8
Internal service teams
Shared JSM model reviewed across IT, Registry/Salesforce, change, procurement, and future service areas.
Jira Service Management Case Study
Jira Service Management Optimization for a Multi-Team Regulatory Environment
AtlasOptima helped a Canadian regulatory organization redesign a shared Jira Service Management environment into a cleaner multi-service operating model with clearer team ownership, rationalized request types, optimized workflows, stronger SLA governance, better reporting, and a structured vendor/security intake path.
This public case study is anonymized. Customer identity and internal implementation artifacts are withheld unless explicit publication approval is granted.
30-35
Estimated practical active-agent need
35+
Vendor/security intake fields structured
100+
Licensed agents reviewed
Practical active-agent need was estimated closer to 30-35 users after service ownership and usage review.
25+
Request types rationalized
Request catalog reviewed against ownership, workflow, reporting, visibility, and SLA needs.
4
Core workflows optimized
IT request, incident/support, change management, and procurement/security review flows were redesigned.
The operating problem
The organization was using Jira Service Management as a shared platform for multiple internal teams. That created a useful centralized foundation, but it also made ownership, request classification, reporting, and automation governance harder to manage over time.
Different teams needed different request types and workflows. Some requests were standard IT support items. Others involved Salesforce or registry support, change control, vendor procurement, security review, privacy details, or future business-service intake. Treating all of those needs as one generic service desk would have made the platform easier to start but harder to scale.
Management also needed cleaner reporting by team, request type, priority, SLA status, and change/request status. At the same time, sensitive requests needed controlled visibility and the licensing footprint needed a practical review because the environment had more than 100 licensed JSM agents while the expected active-agent requirement was closer to 30-35 users.
What AtlasOptima assessed
AtlasOptima reviewed the JSM environment from both an operating-model and configuration perspective. The assessment covered projects and queues, request types, workflows, SLA rules, automation logic, notification patterns, permissions, reporting needs, service ownership, and licensed-agent usage.
Projects, queues, and service ownership boundaries.
Request types, forms, categories, and field requirements.
Workflow states, approvals, SLA timers, and closure logic.
Automation and notification rules that were difficult to isolate or audit.
Permission and visibility patterns for sensitive internal requests.
Agent license usage compared with practical operational need.
How the JSM model changed
The redesigned model separated service ownership so each team could manage its intake, queues, reporting, and request lifecycle with less cross-team noise. This did not mean every team needed a completely isolated platform. It meant the shared service platform needed clear service-area boundaries.
| Service area | Design focus |
|---|---|
| IT Helpdesk | General employee support, intake, triage, incident handling, and request closure. |
| Salesforce and Registry Support | Business-application support with clearer ownership, queues, categories, and reporting. |
| Change Management | Structured change request intake, approvals, CAB support, lifecycle statuses, and closure control. |
| Vendor and Procurement Intake | Security, privacy, compliance, risk, vendor, cloud, and operational review information captured at intake. |
| Future HR and Business Services | Scalable service model that can support new teams without copying unclear ownership patterns. |
SLA and workflow governance
The SLA redesign used P1-P4 priority tiers with response and resolution targets aligned to workflow behavior. That alignment matters because SLA reporting becomes unreliable when timers start, pause, or stop at points that do not match how agents actually triage, investigate, approve, and close work.
| Priority | Response target | Resolution target | Use case |
|---|---|---|---|
| P1 | 1 hour | 8 hours | Major incident or service-impacting critical issue. |
| P2 | 4 hours | 3 business days | High-priority service issue or important business-impacting request. |
| P3 | 8 hours | 5 business days | Standard support request requiring normal queue handling. |
| P4 | 8 hours | 90 business days | Lower-priority request, planned work, or long-running non-urgent item. |
Change management also received a more structured lifecycle with intake, review, approval, CAB support, implementation, closure, and completed-with-issues handling. That gives teams a clearer path for controlled change without forcing all support work through the same process.
Vendor, procurement, and security intake
A separate vendor/procurement intake path was designed to capture risk and review data earlier. The intake model included more than 35 fields across vendor details, cloud and security posture, compliance, operational fit, privacy, risk, and review routing.
Security and cloud posture
Privacy, compliance, and risk
Operations and vendor details
Before and after
| Area | Before | After |
|---|---|---|
| Ownership | Shared service model made team ownership harder to see. | Service areas separated by team, queue, request type, and reporting need. |
| Workflows | Different work patterns competed inside broad request handling. | Four core workflows optimized around support, incidents, change, and vendor/security intake. |
| SLA control | SLA logic needed more specificity by request type, priority, and team. | P1-P4 structure aligned to workflow start, pause, and stop behavior. |
| Automation | Rules were difficult to isolate, audit, and maintain as the platform grew. | 15+ automation and notification rules reviewed and redesigned for clearer ownership. |
| Visibility | Sensitive requests required stronger access control. | Visibility model reviewed for restricted request types and controlled handling. |
| Licensing | More than 100 JSM agents were licensed in the environment. | Practical active-agent need estimated closer to 30-35 users, creating an optimization opportunity. |
Outcome
AtlasOptima helped the organization move from a shared, hard-to-scale JSM setup to a cleaner multi-service model with better ownership, stronger governance, and a platform foundation ready for future service teams.
The engagement created a clearer operating model across IT Helpdesk, Salesforce/Registry Support, Change Management, and Vendor Procurement intake. It also improved the foundation for reporting by team, request type, SLA priority, change status, and request status while reducing administrative complexity in request catalog and automation design.
What similar teams should validate
Multi-team JSM environments usually become fragile when ownership, request types, SLAs, and automation rules grow faster than the operating model. Before adding another team or portal, validate the platform design against these questions.
Which teams own each service area, queue, request type, automation rule, and report?
Which request types need distinct workflows instead of generic issue transitions?
Do SLA start, pause, and stop rules match how agents actually work the ticket?
Which request types contain sensitive details and need restricted visibility?
Which automation rules can be isolated by service, request type, or team before they become hard to audit?
Which licensed agents are active operators versus historical, occasional, or administrative users?
Common Questions
JSM Optimization Questions
The questions that usually come up when a shared Jira Service Management environment starts supporting multiple internal teams.
What did AtlasOptima optimize in this Jira Service Management engagement?
AtlasOptima reviewed the JSM operating model, service ownership, request types, workflows, SLAs, automations, notifications, reporting, sensitive-request visibility, and vendor/security intake structure for a multi-team regulatory environment.
How many teams, request types, and agents were reviewed?
The selected engagement covered approximately 8 internal service teams, more than 25 request types, and more than 100 licensed JSM agents. The practical active-agent requirement was estimated closer to 30-35 users.
Are these JSM optimization results guaranteed for other organizations?
No. These are case-qualified findings from one selected engagement. Outcomes depend on each organization's service catalog, agent usage, workflows, permissions, automation design, reporting needs, and governance constraints.
Need to clean up a growing JSM environment?
AtlasOptima can review service ownership, request catalog structure, SLAs, workflows, automation rules, reporting, permissions, and license usage before the platform becomes harder to govern.