How do the bad units know where to go?

When your customer returns a failed product, there are things you regularly do to understand the problem. Depending on the product, you might check its serial number against your production logs, to see when it was manufactured. Was it part of a batch that you already know had problems? Maybe you check its composition. Does it include components that have given you trouble before? There are multiple avenues you can explore, as part of your root-cause analysis investigation. But do you remember to ask your customer, What exactly were you doing when the product stopped working?

This is not who the story is about!
But I found the illustration on the
Internet and couldn't resist. 

Last week I heard the craziest story. Some customer had an accident that left him unable to walk. But his job required him to move around a lot, so he got a motorized wheelchair. After a month, the engine burned out, and he had it replaced. A month later, the new engine burned out, so he had that one replaced too. And the month after that ... well, you get the idea.

It seems that the wheelchair manufacturer and the customer's insurance company let this cycle go on for some time before they finally began to investigate. What exactly was this guy's job, anyway? It turns out he was a high school football coach. And his idea of how to do the job involved racing back and forth on the sidelines during games, so he could get a close look at what was going on. On the grass. In the mud. All through football season. If he got stuck in a mud patch or a gopher hole, he just jammed the wheelchair into overdrive until he got free. And somehow the engines in his wheelchair kept burning out.

Gosh, who would have guessed?

It reminded me of a story I heard years before, in a problem-solving class. A large manufacturer of high-end cookware kept getting pans returned where the ceramic finish had melted in a way that made the pans unusable.* They studied their manufacturing process, spent a lot of time and money on improvements, and it made no difference to the return rate for this particular failure.

Finally, after a lot of frustration, they hired a problem-solving expert who looked at the overall return data. This company shipped product throughout North America, but all the returns with this problem came from Toronto. Right away he told the company to stop wasting time and money reengineering their manufacturing process.

"Why?" they asked. "How can you be sure that's not the problem?"

"If the problem was caused by manufacturing, it would be evenly distributed across all your customers. But look at this map. How do all the bad pans know to go to Toronto?" 

"Then what's the cause?"

"Put me on the next flight to Toronto, and I'll tell you."

In the end, he discovered there was a popular cooking program on a local TV station which recommended that viewers clean their pans in a certain way. That cleaning method just so happened to destroy the ceramic finish on this company's pans. I don't remember how they finally solved the problem. But until they asked how their customers were using the products, their investigations were fruitless.

So remember to ask. If you see failure data that doesn't fit the patterns you expect, what other pattern does it fit instead? There has to be one. And when you have all the facts, the picture is going to make sense. As long as the failures make no sense, you don't have all the facts.

Just remember: How do all the bad pans know to go to Toronto?

It's a powerful question.

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* I heard this story years ago, so I may have some parts of the story slightly garbled. But the point should be clear.