Explain why forecasts form the basis of all supply chain decisions. How can Amazon use forecasting to
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Question:
- Explain why forecasts form the basis of all supply chain decisions.
- How can Amazon use forecasting to improve its responsiveness and efficiency?
- Why forecast error is a critical factor in any forecast? Explain your response with an example.
- What does forecast accuracy exactly mean? How can one measure it?
- We know that a shorter forecast horizon results in a more accurate forecast. However, long-term forecasts are also necessary (e.g., for capacity planning). How can a firm combine the short-term and long-term forecasts in their decision making?
- Explain in your own words what collaborative forecasting is.
- Give an example in auto-manufacturing industry for how human inputs can improve forecast accuracy.
- Explain the two components of any forecasting method.
- Give an example of a product for which the forecast should be made jointly with another product.
- How can a branch supermarket such as Trader Joes use aggregate forecasting?
- Briefly explain level, trend, and seasonal factor in demand forecasting.
- EXCEL:
- Replicate the Excel model in Figure 7-2.
- Use Excel Regression tool as explained on page 181 to run a regression model.
- Replicate the Excel model in Figure 7-4.
- SUBMIT YOUR EXCEL MODEL on Blackboard.
- Why should the data be first deseasonalized before running the regression?
- EXCEL: Consider the following demand data for periods 1 through 10.
- Use the moving average technique with N = 4 to forecast the demand for periods 1 to 11. You can use the actual demand () as the forecast for the first three periods (i.e., set , , and ).
1 | 142 |
2 | 139 |
3 | 151 |
4 | 148 |
5 | 155 |
6 | 152 |
7 | 163 |
8 | 159 |
9 | 172 |
10 | 169 |
11 | ??? |
- Use simple exponential smoothing with to forecast the demand for periods1 to 11. Assume .
- Calculate the three measures of errors (MSE, MAD, and MAPE) for each of the moving average and exponential smoothing methods you used. (Hint: Calculate the error for periods 1 to 10 only).
- Provide an estimate for the standard deviation of forecast error (equation 7.23).
- Calculate the bias (equation 7.25) for each method.
- Calculate the tracking signal (TS, equation 7.26) for periods 1 to 10.
- Based on your observations in parts c, d, e, and f which method do you recommend?
- Use Excel Solver to find the value of that minimizes MSE (Hint: see Figure 7-5).
- SUBMIT YOUR EXCEL MODEL on Blackboard.
- Why is it important to estimate the forecast error?
- Why are errors in equation 7.21 squared?
- Explain each of the three main measures for forecast error and situations in which each is appropriate.
- What measure should be used to determine if the used forecasting technique should be changed (e.g., due to a sudden change in demand)?
- What is the advantage of the declining alpha method when using exponential smoothing?
Related Book For
Auditing a business risk appraoch
ISBN: 978-0324375589
6th Edition
Authors: larry e. rittenberg, bradley j. schwieger, karla m. johnston
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