Deck 15: Forecasting

Question 1

One way to deal with the bullwhip effect is to develop and share the forecasts with other supply chain members.

Answer 1

True

Question 2

A seasonal pattern is an oscillating movement in demand that occurs periodically over the short-run and is repetitive.

Answer 2

True

Question 3

Movements in demand that do not follow a given pattern are referred to as random variations.

Answer 3

True

Question 4

Sharing demand forecasts with supply chain members has resulted in an increased bullwhip effect.

Question 5

A gradual,long-term up or down movement of demand is called a trend.

Question 6

In today's competitive environment,effective supply chain management requires accurate demand forecasts.

Question 7

A gradual,long-term up or down movement of demand is referred to as a trend.

Question 8

The trend toward continuous replenishment in supply chain design has shifted the need for accurate forecasts from short-term to long-term.

Question 9

Long-range qualitative forecasts are used to determine future demand for new products,markets,and customers.

Question 10

The type of forecasting method selected depends on time frame,demand behaviour,and causes of behaviour.

Question 11

Many companies are shifting from long-term to short-term forecast for strategic planning.

Question 12

Qualitative forecasts use mathematical techniques and statistical formulas.

Question 13

Short-mid-range forecasts tend to use quantitative models that forecast demand based on historical demand.

Question 14

Forecasts based on mathematical formulas are referred to as qualitative forecasts.

Question 15

Because of globalization of markets,managers are finding it increasingly more difficult to create accurate demand forecasts.

Question 16

Forecasting customer demand is rarely a key to providing good quality service.

Question 17

The long-term strategic planning process is dependent upon qualitative forecasting methods.

Question 18

The demand behaviour for skis is considered cyclical.

Question 19

The Delphi method generates forecasts based on informed judgments and opinions from knowledgeable individuals.

Question 20

Because of advances in technology,many service industries no longer require accurate forecasts to provide high quality service.

Question 21

Multiple regression analysis can be used to relate demand to two or more dependent variables.

Question 22

The type of forecasting method used depends entirely whether the supply chain is continuous replenishment or not.

Question 23

The moving average method is used for creating forecasts when there is no variation in demand.

Question 24

Regression is used for forecasting when there is a relationship between the dependent variable,demand,and one or more independent (explanatory)variables.

Question 25

Because of the heightened competition resulting from globalization,most companies find little strategic value in long-range forecasts.

Question 26

Exponential smoothing is an averaging method for forecasting that reacts more strongly to recent changes in demand.

Question 27

Because of the development of advanced forecasting models,managers no longer track forecast error.

Question 28

Time series methods assume that demand patterns in the past are a good predictor of demand in the future.

Question 29

Because of ease of use and simplicity,exponential smoothing is preferred over smoothing average.

Question 30

A correlation coefficient is a measure of the strength of the linear relationship between an independent and a dependent variable.

Question 31

Correlation in linear regression is a measure of the strength of the relationship between the dependent variable,demand,and an independent (explanatory)variable.

Question 32

A linear regression model that relates demand to time is known as a linear trend line.

Question 33

One reason time series methods are popular for forecasting is that they are relatively easy to use and understand.

Question 34

Time series methods use historical data to predict future demand.

Question 35

Linear regression relates two variables using a linear model.

Question 36

The most common type of forecasting method for long-term strategic planning is based on quantitative modelling.

Question 37

The larger the mean absolute deviation (MAD),the more accurate the forecast.

Question 38

Continuous replenishment systems rely heavily on extremely accurate long-term forecasts.

Question 39

Forecast bias is measured by the per-period average of the sum of the forecast errors.

Question 40

The average,absolute difference between the forecast and demand is a popular measure of forecast error.

Question 41

Which of the following is not a type of predictable demand behaviour?

A)trend
B)random variation
C)cycle
D)seasonal pattern

Question 42

If forecast errors are normally distributed,then

A)1 MAD = 1σ.
B)1 MAD ≈ 0.8 σ.
C)0.8 MAD ≈ 1σ.
D)1 MAD ≈ 1.96 σ.

Question 43

Regression forecasting methods relate ___ to other factors that cause demand behaviour.

A)supply
B)demand
C)time
D)money
E)efficiency

Question 44

Given the following demand data for the past five months,the three-period moving average forecast for June is

A)103.33.
B)99.00.
C)95.00.
D)92.50.

Question 45

The sum of the weights in a weighted moving average forecast

A)must equal the number of periods being averaged.
B)must equal 1.00.
C)must be less than 1.00.
D)must be greater than 1.00.

Question 46

The ___ method uses demand in the first period to forecast demand in the next period.

A)naïve
B)moving average
C)exponential smoothing
D)linear trend

Question 47

Forecast methods based on judgment,opinion,past experiences,or best guesses are known as ___ methods.

A)quantitative
B)qualitative
C)time series
D)regression

Question 48

Selecting the type of forecasting method to use depends on

A)the time frame of the forecast.
B)the behaviour of demand and demand patterns.
C)the causes of demand behaviour.
D)all of the above.

Question 49

A long-range forecast would normally not be used to

A)design the supply chain.
B)implement strategic programs.
C)determine production schedules.
D)plan new products for changing markets

Question 50

An exponential smoothing forecasting technique requires all of the following except

A)the forecast for the current period.
B)the actual demand for the current period.
C)a smoothing constant.
D)large amounts of historical demand data.

Question 51

A company wants to product a weighted moving average forecast for April with the weights 0.40,0.35,and 0.25 assigned to March,February,and January,respectively.If the company had demands of 5,000 in January,4,750 in February,and 5,200 in March,then April's forecast is

A)4983.33.
B)4992.50.
C)4962.50.
D)5000.00.

Question 52

Correlation is a measure of the strength of the

A)nonlinear relationship between two dependent variables.
B)nonlinear relationship between a dependent and independent variable.
C)linear relationship between two dependent variables.
D)linear relationship between a dependent and independent variable.

Question 53

A forecast where the current period's demand is used as the next period's forecast is known as a

A)moving average forecast.
B)naïve forecast.
C)weighted moving average forecast.
D)Delphi forecast.

Question 54

Given the following demand data for the past five months,the four-period moving average forecast for June is

A)96.25.
B)99.00.
C)110.00.
D)93.75.

Question 55

The smoothing constant,α,in the exponential smoothing forecast

A)must always be a value greater than 1.0.
B)must always be a value less than 0.10.
C)must be a value between 0.0 and 1.0.
D)should be equal to the time frame for the forecast.

Question 56

A qualitative procedure used to develop a consensus forecast is known as

A)exponential smoothing.
B)regression methods.
C)the Delphi technique.
D)naïve forecasting.

Question 57

The ___ forecast method consists of an exponentially smoothed forecast with a trend adjustment factor added to it.

A)exponentially smoothed
B)adjusted exponentially smoothed
C)time series
D)moving average

Question 58

The closer the smoothing constant,α,is to 1.0,

A)the greater the reaction to the most recent demand.
B)the greater the dampening,or smoothing,effect.
C)the more accurate the forecast.
D)the less accurate the forecast.

Question 59

A ___ is an up-and-down movement in demand that repeats itself over a lengthy time period of more than a year.

A)trend
B)seasonal pattern
C)random variation
D)cycle

Question 60

The exponential smoothing model produces a naïve forecast when the smoothing constant,α,is equal to

A)0.00.
B)1.00.
C)0.50.
D)2.00

Question 61

The weighted moving average forecast for the fifth period with weights of 0.15 for period 1,0.20 for period 2,0.25 for period 3,and 0.40 for period 4,using the demand data shown below is

A)3760.
B)3700.
C)3650.
D)3325.

Question 62

A large positive cumulative error indicates that the forecast is probably

A)higher than the actual demand.
B)lower than the actual demand.
C)unbiased.
D)biased.

Question 63

Given the demand and forecast values below,the naïve forecast for September is

A)100.6.
B)99.0.
C)102.0.
D)cannot be determined.

Question 64

A forecasting model has produced the following forecasts: The forecast error for February is

A)10.
B)-10.
C)-15.
D)-5

Question 65

Which of the following is a reason why a forecast can go "out of control?"

A)a change in trend
B)an irregular variation such as unseasonable weather
C)a promotional campaign
D)all of the above

Question 66

A forecasting model has produced the following forecasts: The mean absolute deviation (MAD)for the end of May is

A)7.0.
B)7.5.
C)10.0
D)3.0

Question 67

The demand and forecast values are shown in the table below: The MAD through the end of October would be

A)9.20.
B)-9.20.
C)1.00.
D)7.00.

Question 68

A mathematical technique for forecasting that relates the dependent variable to an independent variable is

A)correlation analysis.
B)exponential smoothing.
C)linear regression.
D)weighted moving average.

Question 69

The mean absolute percentage deviation (MAPD)measures the absolute error as a percentage of

A)all errors.
B)per period demand.
C)total demand.
D)the average error.

Question 70

The per period average of cumulative error is called

A)cumulative forecast variation.
B)absolute error.
C)average error.
D)noise.

Question 71

Given the demand and forecast values shown in the table below: The three-period moving average forecast for November is

A)516.
B)528.
C)524.
D)515.

Question 72

Which of the following can be used to monitor a forecast to see if it is biased high or low?

A)a tracking signal
B)the mean absolute deviation (MAD)
C)the mean absolute percentage deviation (MAPD)
D)a linear trend line model

Question 73

A forecasting model has produced the following forecasts: At the end of May the tracking signal would be

A)0.000.
B)0.667.
C)1.333.
D)2.143.

Question 74

For the demand values and the January forecast shown in the table below,the exponential smoothing forecast for March using α = 0.30 is

A)489.
B)486.
C)483.
D)480.

Question 75

If the forecast for July was 3300 and the actual demand for July was 3250,then the exponential smoothing forecast for August using α = 0.20 is

A)3300.
B)3290.
C)3275.
D)3250.

Question 76

A tracking signal is computed by

A)multiplying the cumulative error by MAD.
B)multiplying the absolute error by MAD.
C)dividing MAD by the cumulative absolute error.
D)dividing the cumulative error by MAD.

Question 77

A forecasting model has produced the following forecasts: At the end of May the average error would be

A)7.
B)5.
C)3.
D)1.

Question 78

For the demand values and the January forecast shown in the table below,the exponential smoothing forecast for March using α = 0.40 is

A)1200.
B)1220.
C)1222.
D)1225.

Question 79

The demand and forecast values are shown in the table below: The forecast error for September is

A)10.00.
B)-10.00.
C)1.00.
D)39.00.

Question 80

Which of the following statements concerning average error is true?

A)A positive value indicates high bias,and a negative value indicates low bias.
B)A positive value indicates zero bias,and a negative value indicates low bias.
C)A negative value indicates zero bias,and a negative value indicates high bias.
D)A positive value indicates low bias,and a negative value indicates high bias.