Anthony ODonovan decided something had to be done and done sooner rather than done later. ODonovan was the newly appointed Director of Sales of the Print Cartridge and Toner Company (PCTC) located in Mississauga, Ontario. Anthony understood that when you sell a commodity product, when there is minimal difference between the quality and price, customer service and hard, proactive selling effort usually are the difference between success and failure. Unfortunately, PCTCs sales staff was using a fairly random method of soliciting sales, where they would work through an alphabetical list of current customers, making phone calls to those who had not ordered anything that month. Often, the difference between whether PCTC or a competitor got an order simply boiled down to who called at the time the customer needed materials. If the PCTC salesforce called too soon, they didnt get the orders. And if they waited too long for a customer to call, they often lost sales business to a competitor. Anthony decided it was time for PCTC to be a bit more proactive and sophisticated in its sales solicitation efforts. He first convinced his counterparts at PCTCs largest customers that they could create a more efficient supply chain if they shared their monthly usage data of various toner cartridges with PCTC. That way, PCTC could better anticipate its customers needs for various products. This, in turn, would reduce PCTCs need to hold inventory as safety stock and allow PCTC to operate more efficiently while passing some of these cost savings on to its customers in product pricing. PCTCs five largest customers (that account for 85% of PCTCs sales revenue) agreed to share their monthly product consumption data. Now it was up to Anthony to decide what to do with this data. It has been quite some time since Anthony actually did any demand forecasting on his own, and he is far too busy with PCTCs sales and marketing strategy committee to be bothered by such details anyway. To nobodys surprise, Anthony called one of the firms top sales OM specialist, Gertie Chiasson, and dumped the problem in her lap. Specifically, Anthony asked her to come up with a plan for forecasting sales demand for PCTSs toner and printer cartridges and using these forecasts for maximum sales advantage.

a. What issues should Gertie consider in coming up with sales forecasts for PCTCs various products? How would you suggest she go about creating demand forecasts for each product?

b. Should Gertie 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 Gertie and Anthony judge or gauge the accuracy of each product forecast?

d. Suppose Gerties sales operations staff could come up with a way of accurately forecasting monthly demand for PCTCs products. How should PCTC use this information for strategic sales advantage?

e. What other information should Gertie suggest Anthony try to get from PCTCs customers?