The i2 Failure: Tactical or Strategic?
Nike's June 2000 problems with its i2 system reflect the double whammy typical of high-profile enterprise computing failures. First, there's a software problem closely tied to a core business process - in this case, factory orders. Then the glitch sends a ripple through product delivery that grows into a wave crashing on the balance sheet. The wave is big enough that the company must reveal the losses at a quarterly conference call with analysts or risk the wrath of the US Securities and Exchange Commission, shareholders or both. And that's when it hits the pages of The Wall Street Journal, inspiring articles and white papers on the general subject of IT's hubris, limitations, value and cost.
The idea that something so mundane as a computer glitch could affect the performance of a huge company is still so novel that it makes headlines. But what doesn't usually enter the analysis is whether the problem was tactical (and fixable) or strategic (meaning the company should never have bought the software in the first place and most likely won't ever get any value from it). The latter is a goof worthy of a poster; the former is a speed bump.
Nike claims that the problems with its i2 demand-planning software were tactical and therefore fixable. It was too slow, didn't integrate well, had some bugs, and Nike's planners were inadequately trained in how to use the system before it went live. Nike says all these problems were fixed by northern autumn 2000. And the company asserts that its business wasn't affected after that quarter. Indeed, at press time, Nike had just announced that its third-quarter 2003 profit margins were its highest ever.
If there was a strategic failure in Nike's supply chain project, it was that Nike had bought in to software designed to crystal ball demand. Throwing a bunch of historical sales numbers into a program and waiting for a magic number to emerge from the algorithm - the basic concept behind demand-planning software - doesn't work well anywhere, and in this case didn't even support Nike's business model. Nike depends upon tightly controlling the athletic footwear supply chain and getting retailers to commit to orders far in advance. There's not much room for a crystal ball in that scenario.
Indeed, Nike confirms that it stopped using i2's demand planner for its short- and medium-range sneaker planning (it's still used for Nike's small but growing apparel business) in the northern spring of 2001, moving those functions into its SAP ERP system, which is grounded more in orders and invoices than in predictive algorithms. "This allows us to simplify some of our integration requirements," says Nike CIO Gordon Steele.
Wolfram says Nike's demand-planning strategy was and continues to be a mixture of art and technology. Nike sells too many products (120,000) in too many cycles (four per year) to do things by intuition alone. "We've tuned our system so we do our runs against [historical models], and then people look at it to make sure it makes sense," he says. The computer models are trusted more when the product is a reliable seller (that is, just about anything with Michael Jordan's name on it) and the planners' intuition plays a bigger role in new or more volatile products. In this case, says Wolfram, talking with retailers does more good than consulting the system.
"There's been a change in the technology for demand planning," says AMR Research vice president Bill Swanton, who declined to address the Nike case specifically. "In the late 90s, companies said all we need is the data and we can plan everything perfectly. Today, companies are trying to do consensus planning rather than demand planning." That means moving away from the crystal ball and toward sharing information up and down the supply chain with customers, retailers, distributors and manufacturers. "If you can share information faster and more accurately among a lot of people, you will see trends a lot sooner, and that's where the true value of supply chain projects are," Swanton says.
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