I know we have been talking about statistics a lot in my last few articles, but recent reader comments have prompted me to think more about why doing statistics properly matters. Come with me, dear reader, on a journey to find out why you should embrace, and not run screaming from, your inner statistical geek. But to get there, we have some interesting terrain to cover… starting with the human brain.
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After my last column citing some really bizarre flaws in how our brains perceive reality, I thought I might cover some flaws in logic that are applicable in the world of quality. So, basically, even if our brains are working correctly, we can still send our Black Belts off on false trails trying to solve problems, thus offering more proof (as if we need it) for Voltaire’s observation that “common sense is quite rare.”
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With the announcement of another Toyota recall, it seems that everyone and their dog have an opinion about Toyota, and some of them might even be drawing the right conclusions. While everyone is allowed to have opinions (not the dogs—on quality matters I don't trust entities that consider cat poo a delicacy), it’s interesting to note that Toyota’s was not the biggest recall, not even the biggest in recent memory. So why do they get all the bad press—and what does it mean for quality?
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"Come and listen to a story ‘bout a man named Ned / a poor Texas Sharpshooter barely kept his family fed. Then one day he was shootin’ at his barn / and he came up with a plan to spin a silly yarn. ‘Specifications,’ he said, ‘making of… the easy way.’ ” What do a Texas sharpshooter and specifications have to do with each other? And what do you do when your humble author has an old TV show theme song stuck in his head? Let’s find out…
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Although we may use the define, measure, analyze, improve, control (DMAIC) mnemonic to help guide us through our problem solving, that doesn't really give us a lot of specific direction (as I bemoan in my Top 10 Stupid Six Sigma Tricks No. 4). Good experimental design technique is critical to being able to turn problems into solutions, and in my experience Black Belts have not been introduced to a good process to do this. If you know someone whose first thought is, "Let's go collect some data to see what is going on," then read on to avoid losing millions of dollars in experimental mistakes.
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