$1.$ Why is forecasting necessary in OSCM?

$2.$ It is a common saying that the only thing certain about a forecast is that it will be wrong. What is meant by this?

$3.$ From the choice of simple moving average, weighted moving average, exponential smoothing, and linear regression analysis, which forecasting technique would you consider the most accurate? Why?

$4.$ All forecasting methods using exponential smoothing, adaptive smoothing, and exponential smoothing including trend require starting values to get the equations going. How would you select the starting value for, say Ft$-1?$

$5.$ How is a seasonal index computed from a regression line analysis?

$6.$ Discuss the basic differences between the mean absolute deviation and mean absolute percent error.

$7.$ What implications do forecast errors have for the search for ultra$-$sophisticated statistical forecasting models?

$8.$ Causal relationships are potentially useful for which component of a time series?

$9.$ Let$$s say you work for a company that makes prepared breakfast cereals like corn flakes. Your company is planning to introduce a new hot breakfast product made from whole grains that would require some minimal preparation by the consumer. This would be a completely new product for the company. How would you propose forecasting initial demand for this product?

$10.$ How has the development of the Internet affected the way companies forecast in support of their supply chain planning process?