About Sprint Data Gathering

Looking at a sprint document I designed a few years back (and updated by my scrum master colleagues), what I see are all sorts of data: planned total story points, actual finished story points, planned total task hours, actual finished task hours (total, per developer, team per day), burndown chart, attendance records, retrospective notes, tickets notes, returned tasks, unplanned tasks, underestimated tasks. So many information being gathered and compiled every sprint iteration; it’s not really too difficult to document but it does kind of takes away a good chunk of time to manage. Back then when we were new to scrum I thought that crunching numbers will provide insights as to how we can improve estimates and productivity, I thought that maybe we’d become faster and better at what we do after performing some mathematics.

It turns out that it doesn’t work that way. It turns out that estimates and productive behavior is a lot more complicated than it seems. It turns out that personalities and preferences and work environment and team dynamics and other small stuff we don’t pay attention much to play big roles in being good at software development as a team. Data about these things are not shown in the sprint document, and I don’t have the slightest idea how to measure them. So, looking back at all these stuff we’re trying to analyze, I’m haunted by questions: Which data are important enough to keep taking notes of, sprint after sprint, to keep reviewing? Why are they important? How do these data help me define how my team improves in succeeding iterations? Are they just pointing out problems but no solutions in sight? What if I stop documenting these data, would that help me focus my energy towards other possibly more important to-dos?

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