How Bad Is Your Toil?: Measuring the Human Impact of Process
summary
LinkedIn measures toil by monthly 3‑minute surveys that split time into categories and finds ~37% reactive work, 21% overhead and 42% engineering time against a hoped 50/50 project goal. Teams run deeper pulse surveys, score pain on 1–5 scales, and try interventions: changing schedules (3-on/4-off), forcing devs onto early on‑call, and building tools named Insomnia (alert analytics) and on-call retro (postmortem tagging). Results are mixed: schedule changes reduce burnout for worst teams, tagging rates stay low and about 52% of tagged alerts are judged ineffective.
AI-written summary · about
chapters (24)
- 0:00Intro
- 2:20Origins
- 3:14Baseline
- 3:30Time Categories
- 5:33Survey
- 6:23Definitions
- 7:32Results
- 8:17Comments
- 9:04Interlude
- 12:06Downstream Issues
- 13:13Managing Alerts
- 14:31Overall Survey Results
- 15:17Interventions
- 18:12Steps
- 18:45Life Results
- 19:19Insomnia
- 19:43Elastic Search Framework
- 20:29Retro
- 21:48Sleep interruptions
- 22:10Visualizations
- 22:26Tagging
- 22:57Recap
- 23:17Take Steps
- 23:38Questions
related talks
21mHow to Increase Developer Productivity and Happiness
46mObservability for Engineering Teams
46mManaging the Burnout Burndown
35m“On-Call Is Ruining My Life” and Other Tales about Holding the Pager as an SRE
01h 00mManaging the Burnout Burndown
36mHey Focus! How to get the most out of your day
39mSPACE and Beyond - Measuring Developer Productivity
29mShrinking the Impact of Production Incidents