Velocity, burndown, achieved sprint goals — all of these are important.
But even more important is uncovering the connections between them.
A missed sprint goal might look like poor planning —
until you realize that two critical bugs came in.
A drop in velocity might appear to be poor performance —
until you see that code quality has improved by 20%.
An increase in velocity might make everyone happy —
until you notice that team satisfaction has declined.
In other words: understanding the relationships between metrics changes the question from “What went wrong?” to “What does this mean?” — and provides a real basis for decision-making.
This principle is at the core of Sprintometer.
It combines data from multiple sources — Jira, Outlook, Bitbucket, SonarQube, and many more — and enriches them with its own metrics, such as team satisfaction.
Because true agility is only possible when it’s built on a well-founded basis for decisions.
