A manufacturer recently recorded 14 test failures out of a total of 318 products submitted for testing. This failure caused some panic and with it, some hasty decisions. Root cause analysis was performed in a meeting room. Wrong place. A decision was made to modify some tooling on the assumption that this was the root cause. With the new tooling in place another 30 samples were submitted and all passed the test. And there was much rejoicing.
The sample size was wrong. The problem still existed and there was a lot more product in inventory because the group celebrated early, producing a lot more units with both the modified tool and the real root cause.
The sample size chosen only provided 75% confidence, not enough for such an important decision.
There are many reasons why problem solving efforts fail. Knowing the minimum sample size required is one of them and it shouldn't be.
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