Exam 5: Demand Forecasting

Given the following information, calculate the forecast (round to nearest whole number) for period four using exponential smoothing and =0.3. Use a tracking signal to determine if there is a bias problem with the forecasting method.(Assume the control limit for the tracking signal is ± 3.

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Question 1

Correct Answer:

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Since you do not have the forecast for periods 2 and 3, you must calculate those first in order to use them in calculating the forecast for period four.
F₂ = 1590 + .3(1620 - 1590) = 1599
F₃ = 1599 + .3(1680 - 1599) = 1623
F₄ = 1623 + .3(1720 - 1623) = 1652
RSFE = (1620 - 1590) + (1680 - 1599) + (1720 - 1623) + (1770 - 1652) = 326
MAD = 81.5
Tracking signal = 326/81.5 = 4
The results indicate a bias in the forecasts as the tracking signal is not within the control limits of ± 3.

The formula for the forecast error, is calculated by using the equation:

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Question 2

Correct Answer:

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The real value of Collaborative Planning, Forecasting and Replenishment (CPFR) comes from:

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Question 3

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A forecast tracking signal is used to determine:

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Question 4

The calculated forecast for May is 46, using the actual demand shown in the table below, and a 3-month weighted moving average with weights 0.1, 0.4, 0.5 (the heaviest weight applied to the most recent period).

(True/False)

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Question 5

The true value of CPFR comes from the sophisticated forecasting algorithms that provide companies with highly accurate forecasts, not from the exchange of forecasting information.

(True/False)

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Question 6

Without supply chain trading partners collaborating and exchanging information, the supply chain will always be suboptimal and contain excess inventories, resulting in less-than-maximum supply chain profits.

(True/False)

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Question 7

If you felt that recent demand trends were more significant, and thus should be emphasized more in formulating a forecast, then in forecasting demand for the upcoming demand period, you would probably favor using a simple moving average over the conventional weighted moving average.

(True/False)

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Question 8

Using the data set below, what would be the forecast for period 4 using a three period moving average: (Choose the closest answer.)

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Question 9

Using the actual demand shown in the table below, what is the forecast for May (accurate to 1 decimal) using a 3-month weighted moving average and the weights 0.20, 0.35, 0.45 (with the heaviest weight applied to the most recent period.Round to nearest whole number)?

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Question 10

List FOUR benefits that can be achieved by implementing a successful CPFR program.

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Question 11

All of the following may influence demand and should be considered when developing a forecast EXCEPT

(Multiple Choice)

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Question 12

Given the following information, calculate the forecast (round to nearest whole number) for period three using exponential smoothing and = 0.4.

(Multiple Choice)

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Question 13

Which of the following is a benefit of CPFR?

(Multiple Choice)

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Question 14

Individual biases could negatively impact the effectiveness of the Sales Force Composite forecasting approach, due to the proximity of the sales personnel to the consumers.

(True/False)

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Question 15

The Naïve forecast, Mean Profit Leverage, and Mean Square Error are examples of forecasting accuracy measures.

(True/False)

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Question 16

Using the data set below, what would be the forecast for period 5 using a four period weighted moving average? The weights for each period are 0.05, 0.15, 0.30, and 0.50 from the oldest period to the most recent period, respectively.(Choose the closest answer.)

(Multiple Choice)

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Question 17

Explain the key challenges of CPFR implementation.

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Question 18

Using the data set below, what would be the forecast for period 5 using the exponential smoothing method? Assume the forecast for period 4 is 14000.Use a smoothing constant =0.4 (Choose the closest answer.)

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Question 19

One of the benefits of CPFR include integration of planning, forecasting, and logistics activities.

(True/False)

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Question 20

Showing 1 - 20 of 59

Given the following information, calculate the forecast (round to nearest whole number) for period four using exponential smoothing and =0.3. Use a tracking signal to determine if there is a bias problem with the forecasting method.(Assume the control limit for the tracking signal is ± 3.

The formula for the forecast error, is calculated by using the equation:

The real value of Collaborative Planning, Forecasting and Replenishment (CPFR) comes from:

A forecast tracking signal is used to determine:

The calculated forecast for May is 46, using the actual demand shown in the table below, and a 3-month weighted moving average with weights 0.1, 0.4, 0.5 (the heaviest weight applied to the most recent period).

The true value of CPFR comes from the sophisticated forecasting algorithms that provide companies with highly accurate forecasts, not from the exchange of forecasting information.

Without supply chain trading partners collaborating and exchanging information, the supply chain will always be suboptimal and contain excess inventories, resulting in less-than-maximum supply chain profits.

If you felt that recent demand trends were more significant, and thus should be emphasized more in formulating a forecast, then in forecasting demand for the upcoming demand period, you would probably favor using a simple moving average over the conventional weighted moving average.

Using the data set below, what would be the forecast for period 4 using a three period moving average: (Choose the closest answer.)

Using the actual demand shown in the table below, what is the forecast for May (accurate to 1 decimal) using a 3-month weighted moving average and the weights 0.20, 0.35, 0.45 (with the heaviest weight applied to the most recent period.Round to nearest whole number)?

List FOUR benefits that can be achieved by implementing a successful CPFR program.

All of the following may influence demand and should be considered when developing a forecast EXCEPT

Given the following information, calculate the forecast (round to nearest whole number) for period three using exponential smoothing and = 0.4.

Which of the following is a benefit of CPFR?

Individual biases could negatively impact the effectiveness of the Sales Force Composite forecasting approach, due to the proximity of the sales personnel to the consumers.

The Naïve forecast, Mean Profit Leverage, and Mean Square Error are examples of forecasting accuracy measures.

Using the data set below, what would be the forecast for period 5 using a four period weighted moving average? The weights for each period are 0.05, 0.15, 0.30, and 0.50 from the oldest period to the most recent period, respectively.(Choose the closest answer.)

Explain the key challenges of CPFR implementation.

Using the data set below, what would be the forecast for period 5 using the exponential smoothing method? Assume the forecast for period 4 is 14000.Use a smoothing constant =0.4 (Choose the closest answer.)

One of the benefits of CPFR include integration of planning, forecasting, and logistics activities.

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