Operations Management, 11e (Heizer/Render)
Chapter 4 Forecasting
Section 1 What is Forecasting?
1) Forecasts may be influenced by a product’s position in its life cycle.
2) Demand forecasts serve as inputs to financial, marketing, and personnel planning.
3) What two numbers are contained in the daily report to the CEO of Walt Disney Parks & Resorts
regarding the six Orlando parks?
A) yesterday’s forecasted attendance and yesterday’s actual attendance
B) yesterday’s actual attendance and today’s forecasted attendance
C) yesterday’s forecasted attendance and today’s forecasted attendance
D) yesterday’s actual attendance and last year’s actual attendance
E) yesterday’s forecasted attendance and the year–to-date average daily forecast error
4) As compared to long-range forecasts, short-range forecasts:
A) are less accurate.
B) deal with less comprehensive issues supporting management decisions.
C) employ similar methodologies.
D) all of the above
E) none of the above
5) One use of short-range forecasts is to determine:
A) planning for new products.
B) capital expenditures.
C) research and development plans.
D) facility location.
E) job assignments.
6) Forecasts are usually classified by time horizon into which three categories?
A) short-range, medium-range, and long-range
B) finance/accounting, marketing, and operations
C) strategic, tactical, and operational
D) exponential smoothing, regression, and time series
E) departmental, organizational, and industrial
7) A forecast with a time horizon of about 3 months to 3 years is typically called a:
A) long-range forecast.
B) medium-range forecast.
C) short-range forecast.
D) weather forecast.
E) strategic forecast.
8) Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D
typically utilize a:
A) short-range time horizon.
B) medium-range time horizon.
C) long-range time horizon.
D) naive method, because there is no data history.
E) trend extrapolation.
9) The three major types of forecasts used by organizations in planning future operations are:
A) strategic, tactical, and operational.
B) economic, technological, and demand.
C) exponential smoothing, Delphi, and regression.
D) causal, time-series, and seasonal.
E) departmental, organizational, and territorial.
10) Which of the following most requires long-range forecasting (as opposed to short-range or medium-
range forecasting) for its planning purposes?
A) job scheduling
B) production levels
C) cash budgeting
D) capital expenditures
E) purchasing
11) Short-range forecasts tends to ________ longer-range forecasts.
A) be less accurate than
B) be more accurate than
C) have about the same level of accuracy as
D) employ the same methodologies as
E) deal with more comprehensive issues than
12) ________ forecasts are concerned with rates of technological progress, which can result in the birth of
exciting new products, requiring new plants and equipment.
13) ________ forecasts address the business cycle by predicting inflation rates, money supplies, housing
starts, and other planning indicators.
14) A skeptical manager asks what short-range forecasts can be used for. Give her three possible
uses/purposes.
15) A skeptical manager asks what long-range forecasts can be used for. Give her three possible
uses/purposes.
16) Describe the three forecasting time horizons and their use.
17) List and briefly describe the three major types of forecasts that organizations use in planning future
operations.
Section 2 The Strategic Importance of Forecasting
1) What forecasting systems combine the intelligence of multiple supply chain partners?
A) FORE
B) MULTISUP
C) CPFR
D) SUPPLY
E) MSCP
Section 3 Seven Steps in the Forecasting System
1) Forecasts of individual products tend to be more accurate than forecasts of product families.
2) Most forecasting techniques assume that there is some underlying stability in the system.
3) Which of the following is NOT a step in the forecasting process?
A) Determine the use of the forecast.
B) Eliminate any assumptions.
C) Determine the time horizon of the forecast.
D) Select the forecasting model.
E) Validate and implement the results.
4) Identify the seven steps involved in forecasting.
5) What are the three realities of forecasting that companies face?
1) The sales force composite forecasting method relies on salespersons’ estimates of expected sales.
2) A time-series model uses a series of past data points to make the forecast.
3) The quarterly “make meeting” of Lexus dealers is an example of a sales force composite forecast.
4) The two general approaches to forecasting are:
A) qualitative and quantitative.
B) mathematical and statistical.
C) judgmental and qualitative.
D) historical and associative.
E) judgmental and associative.
5) Which of the following uses three types of participants: decision makers, staff personnel, and
respondents?
A) jury of executive opinion
B) sales force composite
C) Delphi method
D) associative models
E) time series
6) The forecasting technique that pools the opinions of a group of experts or managers is known as:
A) the expert judgment model.
B) multiple regression.
C) jury of executive opinion.
D) market survey.
E) management coefficients.
7) Which of the following is not a type of qualitative forecasting?
A) jury of executive opinion
B) sales force composite
C) market survey
D) Delphi method
E) moving average
8) Which of the following techniques uses variables such as price and promotional expenditures, which
are related to product demand, to predict demand?
A) associative models
B) exponential smoothing
C) weighted moving average
D) moving average
E) trend projection
9) ________ forecasts employ one or more mathematical models that rely on historical data and/or
associative variables to forecast demand.
10) ________ is a forecasting technique based upon salespersons’ estimates of expected sales.
11) ________ forecasts use a series of past data points to make a forecast.
12) What are the differences between quantitative and qualitative forecasting methods?
13) Identify four quantitative forecasting methods.
14) What is a time-series forecasting model?
15) What is the difference between an associative model and a time-series model?
16) Name and discuss three qualitative forecasting methods.
Section 5 Time-Series Forecasting
1) A naïve forecast for September sales of a product would be equal to the forecast for August.
2) Cycles and random variations are both components of time series.
3) A naïve forecast for September sales of a product would be equal to the sales in August.
4) One advantage of exponential smoothing is the limited amount of record keeping involved.
5) The larger the number of periods in the simple moving average forecasting method, the greater the
method’s responsiveness to changes in demand.
6) Mean squared error and exponential smoothing are two measures of the overall error of a forecasting
model.
7) In trend projection, the trend component is the slope of the regression equation.
8) In trend projection, a negative regression slope is mathematically impossible.
9) Seasonal indices adjust raw data for patterns that repeat at regular time intervals.
10) A trend projection equation with a slope of 0.78 means that there is a 0.78 unit rise in Y per period.
11) Demand for individual products can be driven by product life cycles.
12) Which of the following statements about time-series forecasting is true?
A) It is always based on the assumption that future demand will be the same as past demand.
B) It makes extensive use of the data collected in the qualitative approach.
C) It is based on the assumption that the analysis of past demand helps predict future demand.
D) Because it accounts for trends, cycles, and seasonal patterns, it is always more powerful than
associative forecasting.
E) All of the above are true.
13) Time-series data may exhibit which of the following behaviors?
A) trend
B) random variations
C) seasonality
D) cycles
E) They may exhibit all of the above.
14) Gradual upward or downward movement of data over time is called:
A) seasonality.
B) a cycle.
C) a trend.
D) exponential variation.
E) random variation.
15) Which of the following is not present in a time series?
A) seasonality
B) operational variations
C) trend
D) cycles
E) random variations
16) The fundamental difference between cycles and seasonality is the:
A) duration of the repeating patterns.
B) magnitude of the variation.
C) ability to attribute the pattern to a cause.
D) all of the above
E) none of the above
17) In time series, which of the following cannot be predicted?
A) large increases in demand
B) cycles
C) seasonal fluctuations
D) random variations
E) large decreases in demand
18) What is the forecast for May using a four-month moving average?
Nov.
Dec.
Jan.
Feb.
Mar.
April
39
36
40
42
48
46
A) 38
B) 42
C) 43
D) 44
E) 47
19) Which time-series model below assumes that demand in the next period will be equal to the most
recent period’s demand?
A) naïve approach
B) moving average approach
C) weighted moving average approach
D) exponential smoothing approach
E) trend projection
20) John’s House of Pancakes uses a weighted moving average method to forecast pancake sales. It
assigns a weight of 5 to the previous month’s demand, 3 to demand two months ago, and 1 to demand
three months ago. If sales amounted to 1000 pancakes in May, 2200 pancakes in June, and 3000 pancakes
in July, what should be the forecast for August?
A) 2400
B) 2511
C) 2067
D) 3767
E) 1622
21) A six-month moving average forecast is generally better than a three-month moving average forecast
if demand:
A) is rather stable.
B) has been changing due to recent promotional efforts.
C) follows a downward trend.
D) exceeds one million units per year.
E) follows an upward trend.
22) Increasing the number of periods in a moving average will accomplish greater smoothing, but at the
expense of:
A) manager understanding.
B) accuracy.
C) stability.
D) sensitivity to real changes in the data.
E) All of the above are diminished when the number of periods increases.
23) Which of the following statements comparing exponential smoothing to the weighted moving
average technique is TRUE?
A) Exponential smoothing is more easily used in combination with the Delphi method.
B) More emphasis can be placed on recent values using the weighted moving average.
C) Exponential smoothing is considerably more difficult to implement on a computer.
D) Exponential smoothing typically requires less record keeping of past data.
E) Exponential smoothing allows one to develop forecasts for multiple periods, whereas the weighted
moving average technique does not.
24) Which time-series model uses BOTH past forecasts and past demand data to generate a new forecast?
A) naïve
B) moving average
C) weighted moving average
D) exponential smoothing
E) trend projection
25) Which of the following is NOT a characteristic of exponential smoothing?
A) smoothes random variations in the data
B) uses an easily altered weighting scheme
C) weights each historical value equally
D) has minimal data storage requirements
E) uses the previous period’s forecast
26) Which of the following smoothing constants would make an exponential smoothing forecast
equivalent to a naive forecast?
A) 0
B) 1 divided by the number of periods
C) 0.5
D) 1.0
E) cannot be determined
27) Given an actual demand this period of 103, a forecast value for this period of 99, and an alpha of .4,
what is the exponential smoothing forecast for next period?
A) 94.6
B) 97.4
C) 100.6
D) 101.6
E) 103.0
28) A forecast based on the previous forecast plus a percentage of the forecast error is a(n):
A) qualitative forecast.
B) naive forecast.
C) moving average forecast.
D) weighted moving average forecast.
E) exponential smoothing forecast.
29) Given an actual demand this period of 61, a forecast for this period of 58, and an alpha of 0.3, what
would the forecast for the next period be using exponential smoothing?
A) 45.5
B) 57.1
C) 58.9
D) 61.0
E) 65.5
30) Which of the following values of alpha would cause exponential smoothing to respond the SLOWEST
to forecast errors?
A) 0.10
B) 0.2246
C) 0.50
D) 0.90
E) cannot be determined
31) A forecasting method has produced the following over the past five months. What is the mean
absolute deviation?
Actual
Forecast
Error
|Error|
10
11
-1
1
8
10
-2
2
10
8
2
2
6
6
0
0
9
8
1
1
A) -0.2
B) -1.0
C) 0.0
D) 1.2
E) 8.6
32) The primary purpose of the mean absolute deviation (MAD) in forecasting is to:
A) estimate the trend line.
B) eliminate forecast errors.
C) measure forecast accuracy.
D) seasonally adjust the forecast.
E) remove random variations.
4-18
33) Given forecast errors of -1, 4, 8, and -3, what is the mean absolute deviation?
A) 2
B) 3
C) 4
D) 8
E) 16
34) Suppose that the last four months of sales were 8, 10, 15, and 9 units, respectively. Suppose further
that the last four forecasts were 5, 6, 11, and 12 units, respectively. What is the Mean Absolute Deviation
(MAD) of these forecasts?
A) 2
B) –10
C) 3.5
D) 9
E) 10.5
35) A time-series trend equation is 25.3 + 2.1x. What is your forecast for period 7?
A) 23.2
B) 25.3
C) 27.4
D) 40.0
E) 179.2
36) For a given product demand, the time-series trend equation is 53 – 4x. The negative sign on the slope
of the equation:
A) is a mathematical impossibility.
B) is an indication that the forecast is biased, with forecast values lower than actual values.
C) is an indication that product demand is declining.
D) implies that the coefficient of determination will also be negative.
E) implies that the cumulative error will be negative.
37) Yamaha manufactures which set of products with complementary demands to address seasonal
variations?
A) golf clubs and skis
B) swimming suits and winter jackets
C) jet skis and snowmobiles
D) pianos and guitars
E) ice skates and water skis
38) Which of the following is TRUE regarding the two smoothing constants of the Forecast Including
Trend (FIT) model?
A) One constant is positive, while the other is negative.
B) They are called MAD and cumulative error.
C) Alpha is always smaller than beta.
D) One constant smoothes the regression intercept, whereas the other smoothes the regression slope.
E) Their values are determined independently.
39) Demand for a certain product is forecast to be 800 units per month, averaged over all 12 months of the
year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the
seasonally-adjusted sales forecast for January?
A) 640 units
B) 798.75 units
C) 801.25 units
D) 1000 units
E) 83.33 units
40) A seasonal index for a monthly series is about to be calculated on the basis of three years’
accumulation of data. The three previous July values were 110, 150, and 130. The average demand over
all months during the three-year time period was 190 . What is the approximate seasonal index for July?
A) 0.487
B) 0.684
C) 1.462
D) 2.053
E) cannot be calculated with the information given
41) Suppose that the demand in period 1 was 7 units and the demand in period 2 was 9 units. Assume
that the forecast for period 1 was for 5 units. If the firm uses exponential smoothing with an alpha value
of .20, what should be the forecast for period 3? (Round answers to two decimal places.)
A) 9.00
B) 3.72
C) 9.48
D) 5.00
E) 6.12