Introduction to Statistical Quality Control

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1. jacques_chesterJul 2020
   I really ought to read an OKR book, because the telephone-game version I hear about seems problematic.

   For example, Austin's Measuring and Managing Performance in Organizations[0] gives a helpful 3-party model for understanding how simplistic measurement-by-numbers goes awry. He starts with a Principal-Agent and then adds a Customer as the 3rd party; the net effect is that as a Principal becomes more and more energetic in enforcing a numerical management scheme, the Customer is at first better served and then served much worse.

   As a side effect he recreates or overlaps with the "Equal Compensation Principle" (described in Milgrom & Roberts' Economics, Organization and Management). Put briefly: give a rational agent more than one thing to do, and they will only do the most profitable thing for them to do. To avoid this problem you need perfectly equal compensation of their alternatives, but that's flawed too, because you rarely want an agent to divide their time exactly into equal shares.

   Then there's the annoyance that most goals set are just made the hell up. Just yanked out from an unwilling fundament. Which means you're not planning, you're not objective, you're not creating comparative measurement. It's a lottery ticket with delusions of grandeur. In Wheeler & Chambers' Understanding Statistical Process Control, the authors emphasise that you cannot improve a process that you have not first measured and then stablised. If you don't have a baseline, you can't measure changes. If it's not a stable process, you can't tell if changes are meaningful or just noise. As they put it, more pithily:

   > This is why it is futile to try and set a goal on an unstable process -- one cannot know what it can do. Likewise it is futile to set a goal for a stable process -- it is already doing all that it can do! The setting of goals by managers is usually a way of passing the buck when they don't know how to change things.

   That last sentence summarises pretty much how I feel about my strawperson impressions of OKRs.

   [0] https://www.amazon.com/Measuring-Managing-Performance-Organi...

   [1] https://www.amazon.com/Economics-Organization-Management-Pau...

   [2] https://www.amazon.com/Understanding-Statistical-Process-Con..., though I prefer Montgomery's Introduction to Statistical Quality Control as a much broader introduction with less of an old-man-yells-at-cloud vibe -- https://www.amazon.com/Introduction-Statistical-Quality-Cont...

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2. mch82Nov 2016
   "The Seventh Edition of Introduction to Statistical Quality Control provides a comprehensive treatment of the major aspects of using statistical methodology for quality control and improvement." http://a.co/5xRV2UE

   Covers: Hypothesis testing (single population), Analysis of variance (multiple populations), Control charts, Design of Experiments (A/B testing and beyond).

   Edit: Used in the undergraduate industrial & systems engineering program at USC when I was a student. The 7th edition has various cook book style walkthroughs.

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