Engineering leaders use Jellyfish to track spending and team performance across their organization. Sprint predictability jumped from 55% to 76.5% after implementation. The platform replaced Jira's limited reporting with detailed dashboards they check daily.
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So this is where Jellyfish comes super handy. Jellyfish gives us a breakdown of our investment allocation. How much every, right, every team that is allocated to a certain product or business unit, every department we have that is allocated to a certain product, and so on. How much do we spend? How much does that cost us?
This is amazing. I can finally see what teams are working on and where we're spending our money and doing that.
Wow. Like, I, you know, like, I don't know, at some point in time, it really like this really became our our go-to dashboard to have a glance at how we're operating as a team.
Reporting in Jira is something that was lacking as well. Yes, they have tons of reports that you can generate, but it was only on a, like, a board. In Jellyfish, there's a ton of similar reports that we can slice and dice and manipulate into, into different buckets.
My first inclination is, oh, I think we might be able to get that in Jellyfish. So I do a lot of exploring to say, Can I meet the need that they're asking for in Jellyfish?
Sprint predictability across the project was like 55% in Q1, and now it's at 76.5%.
Now have sort of our top 10 initiatives that we run in the company, and we have a deck where we kind of scorecard them red, yellow, green. But that links out to all Jellyfish.
Instead of just a delivery team, we can do 10 delivery teams or we can do by manager. And that's something we've never been able to do before.
Pretty much on the daily. Basis several times, um, looking at Jellyfish one way or another.
Without, like, using another tool than Jellyfish, it would probably take us, like, 3 to 4 times what it takes us today.
