A holiday weekend was fast approaching, and in Lima, Ohio, managers at the Procter & Gamble factory were shutting things down early. The move seemed to make sense. Analysis of purchase orders and historical sales trends indicated that the factory had already cranked out enough cases of Liquid Tide to meet the demand of holiday launderers. Rather than keep idle workers on the clock, managers ordered the facility managers shut down the facility ahead of schedule, giving employees some extra time off.
But during the weekend before the holiday, P&G executives were greeted by a surprise. One of the company’s largest retail customers had placed a sizable — and unforeseen — order for detergent. P&G immediately reopened the Lima plant, but had to pay workers overtime and schedule emergency shipments to meet the retailer’s request. The cost of responding to “the event,” according to P&G global product supply officer Keith Harrison, ran into the seven figures.
P&G is not the only business that gets whipsawed by events. Far from it. When managers rely on sales forecasts — and lack real-time point-of-sales and supplier data — they routinely find themselves in a bind. As one company executive grants: “We sell from stock, and the amount of that stock is based on historical trends. Not surprisingly, we’re often sitting on too much or too little inventory.”
The answer? For some, trying to improve forecasting. Certainly, accurate forecasts are crucial when mapping out large manufacturing runs and new product designs. But by definition, sales forecasts are guesses — guesses often shaped by the desire of executives to set audacious goals and hit out-of-the-box numbers. Even managers at businesses with sophisticated forecasting systems have run up against the crystal-ball wall. Says Mitch Myers, vice president of operations at FW Murphy, an instrument maker in Tulsa: “We want to be fast and flexible. We don’t want to be dependent on predictions about what’s going to happen, like some psychic on a 1-900 number.”
A Different Approach
Instead, managers at FW Murphy, along with executives at a growing number of other companies, have adopted a different philosophy: shift the focus from forecasting to reacting. This is no small task. Unlike just-in-time manufacturing — a waste-reduction effort that typically foists inventory risk onto suppliers — demand-driven manufacturing requires a tricky integration of complex computer systems all along the cash-conversion cycle. Point-of-sale data must be funneled into purchase-order systems, which then trigger procurement programs, which eventually push data into supplier portals. In a sense, products become bytes of data. Notes Andy Carlson, vice president of product marketing at business-software maker PeopleSoft Inc.: “Companies are replacing inventory with information from customers and vendors.”
And connecting the two. While supply-chain reengineering is crucial to reacting to unforeseen consumer requests, demand-driven manufacturers go one step further, passing customer data along to suppliers. Dell Inc., long a leader in inventory and supply-chain management, now sends real-time sales data to suppliers every two hours. The Round Rock, Texas-based PC maker has also moved its vendors into shared logistics centers close to the company’s factories — “our buffer between forecasts and reality,” notes Stephen Cook, Dell’s director of manufacturing at the company’s national fulfillment campus in Nashville. P&G is filling retailers’ requests for such diverse products as Pringles and Ivory Soap in less than 72 hours. Ultimately, the Cincinnati-based consumer-goods giant wants to create a real-time, store-shelf-to-supplier system driven by individual consumer purchases. “We want to make what’s actually selling,” explains Harrison, “not what we forecast will be selling.”