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by nrnrjrjrj
608 days ago
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I want to block some time to grok the WBR and XMR charts that Cedric is passionate about (for good reason). I might be wrong but I feel like WBR treats variation (looking at the measure and saying "it has changed") as a trigger point for investigation rather than conclusion. In that case, lets say you do something silly and measure lines of code committed. Lets also say you told everyone and it will factor into a perforance review and the company is know for stack ranking. You introduce the LOC measure. All employees watch it like a hawk. While working they add useless blocks of code an so on. LOC commited goes up and looks significant on XMR. Option 1: grab champagne, pay exec bonus, congratulate yourself. Option 2: investigate Option 2 is better of course. But it is such a mindset shift. Option 2 lets you see if goodhart happened or not. It lets you actually learn. |
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(a) All processes have some natural variation, and for as long as outputs fall in the range of natural process variation, we are looking at the same process.
(b) Some processes apparently exhibit outputs outside of their natural variation. when this has happened something specific has occurred, and it is worth trying to find out what.
In the second case, there are many possible reasons for exceptional outputs:
- Measurement error,
- Failure of the process,
- Two interleaved processes masquerade as one,
- A process improvement has permanently shifted the level of the output,
- etc.
SPC tells us that we should not waste effort on investigating natural variation, and should not make blind assumptions about exceptional variation.
It says outliers are the most valuable signals we have, because they tell us we are not only looking at what we thought we were, but something ... else also.