Fine-Slicing Beats Estimation for Predictability

As requested by JB in the comments to my previous post, here is some data about what happens when a team choose fine-slicing over estimation.

You’re about to see a CFD chart drawn by a team who used BDD to break down every requirement into scenarios before they started hacking on them. The items on the left aren’t actually scenarios in this case, they’re very small user stories which tended to be of a size of about 3-4 scenarios each. The point is, we broke everything down into the smallest pieces of behaviour we could, then re-assembled them into chunks that were meaningful enough to build together.

Rather than using story points to manage the variation in size of stories, we gave each story a value of one point, and used BDD analysis to try to ensure each story was a uniformly small size.

This data was collected over a period of about six months by a team of about eight developers. Their system (a high-volume website) was already live and they were adding features to it.

What strikes me the most is how straight the ‘done’ line is.

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