This post shares Fusion CX Analytics sample content as part of Oracle Fusion Data Intelligence (FDI), a family of prebuilt, cloud-native analytics applications for Oracle Fusion Cloud Applications. These sample artifacts are intended to demonstrate potential use cases, accelerate implementation efforts, and provide examples of how customers can extend and customize FDI content to meet their business needs. To explore additional reusable sample content, visit the FDI Content Library.
Content Description: Service Request Analysis provides service leaders with a consolidated view of service request demand, operational backlog, critical issues, agent workload, customer activity, intake channels, service categories, aging, and resolution performance.
The AI-enabled workbook combines curated dashboards with a contextual OAC AI Agent. Users can review predefined operational views and ask natural-language questions to extend the analysis, compare performance across dimensions, investigate emerging workload, and obtain concise interpretations of the returned data.
Application: Fusion CX Analytics
Functional Area: CX- Service
Fusion Module: Fusion B2B Service
Target Persona: Customer Service Leader, Service Operations Manager, Support Manager, Contact Center Manager, Service Delivery Manager, Service Analyst
Subject Areas: CX - Service Request
Business Use Case/Questions:
- How many total, open, resolved, and critical service requests are there?
- How is service request volume trending over time?
- Which statuses account for the largest open workload?
- Which agents have the most service requests pending their action?
- Which queues contain the most unassigned service requests?
- Which customers generate the most open or critical service requests?
- Which customers have the greatest waiting or aging backlog?
- How are critical service requests distributed across new, in-progress, waiting, and closed stages?
- Which agents are handling the most critical service requests?
- Which channels generate the highest service request volume?
- Which channels have the longest average resolution time?
- Which service categories generate the most total and critical requests?
- Where is service request backlog most concentrated?
- How do service request volume and resolution performance compare across customers, channels, agents, queues, and service categories?
Pre-Requisites: 26.R2 or later
B2B Service Analytics must be enabled and the user must have the required permissions to access the workbook, Local Subject Area, and OAC AI Agent.
Download: FDI Content Library
Best Practices:
- Start with the overview, then drill into critical SRs, channels, service categories, agents, and queues.
- Compare SR volume with resolution time to identify workload and performance issues.
- Treat unassigned, pending-agent-action, and waiting-for-customer SRs as distinct operational queues.
- Review missing values and unusual outliers before drawing conclusions.
We’d love to get your feedback and business use cases to help build a more sample FDI content.
