Deck 5: Supply Chain Planning and Analytics

Question 1

In aggregate planning,when the same amount of output is produced each period,it is called what?

A)Flat production
B)Constant production
C)Level production
D)Chase production
E)None of the above

Answer 1

Level production

Question 2

Which of the following is not an assumption of regression?

A)The residuals are normally distributed
B)The expected value of the residuals is one
C)The residuals are independent of one another
D)The variance of the residuals is constant
E)All of them are assumptions of regression

Answer 2

The expected value of the residuals is one

Question 3

Informal forecasting methods include both quantitative and qualitative techniques.

Answer 3

False

Question 4

Which of the following is not a method for assessing the accuracy of forecasting models?

A)Error
B)Bias
C)MAD
D)MAPE

Question 5

Some of the most significant decisions made by organizations,frequently strategic decisions,are made on the basis of quantitative forecasts.

Question 6

Typically,organizations evolve through a number of stages as they gain experience with analytics and become more sophisticated in applying it toward the goal of developing a world class supply chain.Which of the following is not one of those stages?

A)Depend on suppliers for their data
B)Summarize and report data to decision makers
C)Develop the capability to analyze real-time data
D)Seek to predict what will happen in the future
E)All of the above are stages

Question 7

A time series is simply a set of values of some variable measured either at regular points in time or over sequential intervals of time.

Question 8

Many organizations have recently turned their attention to their supply chains as the next frontier for gaining competitive advantage.

Question 9

Like all business activities,the process of demand planning in general and forecasting in particular can be improved.

Question 10

Examples of the types of problems that arise as a result of poor supply chain planning and execution include which of the following?

A)Customer dissatisfaction because their orders are received late
B)Increased costs when supplies need to be expedited
C)Strained relationships with suppliers
D)Incurring the wrath of the finance department
E)All of the above are problems

Question 11

Which of the following is not a causal quantitative forecasting method?

A)Multiple regression
B)Exponential smoothing
C)Econometric
D)Box-Jenkins
E)All of them are causal quantitative forecasting methods

Question 12

Which of the following is not a time series analysis quantitative forecasting method?

A)Multiple regression
B)Simple regression
C)Exponential smoothing
D)Moving average
E)All of them are time series analysis quantitative forecasting methods

Question 13

Which of the following is not a component of time series data.

A)Trend
B)Seasonal variation
C)Irregular events
D)Cyclical variation
E)Random variation

Question 14

Simple linear regression has how many independent variables?

A)Zero
B)One
C)Two
D)More than two
E)Different models have different numbers

Question 15

A cycle can be defined as a short-term oscillation,or a swing of the data points about the trend line over a period of at least three months.

Question 16

Long-range (two-to five-year)forecasts typically require the most accuracy because they are used for general (or aggregate)planning,

Question 17

There are how many pure aggregate planning strategies?

A)One
B)Two
C)Three
D)More than three
E)It depends on the organization

Question 18

One approach that is gaining increasing acceptance to help coordinate the joint planning of supply chain partners is which of the following?

A)CRAFT
B)CRP
C)Demand management
D)CPFR
E)Vendor-managed inventories

Question 19

Which of the following is true regarding seasonal indices?

A)They are always less than or equal to one
B)About half of them will be negative
C)They sum to the number of periods
D)They sum to one
E)None of the above are true

Question 20

Which of the following is not a common pitfall of using regression to forecast?

A)Making predictions outside the range of data used to develop the model
B)Overly generalizing a regression model
C)Assuming a cause-and-effect relationship based on the model
D)Using a model with a negative slope coefficient
E)All of the above are common pitfalls

Question 21

The true parameters of the regression models used for forecasting are unknown.

Question 22

The trend line is the long-run direction of the data and does not include any seasonal variation.

Question 23

In aggregate planning,level production yields the best utilization of the workforce.

Question 24

When does it make sense to use a qualitative forecasting method over a quantitative method?

Question 25

Seasonal factors are always less than or equal to one.

Question 26

What are the random variations component of a time series?

Question 27

What is the trend component of a time series?

Question 28

What are the seasonal fluctuations of a time series?

Question 29

A negative MAD indicates a forecast that is too low.

Question 30

Moving averages cannot predict a trend,they are only used for seasonal variation.

Question 31

The forecast tells an organization how much to produce.

Question 32

Discuss the two difficulties commonly found with Time series and how to correct it.

Question 33

Our objective in exponential forecasting is to choose the value of alpha that results in the best forecasts.

Question 34

Adaptive forecasting models self-adjust by increasing or decreasing the smoothing constant alpha when the tracking signal becomes too large.

Question 35

Why might a company use the Delphi method of qualitative forecasting rather than say expert opinion?

Question 36

Provide an example of a time series.

Question 37

Most firms do not use just one of the pure aggregate planning strategies.

Question 38

In exponential smoothing,larger values of alpha of are used in situations in which the data exhibit high variability.

Question 39

What is a time series?

Question 40

What is the cyclical component of a time series?

Question 41

Describe how exponential smoothing weights prior periods of demand.

Question 42

Why do companies not just produce the quantity of demand specified by the forecast?

Question 43

What does bias tell about the accuracy of a forecasting model?

Question 44

Describe the relationship between alpha and the variability of demand when forecasting using exponential smoothing.

Question 45

Time series analysis involves two inherent difficulties.Discuss these.

Question 46

Briefly discuss the assumptions of regression analysis.

Question 47

Briefly describe the two pure aggregate planning strategies.

Question 48

What is an outlier as it relates to simple regression?

Question 49

Briefly describe the three stages of CPFR.

Question 50

How does the Delphi method work?

Question 51

Why is the issue of outliers important in simple regression?

Question 52

What is the coefficient of determination.

Question 53

Describe the factors that influence the choice of a demand forecasting method.