In his first two years, Wilke and his team devised dozens of metrics to improve Amazon

Immediately upon moving to Seattle, engineers rather than retail-distribution veterans. He wrote down a list of the ten smartest people he knew and hired them all, including Russell Allgor, a supply-chain engineer at Bayer AG. Wilke had attended Princeton with Allgor and had cribbed from his engineering problem sets. Allgor and his supply-chain algorithms team would become Amazon’s secret weapon, devising mathematical answers to questions such as where and when to stock particular products within Amazon’s distribution network and how to most efficiently combine various items in a customer’s order in a single box.1 Wilke recognized that Amazon had a unique problem in its distribution arm: it was extremely difficult for the company to plan ahead from one shipment to the next. The company didn’t store and ship a predictable number or type of orders. A customer might order one book, a DVD, some tools—perhaps gift-wrapped, perhaps not—and that exact combination might never again be repeated. There were an infinite number of permutations. “We were essentially assembling and fulfilling customer orders. The factory physics were a lot closer to manufacturing and assembly than they were to retail,” Wilke says. So in one of his first moves, Wilke renamed Amazon’s shipping facilities to more accurately represent what was happening there. They were no longer to be called warehouses (the original name) or distribution centers (Jimmy Wright’s name); forever after, they would be known as fulfillment centers, or FCs.

He then applied the process-driven doctrine of Six Sigma that he’d learned at AlliedSignal and mixed it with Toyota’s lean manufacturing philosophy, which requires a company to rationalize every expense in terms of the value it creates for customers and allows workers (now called associates) to pull a red cord and stop all production on the floor if they find a defect (the manufacturing term for the system is andon).

In his first two years, Wilke and his team devised dozens of metrics, and he ordered his general managers to track them carefully, including how many shipments each FC received, how many orders were shipped out, and the per-unit cost of packing and shipping each item. He got rid of the older, sometimes frivolous names for mistakes—Amazon’s term to describe the delivery of the wrong product to a customer was switcheroo—and substituted more serious names. And he instilled some basic discipline in the FCs. “When I joined, I didn’t find time clocks,” Wilke says. “People came in when they felt like it in the morning and then went home when the work was done and the last truck was loaded. It wasn’t the kind of rigor I thought would scale.” Wilke promised Bezos that he would reliably generate cost savings each year just by reducing defects and increasing productivity.

He told his general managers that on each call, he wanted to know the facts on the ground: how many orders had shipped, how many had not, whether there was a backlog, and, if so, why. As that holiday season ramped up, Wilke also demanded that his managers be prepared to tell him “what was in their yard”—the exact number and contents of the trucks waiting outside the FCs to unload products and ferry orders to the post office or UPS.

The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone