This post shares Fusion HCM 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: An AI-enabled Specialization Outcome and Rating Insights Analytics workbook and agent that empowers Learning Administrators, Learning and Development leaders, HR Business Partners, and business leaders to analyze specialization outcomes, ratings, learning program effectiveness, and outcome trends across the organization. Using the HCM - Learning Items and Enrollments and HCM - Specialization Rating and Profile Outcome subject areas, the workbook provides actionable insights into specialization outcome performance, identifies high- and low-performing specialization outcomes, compares outcomes across learning programs, and monitors changes in specialization results over time. The workbook, together with an AI Agent, enables users to ask natural-language questions about specialization outcomes and ratings and quickly identify learning programs delivering stronger outcomes as well as areas that may require further review or improvement.
Application: Fusion HCM Analytics
Fusion Module: Oracle Learning Management
Target Persona: HRBP, Line Manager, Learning Specialist
Subject Areas: HCM - Learning Items and Enrollments and HCM - Specialization Rating and Profile Outcome
Business Use Case/Questions: This Workbook along with the AI Agent can answerbusiness questions like below
- What are the overall specialization outcome results across the organization?
- Which specialization outcomes have the highest performance?
- Which specialization outcomes have the lowest performance?
- How do specialization outcomes vary across different learning programs?
- What are the trends in specialization outcomes over time?
- How are specialization outcomes distributed across the organization?
- Which specializations have the strongest overall outcome results?
- Which specializations require attention based on their outcome results?
- What are the top N specialization outcomes based on rating?
- What are the bottom N specialization outcomes based on rating?
- How do specialization ratings compare across different learning programs?
- Which learning programs have the strongest specialization outcomes?
- Which learning programs have comparatively lower specialization outcomes?
- How do specialization outcomes vary by business unit?
- How do specialization outcomes vary by department?
- Compare specialization outcomes across learner populations.
- How have specialization ratings changed over the last three years?
- Which specialization outcomes have improved the most over time?
- Which specialization outcomes have declined over time?
- How do current-period specialization outcomes compare with the previous period?
Pre-Requisites: Learning Management and Hours
Download: Available in the FDI Content Library.
Best Practices
Be specific about the specialization, learning program, organizational population, rating, and analysis period required.
Always include the relevant time period when asking for trends or period-over-period comparisons.
Good Examples
- What are the overall specialization outcome results for the current year?
- Show the top 10 specialization outcomes based on average rating.
- Which specialization outcomes have the lowest ratings?
- Compare specialization outcomes across learning programs.
- Show specialization outcomes by business unit for the current year.
- How has the average specialization rating changed over the last three years?
- Which specialization outcomes improved compared with the previous year?
- Which learning programs have the highest specialization outcome ratings?
Avoid
- Generic questions such as "Show specialization performance."
- Asking for a trend without specifying an appropriate period.
- Combining specialization outcomes, ratings, learning programs, organizational analysis, and detailed learner information in one question.
- Requesting detailed learner-level information for a large population when summary analysis is sufficient.
- Using terms such as "highest performance" without identifying the rating or outcome measure when multiple measures are available.
We’d love to get your feedback and business use cases to help build more sample FDIContent.
