Panel Discussion: Let's Improve - Leverage DORA to Im...
summary
Offers a practical way to measure and improve delivery using DORA’s research-backed framework, a quick-check tool and a capability catalog; running the quick check often yields midrange scores (example shown is 5.7 out of 10) and highlights velocity gaps in lead time & deploy frequency while stability metrics (change fail rate and MTTR) often look stronger. Key empirical claims: faster code review links to 50% better delivery, AI tooling is early-stage (helps well‑being, not yet broad delivery gains), and the recommended workflow is baseline → experiment → measure → add one improvement story to the backlog.
AI-written summary · about
chapters (13)
- 0:00Welcome to Dora
- 2:26Dora research program
- 3:28Baseline for delivery
- 5:39Interpreting Dora metrics
- 6:22Dora resources
- 7:05Annual Dora survey
- 9:54AI impact on delivery
- 10:18Q&A on lead time
- 12:01Dora for dev teams
- 14:31Managing leadership with Dora
- 16:55Capabilities to performance
- 19:07Valid Dora measurements
- 21:34Closing remarks
related talks
28mAccelerating Success: How to Optimize Value Delivery with DORA
23mOptimizing Delivery with DORA Metrics: How We Prepared and Where to Start
19mAccelerating Code Quality with DORA Metrics
25mFrom Gut Feel to Evidence: What DORA Metrics Actually Tell Us
14mSmarter #Testing for Better Speed & #Quality with DORA Metrics
29mA DORA Metrics Adventure in Deciphering Engineering Changes
27mClosing Keynote
33mMeasuring Developer Productivity: the good, the bad and the data