Agile sprint planning enables teams to agree on user stories, and quickly execute on them to deliver value to users. But one thing is missing from this process—information about quality. Which user stories contain the highest quality risks? Which user stories might require significant testing in later stages of the pipeline? In many cases, teams simply don’t know.
Imagine if a development team could understand the quality risks inherent in each epic or user story as they progress through an iteration. This would allow correct planning of testing or other efforts needed to mitigate the risk. Without visibility into quality risks, defects are only discovered late in the testing stage, or worse, in production.
When quality issues are discovered so late in the process, it is both difficult and expensive to recover. What if teams knew exactly which test gaps existed during sprint planning and could prioritize closing the most impactful? This would enable finding and fixing defects faster, more effectively, and crucially, tackle them before they cause incidents in production.