Why Jira and Confluence quietly become liabilities
Most organizations don’t design their Atlassian stack—they grow into it organically. Projects, fields, and workflows accumulate over years as teams change and leaders rotate.
Eventually, no one can answer simple questions like “How many initiatives are at risk?” or “What’s our real lead time?” without manually cleaning data. We fix that.
Our approach
1) Inventory and rationalize
- Catalog projects, workflows, fields, spaces, and key integrations.
- Identify duplicates, unused schemes, and high-value patterns.
- Map reporting needs across teams, programs, and executives.
2) Design your target operating model
- Define standard workflows and project types for core use cases.
- Align fields and statuses with real-world states, not tool defaults.
- Introduce lightweight governance: who can change what and when.
3) Implement, automate, and migrate
- Implement the new patterns in Jira and Confluence, with change plans.
- Automate repetitive tasks and cross-system updates where sensible.
- Plan and execute migrations to Atlassian Cloud with pilots and rehearsals.
4) Make reporting meaningful
- Design dashboards for teams, managers, and executives.
- Ensure fields and statuses are used consistently to feed those views.
- Train teams on how to maintain data quality without heavy-handed policing.
Key benefits
- Cleaner Jira & Confluence with less noise and duplication.
- Better visibility into portfolio, delivery, and risk.
- Easier governance thanks to clear patterns and permissions.
- Safer Atlassian Cloud adoption with a staged plan.
How we typically engage
- Atlassian assessment (2–3 weeks): inventory, pain points, and reporting needs.
- Design & pilot (4–8 weeks): new patterns implemented for a subset of teams.
- Scale-out & migration: extend patterns and execute your cloud migration roadmap.