Advanced International Journal of Multidisciplinary Research

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Measuring Skill Graph Drift in SAP SuccessFactors Talent Intelligence Hub for Career Mobility, Workforce Reskilling, and Skills-Based Talent Governance

Author(s) Manoj Parasa
Country India
Abstract Organizations increasingly rely on skills-based talent models to support career mobility, workforce reskilling, learning alignment, and long-term talent planning. However, the value of these models depends on the continued accuracy of relationships between employee skills, role requirements, learning content, proficiency levels, and career pathways. In large enterprise environments, these relationships often change faster than formal job profiles, skill libraries, and learning catalogs are reviewed, creating a measurable form of skill graph drift. This paper proposes a structured framework for measuring skill graph drift in SAP SuccessFactors Talent Intelligence Hub, with the purpose of identifying when skills, roles, courses, and mobility pathways become misaligned over time. The study models employees, skills, roles, learning items, goals, and career opportunities as interconnected graph entities and introduces drift metrics for skill demand change, role-skill alignment, learning coverage, skill supply movement, and career pathway stability. The proposed approach is designed to support practical governance decisions by classifying drift severity and linking each drift signal to corrective actions such as role profile review, learning content updates, reskilling prioritization, and career recommendation refinement. The framework is evaluated through an SAP SuccessFactors-aligned benchmark model and compared with manual taxonomy review, keyword-based matching, and static role-skill mapping approaches. The expected contribution of this study is a practical and measurable method for maintaining the reliability of skills-based talent decisions in enterprise HCM systems. By connecting drift measurement with workforce reskilling and career mobility governance, the paper provides organizations with a repeatable approach to improve skill data quality, reduce outdated role mappings, strengthen learning alignment, and support more accurate internal talent movement.
Keywords SAP SuccessFactors, Talent Intelligence Hub, skill graph, skill drift, skill taxonomy, career mobility, workforce reskilling, skills-based talent management, role-skill alignment, learning alignment, internal mobility, talent governance, workforce planning, skill gap analysis, human capital management, enterprise HCM, career development, learning management, job profile management, workforce analytics
Discipline Engineering
Published In Volume 1, Issue 1, July-August 2023
Published On 2023-08-02
DOI https://doi.org/10.62127/aijmr.2023.v01i01.1359
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