1. What did Pat and his team learn about the data patterns for orders and contacts per order from the time series plots and autocorrelation functions?
2. Fit an appropriate smoothing procedure to the orders time series and generate forecasts for the next four months. Justify your choice.
3. Fit an appropriate smoothing procedure to the contacts per order time series and generate forecasts for the next four months. Justify your choice.
4. Use the results for Questions 2 and 3 to generate forecasts of contacts for the next four months.
5. Pat has access to a spreadsheet with historical actual contacts. He is considering forecasting contacts directly instead of multiplying forecasts of orders and contacts per order to get a forecast. Does this seem reasonable? Why?
6. Many orders consist of more than one item (unit). Would it be better to focus on number of units and contacts per unit to get a forecast of contacts? Discuss.
Orders and Contact per Order (CPO) for Web Retailer, June 2001-June 2003

Time Series Plot of Orders, June 2001-June 2003

Time Series Plot of Contacts per Order (CPO), June 2001-June 2003

Example 1.2 introduced Pat Niebuhr and his team, who are responsible for developing a global staffing plan for the contact centers of a large web retailer. Pat needs to take a monthly forecast of the total orders and contacts per order (CPO) supplied by the finance department and ultimately forecast the number of customer contacts (phone, email, and so forth) arriving at the retailer's contact centers weekly.

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