Deck 5: Demand Forecasting
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Deck 5: Demand Forecasting
1
Minimizing the negative impacts of the bullwhip effect on supply chains is one of the goals of an effective CPFR system.
True
2
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.
False
3
The Naïve forecast, Mean Profit Leverage, and Mean Square Error are examples of forecasting accuracy measures.
False
4
As tighter control limits are instituted for the tracking signal, there is a greater probability of finding exceptions that require no action, but it also means catching changes in demand earlier.
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5
Random variations represent either increasing or decreasing movements over many years due to factors such as population growth, population shifts, cultural changes and income shifts.
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6
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.
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7
One of the benefits of CPFR include integration of planning, forecasting, and logistics activities.
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8
Cyclical variations are longer than a year and are influenced by macroeconomic and political factors.
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9
Regression analysis is commonly used in the cause-and-effect forecasting model.
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10
Toymaker Spin Master, did not properly forecast demands for their new product, Hatchimals, in 2016.This caused stockouts for their distributors.
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11
It is possible to expect 100 percent forecast accuracy most of the time.
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12
The goal of a good forecasting technique is to minimize the deviation between actual demand and the forecast.
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13
Trend variations are wavelike movements that are shorter than a year.
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14
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.
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15
Given the following information, the forecast for period two using exponential smoothing an
= 0.3 is 60.5.



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16
Forecast error is the actual quantity minus the forecast.
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17
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).


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18
The Delphi forecasting approach is applicable for high-risk technology forecasting; large, expensive projects; or major new product introductions
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19
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.
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20
Quantitative forecasting methods are based on opinions and intuition, whereas qualitative forecasting methods use mathematical models and relevant historical data to generate forecasts.
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21
Which one of the following is NOT a type of qualitative forecasting?
A) Sales force composite
B) Consumer survey
C) Jury of executive opinion
D) Simple moving average
A) Sales force composite
B) Consumer survey
C) Jury of executive opinion
D) Simple moving average
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22
Given the following information, calculate the forecast (round to nearest whole number) for period three using exponential smoothing and
= 0.4. 
A) 60
B) 65
C) 68
D) 71


A) 60
B) 65
C) 68
D) 71
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23
Using the data set below, what would be the forecast for period 4 using a three period moving average: (Choose the closest answer.) 
A) 11500
B) 11883
C) 12244
D) 14008

A) 11500
B) 11883
C) 12244
D) 14008
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24
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)?

A) 51
B) 56
C) 62
D) 68

A) 51
B) 56
C) 62
D) 68
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25
Random variations in a Time Series component are due to:
A) Population growth
B) Unpredictable events
C) Using a large value for the exponential smoothing constant
D) Inaccurate responses of the expert participants
A) Population growth
B) Unpredictable events
C) Using a large value for the exponential smoothing constant
D) Inaccurate responses of the expert participants
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26
When there is not a lot of currently relevant data available it is generally best to use:
A) Qualitative forecasting
B) Time series forecasting
C) Naive forecasting
D) Simple moving average forecasting
A) Qualitative forecasting
B) Time series forecasting
C) Naive forecasting
D) Simple moving average forecasting
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27
What component of a time series has variations in demand which show peaks and valleys that repeat over a consistent interval such as hours, days, weeks, months, or years?
A) Trend Variations
B) Cyclical Variations
C) Random Variations
D) Seasonal Variations
A) Trend Variations
B) Cyclical Variations
C) Random Variations
D) Seasonal Variations
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28
Quantitative forecasts use mathematical techniques that are based on:
A) Expert opinions
B) Surveys
C) Historical data
D) Sales force knowledge of the market
A) Expert opinions
B) Surveys
C) Historical data
D) Sales force knowledge of the market
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29
Your company is conducting forecasting that revolves around population growth in large cities.This type of forecasting can be referred to as what component of a time series?
A) Cyclical Variations
B) Trend Variations
C) Seasonal Variations
D) Random Variations
A) Cyclical Variations
B) Trend Variations
C) Seasonal Variations
D) Random Variations
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30
The impact of poor communication and inaccurate forecasts resonates along the supply chain and results in the:
A) Bullwhip effect
B) Delphi method
C) CPFR effect
D) Mean deviation
A) Bullwhip effect
B) Delphi method
C) CPFR effect
D) Mean deviation
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31
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.) 
A) 12820
B) 13105
C) 13710
D) 14610

A) 12820
B) 13105
C) 13710
D) 14610
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32
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.)

A) 12660
B) 13190
C) 14030
D) 15220


A) 12660
B) 13190
C) 14030
D) 15220
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33
When linear trend forecasts are developed, demand would typically be:
A) The independent variable
B) The dependent variable
C) The lead variable
D) The passive variable
A) The independent variable
B) The dependent variable
C) The lead variable
D) The passive variable
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34
Cyclical variations are longer than a year and can be influenced by:
A) Events such as natural disasters
B) Imbalances in supply and demand
C) Political factors
D) Population growth
A) Events such as natural disasters
B) Imbalances in supply and demand
C) Political factors
D) Population growth
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35
All of the following may influence demand and should be considered when developing a forecast EXCEPT
A) New competition
B) Supplier quality
C) Ergonomic conditions
D) Emerging markets
A) New competition
B) Supplier quality
C) Ergonomic conditions
D) Emerging markets
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36
In 2016, Spin Master, did not properly forecast demand for their new product, Hatchimals, causing ___________ for their distributors.
A) Excess stock
B) The bullwhip effect
C) Stockouts
D) Price reductions
A) Excess stock
B) The bullwhip effect
C) Stockouts
D) Price reductions
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37
CPFR is more likely to succeed if companies educate their employees on the benefits of the process changes and the disadvantages of maintaining the status quo.
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38
Inaccurate forecasts can result in negative outcomes like:
A) High inventory costs and increased profits
B) Imbalances in supply and demand
C) Material shortages and decreased costs of obsolescence
D) Low inventory costs and stockouts
A) High inventory costs and increased profits
B) Imbalances in supply and demand
C) Material shortages and decreased costs of obsolescence
D) Low inventory costs and stockouts
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39
The smoothing constant for exponential smoothing must be?
A) Positive
B) Negative
C) Between 0 and 1
D) Greater than 1
A) Positive
B) Negative
C) Between 0 and 1
D) Greater than 1
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40
The following time-series approach to forecasting uses historical data to generate a forecast and works well when demand is fairly stable over time:
A) Naïve Forecast
B) Weighted Moving Average
C) Simple Moving Average
D) Exponential Smoothing
A) Naïve Forecast
B) Weighted Moving Average
C) Simple Moving Average
D) Exponential Smoothing
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41
What is a tracking signal? How can managers use the information provided by the tracking signal to improve the quality of forecasts?
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42
What is considered an acceptable range for a tracking signal?
A) ±1
B) ±2
C) ±3
D) ±10
A) ±1
B) ±2
C) ±3
D) ±10
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43
Use the data set below to answer the questions that follow.
a.Find the four-period simple moving average forecasts for Periods 5 and 6.
b.Find the four-period weighted moving average forecasts for Periods 5 and 6 using weights of 0.05, 0.25, 0.30, and 0.40 from the earliest period to the latest period, respectively.
c.Which set of forecasts is more accurate, the simple moving average forecasts or the weighted moving average forecasts? Why is that set of forecasts more accurate in this particular case (using Data Set E4)?
d.Will that type of forecast always be more accurate? Why or why not?

a.Find the four-period simple moving average forecasts for Periods 5 and 6.
b.Find the four-period weighted moving average forecasts for Periods 5 and 6 using weights of 0.05, 0.25, 0.30, and 0.40 from the earliest period to the latest period, respectively.
c.Which set of forecasts is more accurate, the simple moving average forecasts or the weighted moving average forecasts? Why is that set of forecasts more accurate in this particular case (using Data Set E4)?
d.Will that type of forecast always be more accurate? Why or why not?
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44
According to the textbook, the top three challenges for CPFR implementation include all of the following EXCEPT:
A) Making organizational and procedural changes
B) Trust between supply chain partners
C) Cost
D) Supplier lead times
A) Making organizational and procedural changes
B) Trust between supply chain partners
C) Cost
D) Supplier lead times
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45
Explain the key challenges of CPFR implementation.
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46
The real value of Collaborative Planning, Forecasting and Replenishment (CPFR) comes from:
A) Sophisticated forecasting algorithms
B) Exchange of forecasting information
C) Both A and B
D) None of the above
A) Sophisticated forecasting algorithms
B) Exchange of forecasting information
C) Both A and B
D) None of the above
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47
Which of the following is a benefit of CPFR?
A) Provides an analysis of key performance metrics
B) Integrates planning, forecasting and logistics activities
C) Uses joint planning and promotions management
D) All of the above
A) Provides an analysis of key performance metrics
B) Integrates planning, forecasting and logistics activities
C) Uses joint planning and promotions management
D) All of the above
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48
A positive error implies that a forecast was?
A) Too low
B) Too high
C) Neither too high or too low
D) The sign of an error gives no information as to the direction of the error
A) Too low
B) Too high
C) Neither too high or too low
D) The sign of an error gives no information as to the direction of the error
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49
Which of the following is a major cultural issue and big hurdle for widespread implementation of CPFR?
A) There is no software available to use
B) Global economic changes
C) Trust
D) All of the above
A) There is no software available to use
B) Global economic changes
C) Trust
D) All of the above
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50
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.


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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51
Answer the following questions regarding quantitative and qualitative forecasting:
a.Define quantitative forecasting.
b.Explain the naïve forecasting method and give an example.
c.What are the benefits of using the naïve forecasting method?
d.Under which circumstances would one utilize a combination of both quantitative and qualitative forecasting?
a.Define quantitative forecasting.
b.Explain the naïve forecasting method and give an example.
c.What are the benefits of using the naïve forecasting method?
d.Under which circumstances would one utilize a combination of both quantitative and qualitative forecasting?
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52
What does the acronym CPFR represent?
A) Coordinated planning and forecasting relationships
B) Collaborative planning, forecasting, and replenishment
C) Centralized purchasing and forecasting relationships
D) Collaborative purchasing, forecasting, and receivables
A) Coordinated planning and forecasting relationships
B) Collaborative planning, forecasting, and replenishment
C) Centralized purchasing and forecasting relationships
D) Collaborative purchasing, forecasting, and receivables
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53
List FOUR benefits that can be achieved by implementing a successful CPFR program.
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54
A forecast tracking signal is used to determine:
A) If the product has shipped on time
B) The location of the current shipment
C) The price to charge for the product
D) If the forecast bias is within the acceptable control limits
A) If the product has shipped on time
B) The location of the current shipment
C) The price to charge for the product
D) If the forecast bias is within the acceptable control limits
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55
Based on the information in the data set below, what is the mean squared error (accurate to 1 decimal)? 
A) 8.0
B) 10.0
C) 1.00
D) 0.8

A) 8.0
B) 10.0
C) 1.00
D) 0.8
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56
The formula for the forecast error, is calculated by using the equation:
A) Actual demand for period t minus the forecasted demand for period t
B) Actual demand for period t divided by the forecasted demand for period t
C) Actual demand for period t plus the forecasted demand for period t
D) The average of Actual demand for period t and forecasted demand for period t
A) Actual demand for period t minus the forecasted demand for period t
B) Actual demand for period t divided by the forecasted demand for period t
C) Actual demand for period t plus the forecasted demand for period t
D) The average of Actual demand for period t and forecasted demand for period t
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57
List and Explain two types of qualitative forecasting methods.
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58
A forecasting method has produced the following data over the past 5 months shown in the data set.What is the mean absolute deviation (accurate to 1 decimals)? 
A) 10.0
B) -1.2
C) 2.0
D) 2.4

A) 10.0
B) -1.2
C) 2.0
D) 2.4
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59
The four components of time series data are: trend variations, cyclical variations, seasonal variations, and random variations.Briefly describe each type of variation.
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