Everything Must Go

Corporate managers often feel boxed in by their own supply chains. Business-intelligence software may open them up to new possibilities.

The millennium started poorly for North Face Corp. The company’s logo was ubiquitous on college campuses, yet the manufacturer, distributor, and retailer of outdoor apparel was nearly bankrupt, largely because of problems with its supply chain.

“North Face was losing $100 million on $238 million of sales because it was producing too much inventory and could not match this inventory to orders or even ship it effectively,” says Dan Templin, CFO of Outdoor Coalition, a division of VF Corp., the $5.6 billion apparel giant that bought North Face in May 2000.

“The company had zero visibility into its supply chain,” says Templin. “It didn’t know what its orders were or where its purchases were logistically. Everything had come unglued from an information and service standpoint.” On-time performance to retailers was less than 50 percent, bad for any manufacturer but particularly deadly for North Face because there was enormous demand for its apparel.

Given that even “performance” clothing has the limited shelf life of other fashions, there was little opportunity to recoup one season’s botched opportunities the next year. The company, says Templin, was in crisis mode.

VF saw potential, but it had reservations. “We were looking at a business that could not meet its planned sales, had a broken supply chain, and was losing money fast,” says Templin, who was CFO of VF’s knitwear division at the time. Ultimately, what sold VF on North Face was the latter’s solid brand and VF’s faith in its own operational expertise and the power of business-intelligence (BI) software to fix supply-chain problems.

Templin had seen what BI software could do, having used products from Brio Software to fix supply-chain problems at VF’s knitwear division and throughout the company. Confident that the experience could be repeated, VF bought North Face.

North Face’s supply chain was undermined by its reliance on manual processes, arduous under any circumstances and more so for North Face, which had to cope with a mountain of data. The company created reports on nearly 12,000 stock-keeping units (SKUs) and 2,000 resellers.

Transaction data included sales orders, purchase orders, and inventory, which were entered into spreadsheets from which the reports were created. The effort often took weeks and sometimes months, frequently creating situations in which orders on the front end couldn’t be aligned with all the back-end execution needed to satisfy them. Templin wanted to automate the entire process with a data warehouse and BI tools that could provide visibility into orders and drive smarter purchase decisions.

The Brio software culls data from the warehouse to produce more than 50 electronic reports that compare sales-order information with inventory data, determining an accurate delivery date that meets or precedes a customer’s requested ship date. Reports cover historical sales information and open sales orders by customer; the styles, colors, and sizes that are best-sellers and those that may require discontinuation; and more-traditional metrics like business-unit profit-and-loss statements and budgets versus actual spending. The reports are pushed out to North Face decision-makers via E-mail.


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