Organisation Name
UK Public Sector
Summary
Add a prebuilt Internal Help Desk analytics subject area, with supporting data pipelines and semantic model, to enable reporting on Internal Service Requests alongside the existing HR Help Desk analytics capability.
Current gap
In FAIDP/FDI , HR Help Desk analytics is available, but there is no equivalent prebuilt subject area for Internal Help Desk. Organisations using Internal Help Desk for non-HR employee services therefore lack analytics coverage for these requests.
Although Internal Help Desk reporting is available through OTBI, this does not address the need for integrated historical and cross-functional analytics within FAIDP/FDI.
Requested enhancement
Provide a supported Internal Help Desk subject area covering:
- Request volumes, status, priority, category, channel, queue and assigned agent.
- Created, resolved and closed dates; backlog ageing; response and resolution times.
- Request lifecycle, reassignment, reopening and milestone/SLA performance.
- Relevant organisational dimensions, including business unit, department and location, where available and authorised.
- Supported custom attributes, documented refresh behaviour and appropriate role-based and row-level security.
Include historical lifecycle data so customers can analyse backlog and service performance over time, rather than relying only on current request status.
Business impact
The gap limits visibility into non-HR employee support demand, service performance and workload distribution. Customers must build and maintain custom extraction, data models and dashboards, increasing implementation effort, cost and ongoing support.
Expected benefit
Native Internal Help Desk analytics would provide consistent service KPIs, reduce custom development and enable a broader view of employee support across HR and non-HR services, while preserving the required security separation.
Example business questions
- Which queues have the largest or oldest unresolved backlog?
- Which request categories drive demand and longer resolution times?
- Where are service targets being missed?
- How do demand and service performance vary by department, location and reporting period?
