Test Bank Answers Forecasting And Demand Planning Chapter 8

File: ch08, Chapter 8: Forecasting and Demand Planning

Multiple Choice

1. __________ is the process of predicting future events.
2. Planning
3. Sales and Operations Planning
4. Sourcing
5. Forecasting
6. Finance

Level: Easy

1. The process of preparing for future events is__________:
2. Planning
3. Sales and Operations Planning
4. Sourcing
5. Forecasting
6. Finance

Level: Easy

1. Planning decisions include:
2. Resource scheduling
3. Acquiring new resources
4. Whether to outsource
5. Sales plans
6. a and b

Level: Medium

1. When determining future resource needs, factors that should be considered include:
2. Growth of supply chain management
3. Impact of new technologies
4. Competitor actions
5. Existing distribution channels
6. b and c

Level: Medium

1. The process of influencing demand is called:
2. Sales and Operations Planning
3. CPFR
4. Demand management
5. Forecasting
6. Planning

Level: Easy

1. Forecasting impacts the operations function in the following ways:
2. Inventory levels
3. Sources of supply
4. Advertising and promotions
5. Asset acquisition
6. None of the above

Level: Medium

1. An outcome of supply chain partners creating independent forecasts could be:
2. Improved inventory management
3. Improved coordination
4. Bullwhip effect
5. Increased sales
6. a and c

Level: Difficult

1. Ways to mitigate the bullwhip effect include:
2. Data sharing
3. Collaborative forecasting
4. Supplier management
5. Independent forecasting
6. a and b

Level: Difficult

1. __________ forecasts are more accurate than individual forecasts.
2. Qualitative
3. Quantitative
4. Stable
5. Aggregate
6. Causal

Level: Difficult

1. Forecasts are critical to predicting future events, but they are rarely _______ :
2. Useful
3. Accurate
4. Perfect
5. Quantitative
6. Qualitative

Level: Easy

1. Forecasts are more accurate for _________ time horizons:
2. Short
3. Medium
4. Long
5. Annual
6. None of the above

Level: Medium

1. Examples of data patterns that must be considered when forecasting include:
2. Cluster
3. Horizontal
4. Cycle
5. Qualitative
6. b and c

Level: Medium

1. A ________ data pattern is commonly seen an utilized for commodity products:
2. Trend
3. Seasonal
4. Cycle
5. Horizontal
6. Cluster

Level: Difficult

1. The type of data pattern that emerges in times of economic fluctuations is:
2. Trend
3. Seasonal
4. Cycle
5. Horizontal
6. Level

Level: Medium

1. Sophisticated and costly forecasting models would be most appropriate for which product:
2. Paper clips
3. Pencils
4. Smartphones
5. Diapers
6. None of the above

Level: Medium

1. Advantages of quantitative forecasting methods include:
2. Objectivity
3. Responsiveness
4. Includes ‘inside’ information
5. Expensive
6. b and c

Level: Medium

1. Market research is an example of ___________ forecasting method:
2. Quantitative
3. Seasonal
4. Jury of executive opinion
5. Causal
6. Qualitative

Level: Medium

1. Examples of quantitative forecasting models include:
2. Time series
3. Delphi
4. Causal
5. Mean
6. a and c

Level: Medium

1. The mean and moving average forecasting models are typically best for _________ products:
2. Innovative
3. Mature
4. New
5. Functional
6. None of the above

Level: Difficult

1. __________ analysis measures the relationship between two or more variables on the forecast:
2. Qualitative
3. Quantitative
4. Time series
5. Linear Regression
6. Delphi

Level: Medium

1. Two measures of forecast accuracy include:
2. Mean deviation
3. Mean absolute deviation
4. Mean square error
5. a and c
6. b and c

Level: Easy

1. Joint forecasting between supply chain partners is known as:
2. Vendor managed inventory
3. Collaborative planning, forecasting, and replenishment
4. Early supplier involvement
5. Sales and operations planning
6. None of the above

Level: Easy

1. Benefits of joint forecasting between supply chain partners include:
2. Risk sharing
3. Improve customer value
4. Higher sales
5. Decrease inventory
6. All of the above

Level: Medium

1. ______________ is a process by which supply chain functions within an organization collaborate to match supply and demand:
2. Vendor managed inventory
3. Collaborative planning, forecasting, and replenishment
4. Early supplier involvement
5. Sales and operations planning
6. None of the above

Level: Easy

1. Benefits of sales and operations planning include:
2. Understanding of trade-offs in an organization
3. Balanced metrics
4. Collaboration
5. All of the above
6. None of the above

Level: Easy

True/False

1. Forecasting is the process of predicting future events.

Level: Easy

1. The planning process allows a business to be prepared for future events.

Level: Easy

1. Forecasting and planning are especially important given customers’ increasing demands for responsiveness.

Level: Medium

1. Understanding how new market opportunities and competitors could impact a firm are part of the planning decision process.

Level: Medium

1. Advertising and promotions are examples of demand management.

Level: Easy

1. The forecasting process cam impact long range and tactical plans.

Level: Easy

1. An example of the impact of forecasting on marketing is the decision to enter a new market.

Level: Easy

1. An example of the impact of forecasting on finance is scheduling capacity in the plant.

Level: Medium

1. It is important for all members of a supply chain to develop independent forecasts.

Level: Difficult

1. The bullwhip effect is a result of collaborative forecasting and planning.

Level: Difficult

1. Sharing demand and forecast data with supply chain partners can help mitigate the bullwhip effect.

Level: Medium

1. A principle of forecasting is that uncertainty cannot be tolerated.

Level: Medium

1. Aggregate forecasts are more accurate than individual forecasts.

Level: Medium

1. Longer term forecasts are more accurate because a business has more time to adjust the forecast.

Level: Difficult

1. Seasonality and cycles are examples of forecasting data types.

Level: Easy

1. A horizontal data pattern typically occurs with demand patterns for a new product.

Level: Difficult

1. When selecting a forecasting model, a key consideration relates to the type of data available.

Level: Easy

1. When forecasting ‘functional’ products, it is typically best to invest in a sophisticated model.

Level: Difficult

1. Qualitative forecasting methods rely heavily on data sets.

Level: Easy

1. Quantitative forecasting methods tend to be more accurate than qualitative methods.

Level: Easy

1. Qualitative forecasting methods have the advantage of being objective and consistent.

Level: Medium

1. Responsiveness to changes in the environment is an advantage of qualitative forecasting methods.

Level: Medium

1. The Delphi method is an example of a qualitative forecasting method.

Level: Easy

1. A time series forecasting model evaluates data points over a period of time.

Level: Easy

1. Utilizing the mean forecasting model is best for mature, stable products.

Level: Medium

1. Exponential smoothing allows a forecast to put greater or less weight on certain data points.

Level: Medium

1. The key idea of regression analysis is the ability to measure the relationship between two or more variables on the forecast.

Level: Medium

1. Determining the accuracy of a forecast is as important as the forecast itself.

Level: Medium

1. CPFR is a five step process by which supply chain partners generate joint forecasts.

Level: Medium

1. Sales and Operations Planning is a process by which supply chain functions within an organization collaborate to match supply and demand.

Level: Medium

Essay

1. The ABC Company sells computers. Monthly sales for a six-month period are as follows:

Compute the sales forecast for July using the following approaches:
a. Mean
b. Four month simple moving average
c. Exponential smoothing with an alpha smoothing constant = .70 and a June forecast of 22,000

Level: Medium

1. The owner of the Chocolate Outlet store wants to forecast chocolate demand. Demand for the preceding six weeks is shown in the following table:

1. Compute the demand (pounds) forecast for week 7 using the following approaches:
   a. Mean
   b. Three week weighted moving average using .40 for week 6; .40 for week 5; and .20 for week 4
   c. Exponential smoothing with an alpha smoothing constant = .60 and a week 6 forecast of 70,000

1a.) Mean: 68,800 + 71,000 + 75,500 + 71,200 + 65,000 + 60,000/6 = 68,550
1b.) Three week weighted moving average = 60,000(.4) + 65,000(.4) + 71,200(.2) = 64,240
1c.) Exponential smoothing: .6(60,000) + .4(70,000) = 64,000
Response: page 169-172
Level: Difficult