Measuring Success
summary
Productivity measures treat engineering as a dashboard not a single number and rely on concrete signals: mean time to restore, issue cycle time, change failure rate plus deployment frequency, PR comment volume and adoption after shipping. Examples include a 45‑person productivity team serving several thousand engineers, a 225→300 engineer applications org at a 2,000‑person company, and using Jellyfish metrics. Success ties to faster lead time to change, safe CI/CD with feature flags and automated tests, frictionless migrations and outcomes tracked by OKRs rather than raw output.
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chapters (10)
- 0:00Start
- 0:16Katherine Kohler
- 1:31Andrew Lau
- 1:59What Does Success Look like for Your Engineering Team
- 8:44Customer Satisfaction
- 10:01How Do You Know Your Team Is Doing Well
- 12:40Measure Collaboration
- 20:11Sustainable Sustainability
- 23:34Gamification
- 24:57Is It Required for Your Engineering Managers To Have Been a Developer in the Past
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