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Manufacturers dream of a finely tuned supply chain, with finished goods landing softly on distributor and retailer loading docks at exactly the right time in precisely the right quantity. That can't be done, of course, without accurate demand forecasting -- which still tends to be based on intuition, last year's sales numbers, and spreadsheet war games between sales and marketing groups. For most, the dream remains distant.
But manufacturers finally have a shot at turning that fantasy into reality. The key is integrating POS (point-of-sale) data with modern demand-planning tools, which are just now coming together for the enterprise. Wal-Mart has led the way, providing its suppliers POS data per store, updated several times a day, allowing suppliers to adjust their distribution, manufacturing, and marketing efforts based on what's actually selling and where.
"Wal-Mart is setting the gauge for this supply-chain railroad," says Don DePalma, supply-chain analyst at Common Sense Advisory. Other major retailers, such as Best Buy, Home Depot, Kmart, Lowe's, Rite-Aid, and Target, are following suit.
Armed with that POS data, both retailers and manufacturers can build demand models that account for seasonality, regional variations, pricing and promotions, and distribution and manufacturing constraints. For example, analyzing POS data for promotions may tell you that 70 percent of an item is typically sold on the first Saturday of the promotion, letting you arrange your distribution accordingly. Retailers and product makers can also compare their forecasts to uncover differences in assumptions and then adjust them to create a "forecast of record."
Demand-driven systems also help companies adjust to inventory inefficiencies required by the increased use of overseas outsourcing. As companies have increased the use of overseas suppliers, many have had to keep more local inventory, raising costs and countering earlier just-in-time efforts.
A demand-driven system helps companies better manage the flow of these strategic inventory reserves through distribution as demand shifts, as well as provide earlier signals of demand changes so remote suppliers have better notice of when to adjust their output.
The use of near-real-time POS data should not take the place of planning, analysts advise. Instead, POS data should be used in demand-planning tools to refine those forecasts in a continual-improvement process, says Yankee Group Analyst Mike Dominy.
"Forecasting is critical to demand-driven systems," notes Noman Waheed, a partner at the consultancy Accenture. Otherwise, you're just automating the status quo, not avoiding problems and identifying opportunities.
For example, dressings and sauce maker Litehouse Foods uses Ross Systems' demand-planning software to compare POS data from Wal-Mart against its forecasts, says IT director John Shaw. This allows Litehouse to adjust what it sends to Wal-Mart's distribution centers to avoid overstock of fresh supplies that would spoil. It has also significantly reduced divergence between sales and forecasts, which had been as high as 60 percent, Shaw says.
Building on Existing Infrastructure