a. What issues should Dee consider in coming up with forecasts for BP’s various products? How would you suggest she go about creating forecasts for each product?
b. Should Dee try to forecast aggregate monthly product demand for all customers, or individual monthly product demand for each customer? Which of these forecasts would be more accurate? Which of these forecasts would be more useful (and to whom)?
c. Given the available data, how might Dee and Mac judge or gauge the accuracy of each product forecast?
d. Suppose Dee’s technical staff could come up with a way of accurately forecasting monthly demand for BP’s products. How should PB use this information for strategic advantage?
e. What other information should Dee suggest that Mac try to get from BP’s customers?

Mac Brown knew something had to change. As the new Vice President of Sales & Marketing for the PB Chemical Company, Mac understood that when you sell a commodity product, where there is minimal difference between the quality and price, customer service and proactive selling effort usually are the difference between success and failure. Unfortunately, PB’s sales staff was using a fairly random method of soliciting sales, where they would work through an alphabetical list of customers, making phone calls to those who had not paced any orders that month. Often, the difference between whether PB or a competitor got an order simply boiled down to who called at the time the customer needed materials. If the BP salespersons called too soon, they didn’t get an order. And if they waited too long for a customer to call, they often lost business to a competitor.
Mac decided it was time for PB to be a bit more proactive and sophisticated in its sales efforts. He first convinced his counterparts at PB’s largest customers that they could create a more efficient supply chain if they shared their monthly usage data of various chemicals with PB. That way, PB could better anticipate its customers’ needs for various products. This, in turn, would reduce PB’s need to hold inventory as safety stock and would allow PB to operate more efficiently, and pass some of these cost savings on to its customers.
PB’s five largest customers (that account for 85% of PB’s sales) agreed to share their monthly product use data. Now it was up to Mac to decide what to do with the data. It has been quite a while since Mac actually did any demand forecasting on his own and he is far too busy with PB’s strategic planning committee to be bothered by such details anyway. So Mac called one of the firm’s top business analysts, Dee Hamrick, and dumped the problem in her lap. Specifically, Mac asked her to come up with a plan for forecasting demand for BP’s products and using these forecasts for maximum advantage.