Feature Size Distribution
A common question for beginner and intermediate-level squads is what does ‘good’ look like when creating a Feature. This usually includes some sort of quantifiable measure around how large said Feature should be.
Rather than trying to look externally for a ‘best practice’ solution, we should instead look internally. By collecting every Feature, and the number of child User Stories beneath them, and tallying them up into a histogram we can see what a ‘typical’ Feature has looked like up until now. This should in turn spark questions around the characteristics of those Features, namely:
- Were the Features of X size large enough to deliver real customer value?
- Were those same Features small enough to fit in our release cadence, or customer measurement cycle?
- Based on these answers, should we be trying to shift the needle towards larger, or smaller Features?
If you'd like to know how this visualisation could be implemented in your organisation, feel free to contact me!