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How the Bubble Framework works
Essentially, it’s a data-driven feedback loop that enables dev teams to actively respond to change – specifically by accurately tracking progress and anticipating risks of delay – and course-correct accordingly. With the estimator, I used historical data from Jira to compute a project lead time in the form of a probability distribution. Unlike traditional estimation methods, no team estimates are necessary, which not only saves time and hassle but also enables unbiased and instant forward visibility for planning and course correction throughout a project. In developing the algorithm, I drew heavily from two established methods of estimation: the visual component is based on a tool developed by the Critical Chain Project Management community, and the estimate function is rooted in the Monte Carlo method. In essence, what I brought to the table was the pairing of the visual tool and the estimation algorithm to create a short feedback loop that relies on historical data rather than team estimates, thus avoiding some common pitfalls of progress tracking and estimation.
