Service Operations · 2024 to 2025
Jira Service Management Transformation
From an unstructured, email driven workflow to a measurable, AI enabled service platform.
The problem
A midsize enterprise needed a service platform that could keep up with both the daily volume of technology requests and the strategic transformation already underway. Ticket flow lived across email aliases, shared inboxes, and tribal knowledge. Resolution time was unmeasured. Knowledge was not searchable. AI enabled support was emerging across the industry but had not been brought inside the company.
The approach
I led the transformation work end to end on the delivery side, in close collaboration on design. The work spanned four layers:
- Automation workflows. Routing, assignment, escalation, and SLA enforcement designed to remove human friction from predictable paths.
- Knowledge architecture. Confluence space structure, page templates, taxonomy, and permissioning. Articles created during ticket work fed directly back into a searchable institutional memory.
- AI enabled support. Integrated Rovo AI to surface relevant knowledge and triage incoming work, lifting both speed and consistency of first response.
- Reporting. Queue ownership, SLA dashboards, and operational visibility for the first time.
The outcome
- 20 percent reduction in IT support ticket resolution time.
- The organization's first measurable, AI augmented service workflow.
- A reusable knowledge layer that converts every closed ticket into searchable institutional memory.
- A foundation that the cloud monitoring and data engineering work now sits directly on top of.
Stack
- Jira Service Management
- Confluence
- Rovo AI
- Microsoft 365
- Entra ID
- Azure