We’re running both mf-25.4 and Jira in our organization, and I’m getting conflicting velocity forecasts from the two tools for our backlog planning sessions. The mf-25.4 metrics dashboards show our team velocity at 42 story points per sprint, while Jira’s velocity chart shows 38 points for the same sprints.
This 10% difference is causing problems with capacity planning and stakeholder reporting. I’m trying to understand which tool’s calculation is more accurate, or if there’s a way to sync them properly. Has anyone successfully integrated velocity metrics between these tools, or do you just pick one as the source of truth?
Curious to hear how other teams handle cross-tool reporting when metrics don’t align.
You can sync them using the REST API on both sides. Set up a scheduled job that pulls velocity data from Jira and pushes it to ALM’s custom metrics, or vice versa. That way you’re using one tool’s calculation as the authoritative source and just mirroring it to the other. We do this with our setup and it works well.
That makes sense. We do have quite a bit of carry-over work. So there’s no way to actually sync the calculations between the tools? We’d have to manually adjust one to match the methodology of the other?
Another factor is how each tool treats carry-over work from previous sprints. ALM’s velocity calculation includes carried-over items in the completion sprint, while Jira can be configured to count them in the original sprint. This creates discrepancies over time that compound across multiple sprints.