Demand prediction, scan-based trading

Interesting BI example in an NYT article about Wal-Mart:

A week ahead of the storm's landfall, Linda M. Dillman, Wal-Mart's chief information officer, pressed her staff to come up with forecasts based on what had happened when Hurricane Charley struck several weeks earlier. Backed by the trillions of bytes' worth of shopper history that is stored in Wal-Mart's computer network, she felt that the company could "start predicting what's going to happen, instead of waiting for it to happen," as she put it.
The experts mined the data and found that the stores would indeed need certain products - and not just the usual flashlights. "We didn't know in the past that strawberry Pop-Tarts increase in sales, like seven times their normal sales rate, ahead of a hurricane," Ms. Dillman said in a recent interview. "And the pre-hurricane top-selling item was beer."
Thanks to those insights, trucks filled with toaster pastries and six-packs were soon speeding down Interstate 95 toward Wal-Marts in the path of Frances. Most of the products that were stocked for the storm sold quickly, the company said.

The article also mentions scan-based trading, a term with which I was unfamiliar:

Eventually, some experts say, Wal-Mart will use its technology to institute what is called scan-based trading, in which manufacturers own each product until it is sold. "Wal-Mart will never take those products onto its books," said Bruce Hudson, a retail analyst at the Meta Group, an information technology consulting firm in Stamford, Conn. "If you think of the impact of shedding $50 billion of inventory, that is huge."

Here's some more on scan-based trading:

Scan-based trading (SBT) is not so much about coordinating data as it is about shifting financial risk from seller to supplier. Not only must a vendor such as American Greetings pay for the inventory of cards that will sit on the retailers' shelves right up until the moment of sale—such vendors also must bear the burden of making sure there are no holes in the tracking of products and transactions.
The idea behind these systems is simple enough. Rather than paying for products from suppliers as they are brought into the store, the supplier retains "ownership" of products on the shelf. Sales information is sent automatically from retailer to supplier. When the supplier receives that information, an invoice for goods sold is automatically created and an order is submitted to replace the sold merchandise.
In theory, everybody is supposed to come out a winner. The retailer loses the financial risk of carrying inventory while reducing its administrative and order management costs. The supplier gets daily alerts to replenish its wares—which means more sales—and is able to gather nearly real-time data about the performance of products store by store. This data can be used by the supplier to improve forecasting, production planning and product targeting.