Supply Chain Ch. 4
E. exponential smoothing forecast
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.
B. medium-range forecast
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.
D. 1.2
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
C. in trend projection the independent variable is time; in linear regression the independent variable need not be time, but can be any variable with explanatory power.
A fundamental distinction between trend projection and linear regression is that: A) trend projection uses least squares while linear regression does not. B) only linear regression can have a negative slope. C) in trend projection the independent variable is time; in linear regression the independent variable need not be time, but can be any variable with explanatory power. D) trend projection can be a function of several variables, while linear regression can only be a function of one variable. E) trend projection uses two smoothing constants, not just one.
Mean Absolute Percent Error
A measure of forecast error that does not depend upon the magnitude of the item being forecast is the ________.
False
A naïve forecast for September sales of a product would be equal to the forecast for August.
True
A naïve forecast for September sales of a product would be equal to the sales in August
B. deal with less comprehensive issues supporting management decisions
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
True
Focus forecasting tries a variety of computer models and selects the best one for a particular application
C. is an indication that product demand is declining
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.
A. short range, medium range, and long range
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
True
Forecasts may be influenced by a product's position in its life cycle.
False
Forecasts of individual products tend to be more accurate than forecasts of product families
C. long-range time horizon
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.
C. 100.6
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
C. 58.9
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
C. 4
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
C. a trend
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.
naive, moving averages, exponential smoothing, trend projection, and linear regression.
Identify four quantitative forecasting methods
Trend, seasonality, cycles, and random variation
Identify the four components of a time series
1. Determine the use of the forecast. 2. Select the items to be forecasted. 3. Determine the time horizon of the forecast. 4. Select the forecasting model(s). 5. Gather the data needed to make the forecast. 6. Make the forecast. 7. Validate and implement the results.
Identify the seven steps involved in forecasting.
True
One advantage of exponential smoothing is the limited amount of record keeping involved.
E. job assignments
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.
False
Regression lines graphically depict "cause-and-effect" relationships.
True
Seasonal indices adjust raw data for patterns that repeat at regular time intervals.
B. be more accurate than
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
Moving average
Simple ________ forecasts only work well if we can assume that market demands will stay fairly steady over time.
E. 6.12
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
C. 3.5
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
E. A and C are both correct
Taco Bell's unique employee scheduling practices are partly the result of using: A) point-of-sale computers to track food sales in 15 minute intervals. B) focus forecasting. C) a six-week moving average forecasting technique. D) multiple regression. E) A and C are both correct.
B. economic, technological, and demand
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.
D. ratio of cumulative error/MAD
The tracking signal is the: A) standard error of the estimate. B) absolute deviation of the last period's forecast. C) MAD. D) ratio of cumulative error / MAD. E) MAPE
A. qualitative and quantitative
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.
E. they may exhibit all of the above
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.
410
Weekly sales of ten-grain bread at the local organic food market are provided in the table below. Based on these data, forecast week 9 using a five-week moving average. Week Sales 1 415 2 389 3 420 4 382 5 410 6 432 7 405 8 421
D. 44
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
A. yesterday's forecasted attendance and yesterday's actual attendance
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
Exponential smoothing with trend adjustment
When one constant is used to smooth the forecast average and a second constant is used to smooth the trend, the forecasting method is ________.
C. weights each historical value equally
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
B. eliminate any assumptions
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.
Trend projection
________ is a time-series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecasts.
True
Most forecasting techniques assume that there is some underlying stability in the system
Exponential smoothing
The smoothing constant is a weighting factor used in ________.
Sales force composite
________ is a forecasting technique based upon salespersons' estimates of expected sales.
C. CPFR
1) What forecasting systems combine the intelligence of multiple supply chain partners? A) FORE B) MULTISUP C) CPFR D) SUPPLY E) MSCP
B. 0.684
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
A. is rather stable
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.
True
A time-series model uses a series of past data points to make the forecast
D. 40.0
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
True
A trend projection equation with a slope of 0.78 means that there is a 0.78 unit rise in Y per period.
Moving average
A(n) ________ forecast uses an average of the most recent periods of data to forecast the next period
Adaptive Smoothing
An approach to exponential smoothing in which the smoothing constant is automatically changed to keep errors to a minimum is called ________.
A cycle is longer (typically several years) than a season (typically days, weeks, months, or quarters). A cycle has variable duration, while a season has fixed duration and regular repetition. Cycles include a wide variety of factors that cause the economy to go from recession to expansion to recession over a period of years.
Compare seasonal effects and cyclical effects
B. adaptive smoothing
Computer monitoring of tracking signals and self-adjustment if a signal passes a preset limit is characteristic of: A) exponential smoothing including trend. B) adaptive smoothing. C) trend projection. D) focus forecasting. E) multiple regression analysis.
True
Cycles and random variations are both components of time series
D. 1000 units
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
True
Demand for individual products can be driven by product life cycles.
True
Demand forecasts serve as inputs to financial, marketing, and personnel planning.
A. use weights to place more emphasis on recent data
If Brandon Edward were working to develop a forecast using a moving averages approach, but he noticed a detectable trend in the historical data, he should: A) use weights to place more emphasis on recent data. B) use weights to minimize the importance of the trend. C) change to an associative multiple regression approach. D) use a simple moving average. E) change to a qualitative approach.
Seasonal variations
If a barbershop operator noted that Tuesday's business was typically twice as heavy as Wednesday's, and that Friday's business was typically the busiest of the week, business at the barbershop is subject to ________.
True
If a forecast is consistently greater than (or less than) actual values, the forecast is said to be biased.
D. B or C
If two variables were perfectly correlated, what would the coefficient of correlation r equal? A) 0 B) -1 C) 1 D) B or C E) none of the above
False
In a regression equation where y-hat is demand and x is advertising, a coefficient of determination (R2) of .70 means that 70% of the variance in advertising is explained by demand.
D. random variations
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
False
In trend projection, a negative regression slope is mathematically impossible.
True
In trend projection, the trend component is the slope of the regression equation.
D. sensitivity to real changes in data
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.
B. 2511
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
Associative forecasting
Linear regression is known as a(n) ________ model because it incorporates variables or factors that might influence the quantity being forecast.
True
Linear-regression analysis is a straight-line mathematical model to describe the functional relationships between independent and dependent variables.
E. all of the above
Many services maintain records of sales noting: A) the day of the week. B) unusual events. C) the weather. D) holiday impacts. E) all of the above.
False
Mean squared error and exponential smoothing are two measures of the overall error of a forecasting model
Coefficient of correlation
The ________ measures the strength of the relationship between two variables.
D. coefficient of correlation
The degree or strength of a relationship between two variables is shown by the: A) alpha. B) mean. C) mean absolute deviation. D) coefficient of correlation. E) cumulative error.
C. jury of executive opinion
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.
A. duration of the repeating patterns
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
False
The larger the number of periods in the simple moving average forecasting method, the greater the method's responsiveness to changes in demand
False
The larger the standard error of the estimate, the more accurate the forecasting model.
Bias
The last four weekly values of sales were 80, 100, 105, and 90 units. The last four forecasts were 60, 80, 95, and 75 units. These forecasts illustrate: A) qualitative methods. B) adaptive smoothing. C) slope. D) bias. E) trend projection.
C. measure forecast accuracy
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.
True
The quarterly "make meeting" of Lexus dealers is an example of a sales force composite forecast.
True
The sales force composite forecasting method relies on salespersons' estimates of expected sales
E. their values are determined independently
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.
E. moving average
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
B. operational variations
Which of the following is not present in a time series? A) seasonality B) operational variations C) trend D) cycles E) random variations
D. capitol expenditures
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
D. 1.0
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
C. It is based on the assumption that the analysis of past demand helps predict future demand.
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.
D. Exponential smoothing typically requires less record keeping of past data
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.
A. associative models
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
C. Delphi method
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
A. 0.10
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
A. naive approach
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
D. exponential smoothing
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
C. jet skis and snowmobiles
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
C. MAPE
________ expresses the error as a percent of the actual values. A) MAD B) MSE C) MAPE D) FIT E) The smoothing constant
Focus
________ forecasting tries a variety of computer models and selects the best one for a particular application.
Economic
________ forecasts address the business cycle by predicting inflation rates, money supplies, housing starts, and other planning indicators.
Technological
________ forecasts are concerned with rates of technological progress, which can result in the birth of exciting new products, requiring new plants and equipment.
Quantitative
________ forecasts employ one or more mathematical models that rely on historical data and/or associative variables to forecast demand.
Time-series
________ forecasts use a series of past data points to make a forecast.
