Quiz: Demand Forecasting Methods In Supply Chain

30 Questions | Total Attempts: 489

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Quiz: Demand Forecasting Methods In Supply Chain - Quiz

Go through the below quiz to check what you know about demand forecasting methods in supply chain management. Demand forecasting refers to ensuring what customer demand will look like in the future with a vision of how it will affect the business's supply chain. Here, you will be asked questions related to different types of forecasting. So, take your time and choose answers carefully, as at the end of this quiz, you'll get a certificate based on your scores.


Questions and Answers
  • 1. 
    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

  • 2. 
    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

  • 3. 
    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

  • 4. 
    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

  • 5. 
    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 Variation

    • C. 

      Random Variation

    • D. 

      Seasonal Variation

  • 6. 
    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 Variaitons

    • C. 

      Season Variations

    • D. 

      Random Variations

  • 7. 
    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

  • 8. 
    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

  • 9. 
    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

  • 10. 
    Which one of the following is NOT a type of qualitative forecasting?
    • A. 

      Sales composite

    • B. 

      Consumer survey

    • C. 

      Jury of executive opinion

    • D. 

      Simple moving average

  • 11. 
    Quantitative forecasts use mathematical techniques that are based on:
    • A. 

      Expert opinions

    • B. 

      Surveys

    • C. 

      Historical data

    • D. 

      Sales knowledge of the market

  • 12. 
    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

  • 13. 
    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

  • 14. 
    Using the data set below, what would be the forecast for period 4 using a three period moving average:
    • A. 

      11500

    • B. 

      11883

    • C. 

      12244

    • D. 

      14008

  • 15. 
    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
    • A. 

      12820

    • B. 

      13105

    • C. 

      13710

    • D. 

      14610

  • 16. 
    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 of  = 0.4
    • A. 

      12660

    • B. 

      13190

    • C. 

      14030

    • D. 

      15220

  • 17. 
    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
    • A. 

      51

    • B. 

      56

    • C. 

      62

    • D. 

      68

  • 18. 
    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

  • 19. 
    The smoothing constant for exponential smoothing must be?
    • A. 

      Positive

    • B. 

      Negative

    • C. 

      Between 0 and 1

    • D. 

      Greater than 1

  • 20. 
    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

  • 21. 
    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

  • 22. 
    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

  • 23. 
    What is considered an acceptable range for a tracking signal?
    • A. 

      ±1

    • B. 

      ±2

    • C. 

      ±3

    • D. 

      ±10

  • 24. 
    A forecasting method has produced the following data over the past 5 months shown in the data set. What is the mean absolute deviation
    • A. 

      0

    • B. 

      1.2

    • C. 

      2.0

    • D. 

      2.4

  • 25. 
    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. 

      .8

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