Using causal diagrams to analyze how better testing can ironically lead to worse quality.
U-curve charts can help you avoid getting trapped in either / or thinking.
How to use Shewhart charts to understand the variability of your metrics
How to use causal models to discover points of leverage where you can make different decisions
When the right answer to a question is 'it depends,' what does that really mean?