Supply Chain Management Final Revision

4) The result of each stage in the supply chain making its own separate forecast is
A) an accurate forecast.
B) a more accurate forecast.
C) a match between supply and demand.
D) a mismatch between supply and demand.
E) none of the above
Answer- D) a mismatch between supply and demand.
In every stage of supply, own separate forecast is needed to be maintained, these forecasts are often very different. The result may be a mismatch between supply and demand.
5) When all stages of a supply chain produce a collaborative forecast, it tends to be
A) much more detailed.
B) much more complex.
C) much more accurate.
D) much more flexible.
E) all of the above
Answer - C) much more accurate.
Under the mechanism of collaborative forecast, supply chain partners can jointly make demand plan, substantially reduce inventory and lead time, enhance accuracy of forecast, and finally improve supply chain performance ( Marilyn et al., 2000 )
6) The resulting accuracy of a collaborative forecast enables supply chains to be
A) more responsive but less efficient in serving their customers.
B) both more responsive and more efficient in serving their customers.
C) less responsive but less efficient in serving their customers.
D) both less responsive and less efficient in serving their customers.
E) None of the above are true.
Answer - B) both more responsive and more efficient in serving their customers.
When all stages of a supply chain work together to produce a collaborative forecast, it tends to be much more accurate. The resulting forecast accuracy enables supply chains to be both more responsive and more efficient in serving their customers.
7) Leaders in many supply chains have started moving
A) toward independent forecasting to improve their ability to match supply and demand.
B) toward consecutive forecasting to improve their ability to match supply and demand.
C) toward sequential forecasting to improve their ability to match supply and demand.
D) toward collaborative forecasting to improve their ability to match supply and demand.
E) None of the above are true.
Answer - D) toward collaborative forecasting to improve their ability to match supply and demand.
Leaders in many supply chains, from PC manufacturers to packaged-goods retailers, have improved their ability to match supply and demand by moving toward collaborative forecasting.
8) Production can utilize forecasts to make decisions concerning
A) scheduling.
B) sales-force allocation.
C) promotions.
D) new product introduction.
E) budgetary planning.
Answer - A) scheduling.
9) Marketing can utilize forecasts to make decisions concerning
A) scheduling.
B) promotions.
C) inventory control.
D) aggregate planning.
E) purchasing.
Answer - B) promotions.
Failure to make these decisions jointly may result in either too much or too little product in various stages of the supply chain.
10) Finance can utilize forecasts to make decisions concerning
A) scheduling.
B) promotions.
C) plant/equipment investment.
D) aggregate planning.
E) purchasing.
Answer - A) scheduling.
Helps in arranging, controlling and optimizing work and workloads in a production process or manufacturing process.
11) Personnel can utilize forecasts to make decisions concerning
A) scheduling.
B) promotions.
C) plant/equipment investment.
D) workforce planning.
E) purchasing.
Answer - B) promotions.
12) Mature products with stable demand
A) are usually easiest to forecast.
B) are usually hardest to forecast.
C) cannot be forecast.
D) do not need to be forecast.
E) none of the above
A) are usually easiest to forecast.
Promotional forecasting poses many challenges for both retailers and suppliers, but using retailer point-of-sale and inventory data to calculate missed.
13) When either the supply of raw materials or the demand for the finished product is highly variable, forecasting and the accompanying managerial decisions
A) are extremely simple.
B) are relatively straightforward.
C) are extremely difficult.
D) should not be attempted.
E) none of the above
Answer - C) are extremely difficult.
Forecasting and the accompanying managerial decisions are extremely difficult when either the supply of raw materials or the demand for the finished product is highly unpredictable.
14) One of the characteristics of forecasts is
A) forecasts are always right.
B) forecasts are always wrong.
C) short-term forecasts are usually less accurate than long-term forecasts.
D) long-term forecasts are usually more accurate than short-term forecasts.
E) none of the above
Answer- B) forecasts are always wrong.
Forecasts are always wrong and should thus include both the expected value of the forecast and a measure of forecast error.
15) One of the characteristics of forecasts is
A) aggregate forecasts are usually less accurate than disaggregate forecasts.
B) disaggregate forecasts are usually more accurate than aggregate forecasts.
C) short-term forecasts are usually less accurate than long-term forecasts.
D) long-term forecasts are usually less accurate than short-term forecasts.
E) none of the above
Answer - D) long-term forecasts are usually less accurate than short-term forecasts.
Long-term forecasts are usually less accurate than short-term forecasts; that is, long-term forecasts have a larger standard deviation of error relative to the mean than short-term forecasts.
16) One of the characteristics of forecasts is
A) aggregate forecasts are usually more accurate than disaggregate forecasts.
B) disaggregate forecasts are usually more accurate than aggregate forecasts.
C) short-term forecasts are usually less accurate than long-term forecasts.
D) long-term forecasts are usually more accurate than short-term forecasts.
E) none of the above
Answer - A) aggregate forecasts are usually more accurate than disaggregate forecasts.
Aggregate forecasts are usually more accurate than disaggregate forecasts, as they tend to have a smaller standard deviation of error relative to the mean. The greater the degree of aggregation, the more accurate the forecast.
17) Forecasts are always wrong and therefore
A) should include both the expected value of the forecast and a measure of forecast error.
B) should not include both the expected value of the forecast and a measure of forecast error.
C) should only be used when there are no accurate estimates.
D) should be missing the expected value of the forecast and a measure of forecast error.
E) none of the above
Answer - A) should include both the expected value of the forecast and a measure of forecast error.
Forecasts can always be wrong and should therefore include the expected value as well as the measure of forecast error.
18) Long-term forecasts are usually less accurate than short-term forecasts because
A) short-term forecasts have a larger standard deviation of error relative to the mean than long-term forecasts.
B) short-term forecasts have more standard deviation of error relative to the mean than long-term forecasts.
C) long-term forecasts have a smaller standard deviation of error relative to the mean than short-term forecasts.
D) long-term forecasts have a larger standard deviation of error relative to the mean than short-term forecasts.
E) none of the above
Answer - D) long-term forecasts have a larger standard deviation of error relative to the mean than short-term forecasts.
Short-term forecasts are more accurate than long-term forecasts: A longer forecasting horizon significantly increases the chance of changes not known to us yet having an impact on future demand.
19) Aggregate forecasts are usually more accurate than disaggregate forecasts because
A) aggregate forecasts tend to have a larger standard deviation of error relative to the mean.
B) aggregate forecasts tend to have a smaller standard deviation of error relative to the mean.
C) disaggregate forecasts tend to have a smaller standard deviation of error relative to the mean.
D) disaggregate forecasts tend to have less standard deviation of error relative to the mean.
E) none of the above
Answer- B) aggregate forecasts tend to have a smaller standard deviation of error relative to the mean.
Aggregated forecasts are more accurate than disaggregated forecasts. Forecasting the demand for a product at a national level is more accurate than forecasting it at each individual retail outlet. The variation of demand at each sales point is smoothed when aggregated with other locations, providing a more accurate prediction.
20) In general, the further up the supply chain a company is (or the further they are from the consumer),
A) the greater the distortion of information they receive.
B) the smaller the distortion of information they receive.
C) the information they receive is more accurate.
D) the information they receive is more useful.
E) none of the above
Answer - A) the greater the distortion of information they receive.
In general, farther up the Supply Chain, a company is, the greater is the distortion of information it receives. Hence, for such companies, agile systems can respond better to forecast inaccuracies.
22) Forecasting methods that are primarily subjective and rely on human judgment are known as
A) qualitative forecasting methods.
B) time series forecasting methods.
C) causal forecasting methods.
D) simulation forecasting methods.
E) none of the above
Answer - A) qualitative forecasting methods.
Qualitative methods of forecasting are purely based on judgments either of experts or a collective judgment of knowledgeable people in the industry or of potential customers. The five qualitative methods of forecasting include expert’s opinion method, Delphi method, sales force composite method, survey of buyers’ expectation method, and historical analogy method.
23) Forecasting methods that use historical demand to make a forecast are known as
A) qualitative forecasting methods.
B) time series forecasting methods.
C) causal forecasting methods.
D) simulation forecasting methods.
E) none of the above
Answer - B) time series forecasting methods.
Theoretically, Forecasting methods are classified according to the following four types:
a. Qualitative Forecasting methods: Appropriate when historical data are available.
b. Time series forecasting methods: Use historical demand to make a forecast. It is
among most appropriate method, when the basic demand pattern does not vary
significantly from one year to the next.
c. Casual Forecasting Methods: Forecasting methods assume that the demand forecast is
highly correlated with certain factors in the environment (the state of the economy, interest
rates, etc.).
d. Simulation Methods: Simulation forecasting methods focused on ascertaining demand
based on various underlined factors including price, impact of competition etc
24) Forecasting methods that assume that the demand forecast is highly correlated with certain factors in the environment (e.g., the state of the economy, interest rates, etc.) to make a forecast are known as
A) qualitative forecasting methods.
B) time series forecasting methods.
C) causal forecasting methods.
D) simulation forecasting methods.
E) none of the above
Answer - C) causal forecasting methods.
Forecasting methods are classified according to the following four types.
1. Qualitative: Qualitative forecasting methods are primarily subjective and rely on
human judgment.
2. Time series: Time-series forecasting methods use historical demand to make a forecast.
3. Causal: Causal forecasting methods assume that the demand forecast is highly correlated with certain factors in the environment (the state of the economy, interest rates,
etc.).
4. Simulation: Simulation forecasting methods imitate the consumer choices that give
rise to demand to arrive at a forecast.
25) Forecasting methods that imitate the consumer choices that give rise to demand to arrive at a forecast are known as
A) qualitative forecasting methods.
B) time series forecasting methods.
C) causal forecasting methods.
D) simulation forecasting methods.
E) none of the above
Answer - D) simulation forecasting methods.
Simulation: Simulation forecasting methods imitate the consumer choices that give rise to demand to arrive at a forecast. Using simulation, a firm can combine time-series and causal methods to answer such questions as: What will be the impact of a price promotion?
26) Qualitative forecasting methods are most appropriate when
A) there is good historical data available.
B) there is little historical data available.
C) experts do not have critical market intelligence.
D) forecasting demand into the near future.
E) trying to achieve a high level of detail.
Answer - B) there is little historical data available.
Qualitative: Qualitative forecasting methods are primarily subjective and rely on human judgment. They are most appropriate when little historical data is available or when experts have market intelligence that may affect the forecast. Such methods may also be necessary to forecast demand several years into the future in a new industry.
27) Time series forecasting methods are most appropriate when
A) there is little historical data available.
B) the basic demand pattern varies significantly from one year to the next.
C) the basic demand pattern does not vary significantly from one year to the next.
D) experts have critical market intelligence.
E) forecasting demand several years into the future.
C) the basic demand pattern does not vary significantly from one year to the next.
Time series: Time-series forecasting methods use historical demand to make a forecast. They are based on the assumption that past demand history is a good indicator of future demand. These methods are most appropriate when the basic demand pattern does not vary significantly from one year to the next. These are the simplest methods to implement and can serve as a good starting point for a demand forecast.
28) Which forecasting methods are the simplest to implement and can serve as a good starting point for a demand forecast?
A) Qualitative forecasting methods
B) Time series forecasting methods
C) Causal forecasting methods
D) Simulation forecasting methods
E) none of the above
B) Time series forecasting methods
Time series: Time-series forecasting methods use historical demand to make a forecast. They are based on the assumption that past demand history is a good indicator of future demand. These methods are most appropriate when the basic demand pattern does not vary significantly from one year to the next. These are the simplest methods to implement and can serve as a good starting point for a demand forecast.
29) Which of the following is not a step to help an organization perform effective forecasting?
A) Understand the objective of forecasting.
B) Integrate demand planning and forecasting throughout the supply chain.
C) Understand and identify customer segments.
D) Identify and understand supplier requirements.
E) Determine the appropriate forecasting technique.
Answer - D) Identify and understand supplier requirements.
The following basic, six-step approach helps an organization perform effective forecasting.
1. Understand the objective of forecasting.
2. Integrate demand planning and forecasting throughout the supply chain.
3. Understand and identify customer segments.
4. Identify the major factors that influence the demand forecast.
5. Determine the appropriate forecasting technique.
6. Establish performance and error measures for the forecast.
30) The goal of any forecasting method is to
A) predict the random component of demand and estimate the systematic component.
B) predict the systematic component of demand and estimate the random component.
C) predict the seasonal component of demand and estimate the random component.
D) predict the random component of demand and estimate the seasonal component.
E) predict the trend component of demand and estimate the random component.
Answer - B) predict the systematic component of demand and estimate the random component.
The goal of any forecasting method is to predict the systematic component of demand and estimate the random component. In its most general form, the systematic component of demand data contains a level, a trend, and a seasonal factor.
Describe the basic characteristics of forecasts that managers should be aware.
1. Forecasts are always wrong and should thus include both the expected value of the forecast and a measure of forecast error.
2. Long-term forecasts are usually less accurate than short-term forecasts; that is, longterm forecasts have a larger standard deviation of error relative to the mean than short-term forecasts.
3. Aggregate forecasts are usually more accurate than disaggregate forecasts, as they tend to have a smaller standard deviation of error relative to the mean.
4. In general, the farther up the supply chain a company is (or the farther it is from the consumer), the greater is the distortion of information it receives.
The forecast of demand forms the basis for all strategic and planning decisions in a supply chain.
TRUE - Demand forecasts form the basis of all supply chain planning.
For pull processes, a manager must forecast what customer demand will be in order to plan the level of available capacity and inventory.
TRUE - For pull processes, a manager must plan the level of available capacity and inventory but not the actual amount to be executed. In both instances, the first step a manager must take is to forecast what customer demand will be.
The result when each stage in the supply chain makes its own separate forecast is often a match between supply and demand because these forecasts are often very different.
FALSE - When each stage in the supply chain makes its own separate forecast, these forecasts are often very different. The result is a mismatch between supply and demand. When all stages of a supply chain work together to produce a collaborative forecast, it tends
to be much more accurate. The resulting forecast accuracy enables supply chains to be both more responsive and more efficient in serving their customers
Leaders in many supply chains have started moving toward collaborative forecasting to improve their ability to match supply and demand.
TRUE - Leaders in many supply chains, from PC manufacturers to packaged-goods retailers, have improved their ability to match supply and demand by moving toward collaborative forecasting.
Mature products with stable demand are usually the most difficult to forecast.
FALSE - Mature products with stable demand, such as milk or paper towels, are usually easiest to forecast. Forecasting and the accompanying managerial decisions are extremely difficult when either the supply of raw materials or the demand for the finished product is highly unpredictable.
Forecasting and the accompanying managerial decisions are extremely difficult when either the supply of raw materials or the demand for the finished product is highly variable.
TRUE - Forecasting and the accompanying managerial decisions are extremely difficult when either the supply of raw materials or the demand for the finished product is highly unpredictable.
Forecasts should include both the expected value of the forecast and a measure of forecast error.
TRUE - Forecasts are rarely perfect so the forecasting studies should include both the expected value of the forecast and a measure of forecast error or demand uncertainty.
Aggregate forecasts are usually more accurate than disaggregate forecasts, as they tend to have a smaller standard deviation of error relative to the mean.
TRUE - Aggregate forecasts are usually more accurate than disaggregate forecasts, as they tend to have a smaller standard deviation of error relative to the mean. For example, it is easy to forecast the Gross Domestic Product (GDP) of the United States for a given year with less than a 2 percent error
Collaborative forecasting based on sales to the end customer can help enterprises further up the supply chain reduce forecast error.
TRUE - Collaborative forecasting based on sales to the end customer helps upstream enterprises reduce forecast error.
Qualitative forecasting methods are most appropriate when there is good historical data available or when experts do not have market intelligence that is critical in making the forecast.
FALSE
Time series forecasting methods are the most difficult methods to implement.
FALSE
Causal forecasting methods find a correlation between demand and environmental factors and use estimates of what environmental factors will be to forecast future demand.
TRUE
The forecast error measures the difference between the forecast and the estimate.
FALSE
The goal of any forecasting method is to predict the systematic component of demand and estimate the random component.
TRUE
In adaptive forecasting, the estimates of level, trend, and seasonality are updated after each demand observation.
TRUE
The moving average forecast method is used when demand has an observable trend or seasonality.
FALSE
Forecasting and the accompanying managerial decisions are extremely difficult when either the supply of raw materials or the demand for the finished product is highly unpredictable.
TRUE
Long-term forecasts have a larger standard deviation of error relative to the mean than short-term forecasts.
TRUE
The basis for all strategic and planning decisions in a supply chain comes from
the forecast of demand.
For push processes, a manager must forecast what customer demand will be in order to
plan the level of production.
The result of each stage in the supply chain making its own separate forecast is
a mismatch between supply and demand.
When all stages of a supply chain produce a collaborative forecast, it tends to be
much more accurate.
The resulting accuracy of a collaborative forecast enables supply chains to be
both more responsive and more efficient in serving their customers.
Leaders in many supply chains have started moving
toward collaborative forecasting to improve their ability to match supply and demand.
Production can utilize forecasts to make decisions concerning
scheduling.
Personnel can utilize forecasts to make decisions concerning
promotions.
Mature products with stable demand
are usually easiest to forecast.
When either the supply of raw materials or the demand for the finished product is highly variable, forecasting and the accompanying managerial decisions
are extremely difficult.
One of the characteristics of forecasts is
long-term forecasts are usually less accurate than short-term forecasts.
One of the characteristics of forecasts is
aggregate forecasts are usually more accurate than disaggregate forecasts.
Forecasts are always wrong and therefore
should include both the expected value of the forecast and a measure of forecast error.
Long-term forecasts are usually less accurate than short-term forecasts because
long-term forecasts have a larger standard deviation of error relative to the mean than short-term forecasts.
Aggregate forecasts are usually more accurate than disaggregate forecasts because
aggregate forecasts tend to have a smaller standard deviation of error relative to the mean.
In general, the further up the supply chain a company is (or the further they are from the consumer),
the greater the distortion of information they receive.
Forecasting methods that use historical demand to make a forecast are known as
time series forecasting methods.
Forecasting methods that assume that the demand forecast is highly correlated with certain factors in the environment (e.g., the state of the economy, interest rates, etc.) to make a forecast are known as
causal forecasting methods.
Forecasting methods that imitate the consumer choices that give rise to demand to arrive at a forecast are known as
simulation forecasting methods.
Qualitative forecasting methods are most appropriate when
there is little historical data available.
Which forecasting methods are the simplest to implement and can serve as a good starting point for a demand forecast?
Time series forecasting methods
The goal of any forecasting method is to
predict the systematic component of demand and estimate the random component.
________ forecasting methods assume that the demand forecast is highly correlated with certain factors in the environment (the state of the economy, interest rates, etc.).
Causal
________ forecasting methods are primarily subjective and rely on human judgment.
Qualitative
________ forecasting methods use historical demand to make a forecast.
Time-series
The multiplicative form of the systematic component of demand is shown as
level × trend × seasonal factor.
The additive form of the systematic component of demand is shown as
level + trend + seasonal factor.
The mixed form of the systematic component of demand is shown as
(level + trend) × seasonal factor.
A static method of forecasting
assumes that the estimates of level, trend, and seasonality within the systematic component do not vary as new demand is observed.
In adaptive forecasting,
the estimates of level, trend, and seasonality are updated after each demand observation.
The moving average forecast method is used when
demand has no observable trend or seasonality.
The simple exponential smoothing forecast method is appropriate when
demand has no observable trend or seasonality.
The trend corrected exponential smoothing (Holt's Model) forecast method is appropriate when
demand has observable trend but no seasonality.
Use a simple moving average of three periods to forecast the demand for July. What is the forecast?
45.3
Use exponential smoothing to forecast the demand for March. What is the forecast if α = 0.7?
27.5
What is the level component of Holt's model for period 0?
-2.5
The measure of forecast error where the amount of error of each forecast is squared and then an average is calculated is
mean squared error (MSE).
The measure of forecast error where the absolute amount of error of each forecast is averaged is
mean absolute deviation (MAD).
The measure of forecast error where the average absolute error of each forecast is shown as a percentage of demand is
mean absolute percentage error (MAPE).
The measure of whether a forecast method consistently over- or underestimates demand is
A) mean absolute deviation (MAD).
bias
The measure of how significantly a forecast method consistently over- or underestimates demand is
the tracking signal
Which of the following is a commonly used measure for measuring forecast error?
MAD
The ________ is a good measure of forecast error when the underlying forecast has significant seasonality and demand varies considerably from one period to the next.
MAPE
Calculate the MAD for this scenario if the forecasts for periods 1-10 are in order, 176.6, 174.2, 176.1, 178.7, 160.4, 165.4, 177.7, 191.1, 191.0, and 175.2.
11.04
Calculate the MSE for this scenario if the forecasts for periods 1-10 are in order, 176.6, 174.2, 176.1, 178.7, 160.4, 165.4, 177.7, 191.1, 191.0, and 175.2.
219.80
What is the largest value for the tracking signal (either under or overforecasting) if the forecasts for periods 1-10 are in order, 176.6, 174.2, 176.1, 178.7, 160.4, 165.4, 177.7, 191.1, 191.0, and 175.2?
2.58
What is the mean absolute percentage error if the forecasts for periods 1-10 are in order, 176.6, 174.2, 176.1, 178.7, 160.4, 165.4, 177.7, 191.1, 191.0, and 175.2?
5.6
Use Solver to determine the alpha that minimizes the MAD for the ten period forecast for the data that appear in this table. Use the actual demand as the forecast for period 1 and then use exponential smoothing.
0.5