Some companies now postpone the manufacturing of goods until they are reasonably sure there is a market for them. More specifically, companies defer completion of a certain portion of a product line. “Previously, we would convert all raw materials purchased into finished goods,” says Coach CFO Devine. “Now, we take a deeper position in continuing raw materials [but hold off on manufacturing]. This allows us to respond more nimbly to consumer buying patterns.”
Coach might, for example, load up on more leather or silk than it needs to manufacture products for a given season, and use the remaining materials for later seasons. If demand suddenly does spike, however, “we’ll have raw materials available to quickly up production,” Devine says.
Similarly, some companies are stocking up at their warehouses but delaying the shipment of finished goods to stores. In a May earnings call, Saks announced that it would install such a “hold-and-flow system” in phases beginning this summer. The system “will drive allocation effectiveness by holding back a portion of certain merchandise orders at our distribution center…employing the product through the stores as demand dictates,” says Ron Frasch, the luxury clothing chain’s president and chief merchandising officer.
Such techniques do add warehousing costs, but also have the potential to boost revenues and gross margins. That’s because improved precision in meeting demand makes it more likely that goods will be sold at full price. If they’re used successfully, “the benefit of full-price sell-through outweighs any additional expense to warehouse the product,” says Matthew Katz, a managing director at AlixPartners. “If you warehouse product and then don’t get the full-price sell-through, however, then you’ve got a problem.”
Companies are also adopting a more sophisticated approach to forecasting that includes probing the effects of their own actions on customers. Previously, companies relied solely on past sales-trend data, along with such well-worn gauges as seasonal effects on sales, as a basis for their forecasts, according to SAS’s Chase. “Then, whatever is left over is called ‘unexplained’ or attributed to randomness,” he says. “But, in fact, it can be attributed to sales promotion, marketing, price, and [the accuracy of your] economic forecast.”
In his recent book, Demand-Driven Forecasting, Chase argues that managers imperil their predictions and their profits if they ignore such factors. “For example, a price change occurring simultaneously with a product sales promotion could erode the profitability of the product or create an unexpected out-of-stock situation on the shelf at the retailer,” he writes.
Yet such internal factors must be balanced against broader economic and social factors. Two years ago, OfficeMax, a retailer that does a big business in school supplies, ran a promotion in which crayons, glue, and other specified items were sold for a penny apiece in an effort to lure buyers to shop for all their back-to-school needs at the store.
Unfortunately, this coincided with the start of the recession. Instead of filling their baskets with a mix of loss leaders and full-priced items, OfficeMax customers spread their spending across a variety of competing stores on the basis of price, according to Reuben Slone, executive vice president of supply chains at the company. “People had a lot more time than money,” he says, “because unemployment was really beginning to mushroom, and they were literally watching their pennies.” Slone says the promotion failed because of the most common kind of error in forecasting: an error in assumptions about human behavior, rather than a numerical miscalculation.