and solve typical problems.
Topic: 03-24 Multiple Regression

37. The forecast error is the difference between the actual value and the forecast value for a given period.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-07 Describe three measures of forecast accuracy and two ways of controlling forecastes; and solve typical problems.
Topic: 03-25 Accuracy and Control of Forecasting Process

38. Positive forecast errors, the case when the forecast is low relative to the actual value, are preferable to negative forecast errors, the case when the forecast is higher than the actual value
FALSE

39. MAD is equal to the square root of MSE.
FALSE

40. The MSE is the best measure to use in a control chart to monitor if forecast error is randomly distributed around a mean value of 0.
FALSE

41. The square root of MSE is used to estimate the sample standard deviation of forecast errors.
TRUE

42. A control chart involves setting control limits to monitor cumulative forecast error.
FALSE

43. The use of a control chart assumes that errors are normally distributed about a mean of zero.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Hard
Learning Objective: 03-07 Describe three measures of forecast accuracy and two ways of controlling forecastes; and solve typical problems.
Topic: 03-27 Controlling the Forecasting Process

44. When error values fall outside the limits of a control chart, this signals a need for corrective action
TRUE

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-07 Describe three measures of forecast accuracy and two ways of controlling forecastes; and solve typical problems.
Topic: 03-27 Controlling the Forecasting Process

45. Using control charts to monitor forecast error are best suited for forecasting applications involving a single forecast rather than applications involving a series of forecasts (e.g. monthly sales).
FALSE

46. A random pattern of errors within the limits of a control chart signals a need for corrective action.
FALSE

47. When all the forecast errors plotted on a control chart are either all positive, or all negative, this shows that the forecasting technique is performing adequately.
FALSE

48. The best forecast is always the one that is the most accurate.
FALSE

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-08 Identify the major factors to consider when choosing a forecasting technique.
Topic: 03-28 Choosing a Forecasting Technique

49. Moving average and exponential smoothing forecasting techniques are used for long range forecasts.
FALSE

Accessibility: Keyboard Navigation
Difficulty: Hard
Learning Objective: 03-08 Identify the major factors to consider when choosing a forecasting technique.
Topic: 03-28 Choosing a Forecasting Technique

50. A proactive approach to forecasting views forecasts as probable descriptions of future demand, assuming actions can be taken to meet that demand.
FALSE

51. A proactive approach to forecasts might involve advertising or other attempts to influence the demand level.
TRUE

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-08 Identify the major factors to consider when choosing a forecasting technique.
Topic: 03-29 Using Forecast Information

Multiple Choice Questions

52. Forecasts can help a manager to do all of the following EXCEPT:
A.reduce uncertainty in planning.
B. design the system.
C. plan the medium-term use of the system.
D. schedule the short-term use of the system.
E. predict the future precisely.

53. In operations, forecasts are the basis for all of the following EXCEPT:
A.capacity planning
B. project management
C. inventory planning
D. work assignments and workloads
E. pricing and promotion

Forecasts are used for all of the responses, however, specific to operations answer E does not apply. E relates to marketing use of forecasts.

54. All of the following are true about forecasts EXCEPT:
A.become less accurate with longer time horizons.
B. are less accurate for individual items than for groups of items.
C. are always perfect.
D. are usually the responsibility of operating managers to prepare.
E. assume the same underlying causal system in the future as the past.

55. Which would not generally be considered a feature common to all forecasts?
A.An assumption of a stable underlying causal system.
B. Actual results will differ somewhat from predicted values.
C. Historical data is available on which to base the forecast.
D. Forecasts for groups of items tend to be more accurate than forecasts for individual items.
E. Accuracy decreases as the time horizon increases.

56. Which of the following is not a step in the forecasting process?
A.Determine the purpose of the purpose.
B. Eliminate any assumptions and rely solely on verifiable factual data.
C. Establish a forecasting horizon.
D. Select a forecasting technique.
E. Monitor the forecast.

57. Which of the following is not part of determining the purpose of the forecast?
A.The level of detail required in the forecast
B. The amount of personnel that can be justified
C. The level of accuracy required
D. The forecasting time interval
E. The amount of dollars that can be justified

58. The two general approaches to forecasting are:
A.mathematical and statistical.
B. qualitative and quantitative.
C. judgmental and quantitative.
D. historical and associative.
E. judgmental and associative.

59. Which of the following is not necessarily an element of a good forecast?
A.The degree of accuracy is stated.
B. Time horizon long enough so forecast results can be used.
C. Expressed in meaningful units.
D. Low cost to complete.
E. Technique is simple to understand and use.

60. Which of the following is not a requirement of a properly prepared forecast?
A.Timely
B. Accurate
C. Reliable
D. Simple to understand and use
E. Inexpensive

61. Which of the following is not a type of judgmental forecasting?
A.Executive opinions
B. Sales force opinions
C. Consumer surveys
D. Expert opinions
E. Time series analysis

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-06 Judgmental Methods

62. Which of the following steps is considered the last step in the forecasting process?
A.Gather and analyze relevant historical data.
B. Determine the purpose of the forecast.
C. Monitor the forecast.
D. Prepare the forecast.
E. Establish a time horizon.

63. Which of the following would be an advantage of using opinions of a sales force to develop a demand forecast?
A.The sales staff is least affected by changing customer needs.
B. The sales force can easily distinguish between customer desires and probable actions.
C. The sales staff is often aware of customers’ future plans.
D. Salespeople are least likely to be influenced by recent events.
E. Salespeople are least likely to be biased by sales quotas.

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-08 Sales Force Opinions

64. Which phrase most closely describes the Delphi technique?
A.Associative forecast
B. Consumer survey
C. Series of questionnaires
D. Double smoothing
E. Historical data

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-11 Expert Opinions

65. A network security company is securing input from information technology managers trying to anticipate when Wi Fi networks might be available in at least half of their client’s businesses. Which method are they most likely to use?
A.The Delphi method
B. Consumer surveys
C. Regression models
D. Naive method
E. Trend models

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-06 Judgmental Methods

66. The forecasting method which uses anonymous questionnaires to achieve a consensus forecast is:
A.sales force opinions.
B. consumer surveys.
C. the Delphi method.
D. time series analysis.
E. executive opinions.

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-11 Expert Opinions

67. One reason for using the Delphi method in forecasting is:
A.responses are anonymous.
B. to achieve a high degree of accuracy.
C. to maintain accountability and responsibility.
D. to be able to replicate results.
E. the ability to directly meet with customers

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-02 Describe at least three judgmental forecasting methods.
Topic: 03-11 Expert Opinions

68. Time series data may exhibit all but which of the following behaviours?
A.Trend
B. Seasonality
C. Cycles
D. Irregularities
E. Identification of variables.

69. Persistent upward or downward movement in time series data is called:
A.seasonal variation.
B. cycles.
C. irregular variation.
D. trend.
E. random variation.

70. The primary difference between seasonality and cycles is:
A.the duration of the repeating patterns.
B. the magnitude of the variation.
C. the ability to attribute the pattern to a cause.
D. There is more forecasting “noise” in a cycle.
E. There is less forecasting “noise” in a cycle.

71. Averaging forecasting techniques are useful for:
A.distinguishing between random and non-random variations
B. forecasting cyclical time series
C. smoothing out fluctuations in data
D. forecasting seasonal indexes
E. identifying variables in the demand

72. Disadvantages of naive forecasts include:
A.time-consuming to prepare
B. it is expensive to use
C. the technique is difficult to understand
D. inability to provide highly accurate forecasts
E. time to develop a forecast is lengthy

73. Which of the following is not a characteristic of Naive forecasting methods
A.are quick and easy to prepare.
B. are easy for users to understand.
C. can serve as an accuracy standard for other techniques.
D. able to quickly identify changes in demand.
E. have virtually no cost.

74. Using the latest observation in a sequence of data to forecast the next period is:
A.a moving average forecast.
B. a naive forecast.
C. an exponentially smoothed forecast.
D. an associative forecast.
E. a judgmental forecast.

75. For the data given below, if the time series was assumed to be stable, what would the naive forecast be for the next period?

Period	Demand
1	58
2	61
3	60
4	61

59. 58
B. 62
C. 59.5
D. 61
E. 60.5

Stable series.

76. Given the following historical data, what is the simple three-period moving average forecast for period 6?

Period	Value	Period	Value
1	73	4	72
2	68	5	67
3	65

68. 67
B. 115
C. 69
D. 68
E. 68.67

77. Given the following historical data and weights of .5 for the most recent period, .3 for the next most recent, and .2 for the next after that, what is the weighted three-period moving average forecast for period 5?

Period	Value	Period	Value
1	138	3	148
2	142	4	144

144. 144.20
B. 144.80
C. 144.67
D. 143.00
E. 144.00

78. Moving average forecasting techniques:
A.immediately reflect changing patterns in the time series.
B. lead changes in the time series.
C. smooth variations in the time series.
D. exhibit more variability than the original data.
E. are best used when demand shows a steady increase.

79. Which is not a characteristic of simple moving averages applied to time series data?
A.Smooths random variations in the data
B. Weights each historical value equally
C. Lags changes in the data
D. Has minimal reliance on historical data
E. Smooths real variations in the data

80. In order to increase the responsiveness of a forecast made using the moving average technique, the number of data points in the average should be:
A.decreased.
B. increased.
C. multiplied by a larger alpha.
D. multiplied by a smaller alpha.
E. divided by alpha.

81. As compared to a simple moving average, the weighted moving average is:
A.easier to compute.
B. more reflective of the most recent periods.
C. smoother.
D. less reflective of the most recent periods.
E. more readily able to identify random variations.

82. A forecast based on the previous forecast plus a percentage of the forecast error is:
A.a naive forecast.
B. a simple moving average forecast.
C. a centred moving average forecast.
D. an exponentially smoothed forecast.
E. an associative forecast.

83. Which is not a characteristic of exponential smoothing?
A.Smooths random variations in the data
B. Weights each historical value equally
C. Provides an easily altered weighting scheme
D. Directly accounts for forecast error
E. Smooths real variations in the data

84. Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?
A.0
B. .01
C. 1
D. 5
E. 1.0

85. Simple exponential smoothing is being used to forecast demand. The previous forecast of 66 turned out to be 3 units less than actual demand. The next forecast is 66.6, implying a smoothing constant, alpha, equal to:
A.01
B. 10
C. 15
D. 20
E. 60

86. Given an actual demand of 57, a previous forecast of 62, and an alpha of .3, what would the forecast for the next period be using simple exponential smoothing?
A.36.9
B. 57.5
C. 60.5
D. 62.5
E. 65.5

87. Given an actual demand of 105, a predicted value of 97, and an alpha of .4, the simple exponential smoothing forecast for the next period would be:
A.80.8
B. 93.8
C. 100.2
D. 101.8
E. 108.2

88. Which of the following possible values of alpha would cause exponential smoothing to respond the most quickly to forecast errors?
A.0
B. .01
C. .05
D. .10
E. .15

89. A manager uses the following equation to predict monthly receipts: Yt = 40,000 + 150t. What is the forecast for December if t = 0 for the month of April?
A.40,050
B. 41,050
C. 41,200
D. 41,300
E. 41,500

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-04 Describe trend forecasting and solve typical problems.
Topic: 03-16 Techniques for Trend

90. In trend-adjusted exponential smoothing, the trend adjusted forecast (TAF) consists of:
A.an exponentially smoothed forecast and a smoothed trend factor.
B. an exponentially smoothed forecast and an estimated trend value.
C. the old forecast adjusted by a trend factor.
D. the old forecast and a smoothed trend factor.
E. a moving average and a trend factor.

Accessibility: Keyboard Navigation
Difficulty: Hard
Learning Objective: 03-04 Describe trend forecasting and solve typical problems.
Topic: 03-18 Trend-Adjusted Exponential Smoothing

91. In the “additive” model for seasonality, seasonality is expressed as a ______________ adjustment to the average; in the multiplicative model, seasonality is expressed as a ______________ adjustment to the average.
A.quantity; proportion
B. proportion; quantity
C. quantity; quantity
D. proportion; proportion
E. index; quantity

92. Which technique is useful in computing seasonal relatives?
A.Double smoothing
B. Delphi technique
C. MSE
D. Centred moving average
E. Exponential smoothing

93. The following equation is used to predict quarterly demand: Y_t = 350 – 2.5t, where t = 0 in the second quarter of last year. Quarter relatives are Q1 = 1.5; Q2 = 0.8; Q3 = 1.1; and Q4 = 0.6. What is the forecast for the last quarter of this year?
A.201
B. 335
C. 268
D. 199.5
E. 266

94. Which of the following might be used to forecast the cyclical component of a time series?
A.An associated leading variable
B. Centred moving average (CMA)
C. Delphi technique
D. Exponential smoothing
E. Seasonal relatives

95. The primary method for associative forecasting is:
A.Naïve method
B. Regression analysis
C. Simple moving averages
D. Centred moving averages
E. Exponential smoothing

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-06 Describe associated models (regression) and solve typical problems.
Topic: 03-21 Associative Models

96. Which term most closely describes what associative forecasting techniques are based on?
A.Time series data
B. Linear relationships
C. The Delphi technique
D. Consumer survey
E. Predictor variables

Accessibility: Keyboard Navigation
Difficulty: Medium
Learning Objective: 03-06 Describe associated models (regression) and solve typical problems.
Topic: 03-21 Associative Models

97. Which of the following corresponds to the predictor variable in simple linear regression?
A.Regression coefficient
B. Dependent variable
C. Independent variable
D. Predicted variable
E. Demand

Accessibility: Keyboard Navigation
Difficulty: Easy
Learning Objective: 03-06 Describe associated models (regression) and solve typical problems.
Topic: 03-22 Simple Linear Regression

98. Use of simple linear regression analysis assumes that:
A.Variations around the line are non-random.
B. Deviations around the line are not normally distributed.
C. Predictions can be made outside the range of observed values of the predictor variable.
D. A straight line will be determined that maximizes the sum of deviations of the data points.
E. Predictions are to be made only within the range of observed values of the predictor variable.

Accessibility: Keyboard Navigation
Difficulty: Hard
Learning Objective: 03-06 Describe associated models (regression) and solve typical problems.
Topic: 03-22 Simple Linear Regression

99. The mean absolute deviation (MAD) is used to:
A.estimate the trend line.
B. eliminate forecast errors.
C. measure forecast accuracy.
D. seasonally adjust the forecast.
E. measure average data.

100. All of the following are used to measure forecast errors EXCEPT?
A.Mean absolute difference (MAD)
B. Mean weighted moving average (MWMA)
C. Mean absolute percentage error (MAPE)
D. Mean squared error (MSE)

101. MAPE measures the:
A.mean actual produced error.
B. mean absolute percent error.
C. main accuracy percent evaluation.
D. mean absolute produced error.
E. mean average percent error.

102. Positive forecast errors mean that the forecast:
A.was too high.
B. was too low.
C. was accurate.
D. was irregular.
E. is where the predictor variable indicated.

103. Given forecast errors of 4, 8, and -3, what is the mean absolute deviation?
A.4
B. 3
C. 5
D. 6
E. 12

104. MSE weighs errors according to ______________ and MAPE weighs according to _______________.
A.squared values; mean absolute values
B. absolute values; absolute percentage error
C. absolute percentage error; squared values
D. squared values; absolute percentage error
E. absolute error; average error

105. Given forecast errors of 5, 0, -4, and 3, what is the mean absolute deviation (MAD)?
A.4
B. 3
C. 2.5
D. 2
E. 1

106. Given forecast errors of -5, -10, and +15, what is the mean absolute deviation (MAD)?
A.0
B. 10
C. 30
D. 175
E. 7.5

107. The actual demand and the forecasted demand for a product were as follows:

period:	1	2	3
actual:	286	255	275
forecast:	280	290	295

Compute the MAPE.
A. 0.77%
B. 7.7%
C. 0.23
D. 23
E. 6.9%

108. Which of the following is used for constructing a control chart?
A.Mean absolute deviation (MAD)
B. Mean absolute percentage error (MAPE)
C. Tracking signal (TS)
D. Actual – forecast
E. None of the choices are correct.

109. The two most important factors in choosing a forecasting technique are:
A.cost and time horizon.
B. accuracy and time horizon.
C. cost and accuracy.
D. accuracy and buy-in.
E. cost and ease of use.

110. Which of the following factors is generally not a consideration at the time of selecting an appropriate forecasting method to use?
A.Amount of historical data available
B. Forecast horizon
C. Mean square error in the forecast
D. Evidence of a pattern in time series data
E. Preparation time (cost)

111. Sales for a product have been fairly consistent over several years, although showing a steady upward trend. The company wants to understand what drives sales. The best forecasting technique would be:
A.trend models.
B. judgmental methods.
C. moving averages.
D. regression models.
E. exponential smoothing techniques.

112. Which of the following techniques are most likely to be used for forecasting demand for new products and services?
A.Trend models
B. Judgmental methods
C. Moving averages
D. Regression models
E. Exponential smoothing techniques

113. Which of the following are most likely to be used for forecasting demand for the longer term?
A.Regression trend models
B. Judgmental methods
C. Delphi method
D. Simple exponential smoothing
E. Naïve method

114. An automobile company is trying to forecast demand for minivans over the next 10 years. Which method of forecasting are they most likely to use?
A.Regression trend models
B. Moving averages
C. Delphi method
D. Simple exponential smoothing
E. Naïve method

115. A company is conducting long-term planning of which types of services they should offer. Which of the following forecasting techniques are they most likely to use?
A.Trend models
B. Executive opinion
C. Regression models
D. Simple exponential smoothing
E. Naïve method

116. A managerial approach toward forecasting which seeks to actively influence demand is:
A.reactive.
B. proactive.
C. reflexive.
D. protracted.
E. retroactive.

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