MPR Chapter 2: Forecasting Demand

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Sandy2015
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MPR Chapter 2: Forecasting Demand
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2015-10-05 14:26:14
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Forecasting Demand MPR
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Forecasting Demand
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This is chapter 2 of MRP
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  1. True or false
    Cost of forecast at the strategic level reflects emphasis on causal or regression techniques.
    true
  2. True or false
    Level of executive involvement, forecast aggregation, frequency, and horizon vary in accordance with the requirements of strategic and business planning, S&OP, and master production scheduling
    true
  3. True or false
    The master production scheduling horizon can be days for some products but usually are several weeks in length
    true
  4. True or false
    Executive involvement in sales and operations planning reconciles the functional plans of finance, sales, manufacturing, hr, engineering, and so on
    True
  5. True or False:
    Executive involvement can minimize the business risk of not getting the forecasts right, especially at the strategic planning level
    True
  6. True or False:

    As MPC moves from strategic planning to master production scheduling, forecasts need to be more detailed, require less executive management direction  and are better served by some forecasting techniques than others.
    True
  7. For Strategic and business planning, Quantitative techniques include things like
    regression analysis
  8. For strategic and business planning, Qualitative techniques are:
    market research, expert opinion, and management estimation
  9. T or F
    Forecasting for strategic and business planning is short term range, consistent with lead time needed to implement the kinds of things in strategic and business plans
    • False
    • Forecasting for strategic and business planning is long range....
  10. For S&OP, quantitative techniques include
    time series forecasts, including decomposition, and causal techniques such as regression analysis
  11. For S&OP, quantitative techniques are
    expert opinion, pyramid, focus group, and Delphi
  12. What is pyramid forecasting?
    • A Technique that combines quantitative and qualitative elements, used in S&OP, and includes the following forecasts:
    • a. Sales and marekting
    • b. Product family
    • c. Business level forecast at the corporate level
    • d. Assures consistency among strategic direction, marketing and sales, and use of manufacturing resources.
  13. To calculate a force down forecast, what ratio do you use?
    management forecast over the  rollup forecast sales dollars.

    You use this ratio and multiply each element by the ratio.
  14. What three factors are the key to successful forecasting?
    • 1. people
    • 2. Data
    • 3. Software
  15. Explain the principles for ownership of the forecast
    Whoever develops the forecast needs to be the one responsible for executing it and by extension the one who owns it. The demand planner.
  16. How long is the forecast horizon for S&OP?
    Varied depending on order fulfillment lead time for the product lines. Could be several months to a year or more. 

    Forecasts accommodate incremental capacity, workforce adjustments, engineering lead time
  17. How long is the forecast horizon for strategic and business planning?
    Can be 3 years or longer

    Forecasts include data at a high level and highly qualitative, and a major objective is to determine long term resource and capacity needs that require long lead time.
  18. What is the forecast horizon for master scheduling?
    Forecast is derived from the sales and operations plan by dividing the months up through the planning time fence and slightly beyond, into weeks by 4, 4.3, and 5
  19. What is the forecast horizon for the annual budget and financial planning?
    3 months before the start of the budget year so it needs to span 15 months. 

    it must roll 12 months
  20. What is forecast interval?

    A) Forecast is derived from the sales and operations plan by dividing the months up through the planning time fence and slightly beyond, into weeks by 4, 4.3, and 5
    B) Forecast is derived from the sales and operations plan by dividing the months up through the planning time fence and slightly beyond, into weeks by 4, 4.3, and 5
    C) the duration of the time period used in the forecast
    D) time series forecasts, including decomposition, and causal techniques such as regression analysis
    C) the duration of the time period used in the forecast
    (this multiple choice question has been scrambled)
  21. What are the advantages and disadvantages to using a quarterly forecast interval?
    appropriate in industries with long production lead times, as in Engineered to order environments. May hide seasonal demand patterns but are good for mutliyear forecasts.
  22. What are the advantages and disadvantages to using a monthly forecast interval?
    Its not too detailed and gives an adequate level of precision. Allows detection of seasonal patterns that are hidden in quarterly intervals
  23. what are the advantages and disadvantages of using a weekly interval?
    weekly is necessary for master scheduling and can be achieved by dividing the monthly product family forecasts into weekly buckets. 

    it can give a false sense of precision
  24. What does the term forecasting model pertain to?
    judgmental and quantitative methods used in forecasting, and especially to statistical and mathematical ones.
  25. What forecasting model would you use for high volume and high variance?
    Aggregate forecast and then assemble to order
  26. What forecasting model would you use for low volume, low variance?
    Aggregate forecast and inventory then Make to order
  27. How do you calculate the coefficient of variation (CV)?
    Standard deviation of period demand over average period demand.
  28. What forecasting model would you use for high volume and high variance?
    High risk of obsolete inventory, check profitability, and move to Make to order only
  29. What forecasting model would you use for high volume and low variance?
    use statistical forecasting techniques and Make to stock
  30. Describe the eight steps of the forecasting process
    • 1. Data gathering and preparation
    • 2. Forecast generation
    • 3. Volume and mix reconciliation #1
    • 4. Applying judgement
    • 5. Volume and mix reconciliation #2
    • 6. Decision making and authorization
    • 7. Volume and mix reconciliation #3
    • 8. Documenting assumptions.
  31. What do qualitative techniques consist of?
    subjective or judgmental techniques
  32. What are two quantitative methods for forecasting?
    • 1. Time Series (intrinsic)
    • 2. Causal (extrinsic)
  33. What are the two main categories of forecasting techniques
    Quantitative and Qualitative
  34. What are internal forecasting factors?
    • Things you can control like
    • new products
    • product life cycle
    • pricing and promotions
    • bids
    • historical data
    • management judgement
    • intra-company demand
  35. What are external forecasting factors?
    Things you cannot control

    • customers
    • competition
    • economic outlook and demographics
    • disruptive events
    • market life cycle
    • emerging technology
  36. What are Qualitative techniques?
    • Expert opinion
    • management estimation
    • pyramid forecasting
    • focus groups
    • survey
    • panel consensus
    • delphi technique
    • sales force composite
    • product life cycle analysis
  37. What are Causal (extrinsic) forecasting techniques?
    • Regression
    • Multiple regression
  38. What are Time Series  (intrinsic) forecasting techniques?
    • Simple average
    • moving average
    • Exponential smoothing 
    • Time series decomposition
  39. In the decline stage, what are sales doing?
    lower and/or declining sales and product line simplification
  40. In the mature stage, what do sales typically look like?
    more competition, continuous demand that is gradually rising, level or gradually falling
  41. In the introduction and growth states what do wales look like for a first mover?
    high initial sales growth
  42. What are the 5 categories of qualitative forecasting techniques?
    • 1. independent judgement of experts
    • 2. judgments of executives and managers
    • 3. market research relating to specific customer groups in specific markets
    • 4. sales estimates made by the sales force
    • 5. historical analogy
  43. What are the disadvantages of qualitative techniques?
    • 1. Bias and overconfidence
    • 2. Incomplete supporting documentation
    • 3. not practical when organizations have thousands of stockkeeping units
    • 4. Adverse effect of peer pressure in group decision making.
  44. What are the advantages of qualitative techniques?
    • Qualititative techniques are useful when:
    • 1. Initial quantifiable data are lacking
    • 2. demand patterns and relationships are highly unstable
    • 3. Strong need exists for executive and expert insight
    • 4. long term forecasting needs behavioral insights from market research
    • 5. sales forecasts need to be assembled quickly
  45. Explain the inter-dependency between qualititative and quantitative forecasts.
  46. What is Simple average?
    SAF - Simple average forecast

    The forecast for a period is the average of actual demand for the last two periods.
  47. What is weighted moving average forecast?
    Forecasters will weight actual demand values int he time series to determine a forecast that approximates the demand pattern
  48. What is simple and moving average forecasts?
    • MAF techniques:
    • Objective is the smooth or average past demand to forecast future demand. 

    Sum of the past X periods /X = forecast for next period
  49. When are time series techniques used?
    When historical demand patterns can be assumed to continue into the future
  50. What is exponential smoothing forecasting?
    ESF - enables forecasters to assign weights to historical and current demand data and to calculate forecasts that take into account trend and seasonality.
  51. If you have a medium to high smoothing constant, alpha, what demand pattern do you have?
    Demand shows trend with low variability
  52. If you have a low - medium smoothing constant, alpha, what demand pattern do you have?
    Demand shows trend with volatility.
  53. If you have a low smoothing constant, alpha, what is the demand pattern?
    Demand is random with low variability
  54. Time series decomposition can be divided into 4 components
    • 1. trend
    • 2. seasonal
    • 3. cyclical
    • 4. random (no pattern)
  55. How do you calculate trend adjusted seasonal forecasts?
    The trend adjusted seasonal factors based on averaging same quarter ratios
  56. How do you calculate the trend ratio?
    Actual divided by trend
  57. What do quantitative forecasting techniques that consist of causal techniques apply in forecasting?
    • 1. Analyze and predict based on relationships between event or occurrences, such as housing starts or sales of central ac
    • 2. attempt to explain and quantify the relationships in order to predict demand in the future.
  58. What do quantitative intrinsic techniques focus on?
    • 1. Analyzing time series data
    • 2. decomposition of demand patterns into trend, seasonal, cyclical, and random demand patterns.
    • 3. determining the mathematical relationships within the data and demand patterns and extending them into the future.
  59. Causal Techniques attempt to quantify the relationship between two types of events. What are they?
    • 1. The predictor or independent variable. This is the cause of or influence on the 2nd event.
    • 2. The Predicted or Dependent variable. You could call this the effect or the associated effect.
  60. What are some advantages of causal analysis?
    • 1. Relate internal and external factors to forecasts
    • a. Effects of promotions on sales
    • b. Market acceptance rates for new products
    • c. Use of leading indicators

    2. Provide key insights into time series data

    • 3. Are effective in long term forecasting
    • 4. Are excellent at predicting aggregate demand
    • 5. Are available in many software packages.
  61. What are disadvantages of causal analysis?
    • 1. Are sensitive to changes in relationships between variables.
    • 2. Require high levels of external data collection
    • 3. Require diverse numerical and behavioral data.
    • 4. Have high data management, modeling, and storage costs.
    • 5. Are seldom used in short term forecasts
    • 6. Require extensive training in statistics.
  62. What is Multiple regression analysis?
    Forecasts based on relationships between more than one independent and one dependent variable

    Models past relationships between more than one independent variable and a dependent variable.

    • a. has much higher computational requirements than single regression
    • b. Simultaneously measures the relationship between several variables and the dependent value, leading to a more robust forecast.
  63. What is simple regression analysis?
    Forecasts based on relationships between an independent and dependent variable.

    • Models past relationships between an independent and dependent variable. 
    • a. identifies the relationship between the variables
    • b. Measures the error in using the relationship to predict values of the dependent variable.
    • c. Measures the degree of association between the two variables.
    • d. Calculates the degree of forecast error.
  64. Summarize the value proposition of collaborative planning, forecasting, and replenishment (CPFR)
    • The objective was to
    • 1. use one set of numbers in planning and forecasting by manufacturers and retailers.

    2. Adopt standards for electronic communication and sharing of data.
  65. What are the two aspects to CPFR?
    1. Business process model in which parties electronically exchange written comments and data on demand trends, schedules, promotions, and forecasts.

    2. Set of standards for electronic communication of data among the participating supply chain partners , which is beyond the scope of this course.
  66. True or false:

    The voluntary interindustry commerce standards association has the standards of CPFR model.
    True
  67. The CPFR model sets guidelines for collaboration at four levels of the partnering enterprises.
    • 1. Strategy and planning
    • 2. Demand and supply management
    • 3. Execution
    • 4. Analysis
  68. In CPFR, Strategy and planning guidelines for collaboration are:
    1. Collaboration arrangement (planning) - setting of business goals, scope of collaboration, and roles and responsibilities of the partners

    2. Joint business plan - identifying significant events such as promotions, inventory policy changes, store openings, and product introductions.
  69. In CPFR, demand and supply management guidelines for collaboration are:
    • 1. Sales forecasting - analysis of market data by the manufacturer and point of sale data by the retailer
    • 2. order planning and forecasting - demand planning by the manufacturer and replenishment planning by the retailer.
  70. In CPFR, execution management guidelines for collaboration are:
    1. Order generation - production and supply planning by the manufacturer; buying activities by the retailer

    2. Order fulfillment - logistics and distribution management, both by the manufacturer and retailer
  71. In CPFR, Analysis guidelines for collaboration are:
    1. Exception management - execution monitoring by the manufacturer; store execution by the retailer

    2. performance assessment - keeping of scorecards.
  72. A collaboration process whereby supply chain trading partners can jointly plan key supply chain activities from production and delivery of raw materials to production and delivery of final products to end customers.
    CPFR
  73. A moving average where the oldest data point is dropped and the newest data point is included in the calculation
    Simple moving average
  74. A type of weighted moving average forecasting technique in which past observations are geometrically discounted according to their age.
    Exponential smoothing forecast
  75. An approach to forecasting where historical demand data is used to project future demand
    Quantitative forecasting techniques
  76. An averaging technique in which the data to be averaged are not uniformly weighted but are given values according to their importance
    weighted moving average
  77. A number used to adjust data to seasonal demand
    seasonal index
  78. Analysis of any variable classified by time in which the values of the variable are functions of the time periods
    time series analysis
  79. A method of forecasting where time series data are separated into up to three components: trend, seasonal, and cyclical; where trend includes the general horizontal upward or downward movement over time;seasonal includes a recurring demand pattern such as day of the week, weekly, monthly, or quarterly; and cyclical includes any repeating, nonseasonal pattern
    Decomposition
  80. A type of forecasting that uses cause and effect associations to predict and explain relationships between the independent and dependent variables
    Causal forecast
  81. A statistical technique for determining the best mathematical expression describing the functional relationship between one response and one or more independent variables
    Regression analysis
  82. Forecasts for products that are subject to promotional demand are most useful if they are based on

    A) Causal forecast
    B) time series analysis
    C) both quantitative and qualitative factors
    D) time series forecasts, including decomposition, and causal techniques such as regression analysis
    C) both quantitative and qualitative factors
    (this multiple choice question has been scrambled)
  83. Statistical forecasting provides the best solution in which of the following situations in an MTS environment?

    A) Forecast is derived from the sales and operations plan by dividing the months up through the planning time fence and slightly beyond, into weeks by 4, 4.3, and 5
    B) the duration of the time period used in the forecast
    C) Sales volume is high and forecast variance is low.
    D) Decomposition
    C) Sales volume is high and forecast variance is low.
    (this multiple choice question has been scrambled)
  84. Which of the following is most directly affected by forecast inaccuracy?

    A) Sales volume is low and forecast variance is low
    B) Regression analysis
    C) Planned finished goods inventory level in an MTS environment
    D) Aggregate forecast and inventory then Make to order
    C) Planned finished goods inventory level in an MTS environment
    (this multiple choice question has been scrambled)
  85. Which of the following qualitative methods of forecasting should a company consider for a product that is replacing another?

    A) Establishment of the firm planning time fence in master schedule
    B) Aggregate forecast and then assemble to order
    C) Historical analogy
    D) Causal forecast
    C) Historical analogy
    (this multiple choice question has been scrambled)
  86. Seasonality is demand that shows which of the following patterns?

    A) Historical analogy
    B) Demand shows trend with volatility.
    C) Causal forecast
    D) Repetitive pattern over some time interval
    D) Repetitive pattern over some time interval
    (this multiple choice question has been scrambled)
  87. Which of the following techniques is best suited to forecasting demand when the demand pattern shows seasonal and trend components?

    A) more competition, continuous demand that is gradually rising, level or gradually falling
    B) Historical analogy
    C) Decomposition
    D) regression analysis
    C) Decomposition
    (this multiple choice question has been scrambled)
  88. Which of the following responses is the company most likely to consider when establishing the forecast for a new item being added to an MTS product line?

    A) Evaluate the sales promotion effect of the new item on sales of existing products
    B) Reduce the alpha factor so that downward trending demand in recent periods is more heavily weighted.
    C) Adopt pyramid forecasting in order to evaluate the importance of the new item above its family members
    D) Apply quantitative analysis techniques based on leading economic indicators to establish short term forecasts
    A) Evaluate the sales promotion effect of the new item on sales of existing products
  89. In which of the following processes are qualitative techniques appropriately used?

    A) extrapolation of essentially level data
    B) Detection of a demand increase or decrease
    C) Determination of a seasonal index
    D) Pyramid forecating
    D) Pyramid forecating
    (this multiple choice question has been scrambled)
  90. Which of the following quantitative techniques responds the most quickly to trends?
    A. moving average
    B. high alpha factor exponential smoothing
    C. expert opinion
    D. seasonal index
    B. high alpha factor exponential smoothing
    (this multiple choice question has been scrambled)
  91. Given the following information, calculate the new forecast for Product A using exponential smoothing.

    Alpha factor - 0.7
    Actual Demand 600
    Old forecast 562
    Seasonal index 2.1
    • Alpha (AD) + (1-alpha) Old Forecast
    • 0.7(600) + (1-0.7) 562 = 589

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