https://www.cloudbees.com/blog/measuring-engineering-efficiency
- what to measure, measure at team level
- what NOT to measure, NOT at insividual level
- perverse incentives, atory point inflation
- Ensure Your Team Builds What Matters the Most, Quickly and Efficiently
good metrics:
- Average Cycle Time
- Time Spent by Area
- Time Spent on Planned vs. Unplanned Work
https://sourcegraph.com/blog/developer-productivity-thoughts
- Flow state and interruptions
- Cycle time, developer hertz
- Concurrency and parallelism
- Amdahl’s law
EE and productivity
https://newsletter.pragmaticengineer.com/p/linkedin-engineering-efficiency
At Google and Linkedin
I came to the conclusion that optimizing for human developer time is almost always the only worthwhile investment.
The value of human time at most software companies is 20-100x the value of machine time. This means it’s possible to lose money by doing optimizations which save only machine time, but not any human time!
DORA, SPACE and other metrics, the good and the bad
https://leaddev.com/process/what-mckinsey-got-wrong-about-developer-productivity
DORA:
- Change failure rate
- Failed deployment recovery time (until recently, called mean time to recovery (MTTR))
- Deployment frequency
- Lead time
SPACE:
- Satisfaction and well-being
- Performance
- Activity
- Communication and collaboration
- Efficiency and flow