Your data team ships pipelines fast. That’s the First Way. They’re ignoring the other two.
Gene Kim’s Three Ways from The Phoenix Project changed software delivery forever. Flow, feedback, learning. Most data teams only got the memo on flow.
The First Way is about moving work left to right. Source to insight without bottlenecks. Data teams are decent at this - they build pipelines, ship dashboards, move data. Fine.
The Second Way is feedback. And this is where it falls apart. Most teams find out data is broken when a stakeholder screenshots a wrong dashboard. Damage control. Feedback came too late to matter.
The Third Way is continual learning. Blameless post-mortems after data incidents. Investing time to improve existing pipelines instead of only building new ones. I’ve seen maybe two data teams in five years that actually do this.
Here’s the uncomfortable part: data has constraints the books never addressed. Schema evolution. Stateful transformations. Sources you don’t control. The Three Ways still apply - they just need adapting for data reality.
Which of the Three Ways is your data team weakest at: flow, feedback, or learning?