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 Library.
Content Description: This AI-enabled workbook combines operational service work order dashboards with an OAC AI Agent. It helps users track open and closed work orders, monitor backlog and incomplete work, evaluate compliance outcomes, analyze assignee and field execution performance, and drill into customer, product, installed asset, and individual work order details. The AI Agent allows users to ask natural-language questions about service workload, lifecycle status, backlog, compliance, assignees, customers, products, assets, geography, and request channels, complementing the workbook’s guided dashboards with on-demand analysis.
Application: Fusion CX Analytics
Fusion Module: Fusion B2B Service
Target Persona: Service Operations Manager, Field Service Manager, Customer Service Leader, Service Delivery Manager, Service Analyst
Subject Areas: CX - Service Work Order
Business Use Case / Questions: This workbook helps answer:
- How many service work orders exist overall?
- How many work orders are open, closed, not done, or not submitted?
- Is work order volume increasing or decreasing over time?
- Which work order statuses have the largest volume?
- Where is backlog building in the work order lifecycle?
- Which activity types drive the most service workload?
- Which activity types have the most incomplete work?
- How many open work orders are compliant or non-compliant?
- How many open work orders are expected to become non-compliant?
- Are closed work orders meeting resolution due-date expectations?
- Is SLA compliance improving or worsening over time?
- Which assignees or teams carry the highest workload?
- Which assignees have the strongest or weakest compliance performance?
- Which customers generate the most service work?
- Which products or installed base assets are associated with repeated work orders?
Pre-Requisites: B2B Service Analytics Functional Area must be enabled
Download: Available in the FDI Content Library.
Best Practices:
- Start with executive workload KPIs before drilling into status, compliance, and detail views.
- Use creation date filters to analyze workload trends over time.
- Use resolution due date views to evaluate SLA compliance and future compliance risk.
- Use installed base asset analysis to identify specific assets or serial-numbered products with recurring service demand.
- Use detail tables for operational follow-up on specific work orders requiring action.
- When asking about customers, the AI Agent uses Sales Account Name by default. Explicitly request another customer concept when required.
- Review negative counts, unexpected percentages, or other inconsistent values as possible data-quality conditions. The AI Agent reports the available dataset values and does not silently correct them.
- Use AI-generated responses to complement workbook visualizations and detailed records, and validate important operational decisions against the underlying service work order data.
We’d love to get your feedback and business use cases to help build a more sample FDI content.
