There’s a saying in data science: Garbage In, Garbage Out (or GIGO, if you prefer). The most advanced formulas and models won’t provide outputs worth a dead cat if you don’t have high quality inputs. When it comes to something as difficult and uncertain as feature planning and estimation, that’s quadruply so. In this post I’m going to walk you through the system I’ve used successfully, how it works, and why. And it’s all based on the counter part to the story points from Part 5, user stories. The article image for “User Stories Make For Better Consensus – Game Planning With Science! Part 6” is from GraphicStock. Used under license. Previously on “Game Planning With Science!”: Part 1 Part 2 Part 3 Part 4 Part 5 By Reading This Post, You Will Learn: A formal taxonomy of a user story Why investing a little time now is better than wasting a lot of time … Continue reading User Stories Make For Better Consensus – Game Planning With Science! Part 6