Data-driven visibility has transformed planning and now optimizes engineering and QA collaborationThe best features Jellyfish offers are Allocation and Investment View, seamless integrations, DevEX and delivery metrics, Team Health and Work Profile, Executive Reports, and justified test automation investments, improved developer and QA collaboration, and better sprint estimation. The Allocation and Investment View stands out for me as a killer feature. It shows us exactly where engineering time is invested, such as roadmaps, bugs, infrastructure, and KTLO. This helped us balance feature work and quality work. When it comes to Executive Reports, they provide very clean dashboards that even non-technical managers can understand. There is no need to explain Jira queries anymore. I would also say the seamless integrations are impressive. The Jira plus GitHub plus Jenkins integration took less than 30 minutes. It automatically maps commits to Jira tickets, so no manual tagging is needed. One positive impact Jellyfish has had on my organization is that it reduced unplanned work. We found that 30% of our QA time was going into production hotfix testing, which was not planned. With Jellyfish data, we created a dedicated buffer for unplanned work in sprint planning. Unplanned work dropped to 12% in three months. It has also improved developer-QA collaboration and led to better sprint estimation. We started comparing estimated versus actual allocation. Now our sprint predictions are 85% accurate versus 50% earlier. There are no more last-minute release postmortems. It also helped identify bottlenecks in QA where Jellyfish showed that tickets were stuck in 'Ready for QA' status for an average of 1.8 days due to environment unavailability. We then containerized our test environment with Docker and Jenkins, cutting wait time to four hours.
