An Intelligent Digital Framework for Talent Management and Succession Planning in Thai Public Higher Education Institutions
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Abstract
Background and Objectives: Thailand’s higher education sector faces significant challenges in talent management and succession planning, driven by demographic shifts, evolving academic roles, and rapid digital transformation. Many universities are experiencing an aging workforce, shortages of qualified successors, and increasing demands for digital competencies. Existing human resource systems often lack integration, predictive capabilities, and comprehensive analytics, which limit leadership continuity and workforce sustainability. In this context, there is an urgent need for a unified and intelligent system that supports evidence-based decision-making and fosters leadership pipeline development. This study aims to develop an intelligent digital framework for talent management and succession planning tailored to the Thai higher education context, enabling systematic talent identification, performance optimization, and strategic workforce planning to enhance institutional agility and resilience.
Methodology: The study employed a conceptual development and design research approach, integrating principles from Design Science Research (DSR) and the System Development Methodology (SDM). A five-phase process encompassing literature synthesis, standards alignment, and best practices integration, framework conceptualization, system modeling, and framework validation was implemented. Gaps in human resource management and succession planning were identified through an extensive review of both global and regional practices. Alignment with international standards, including ISO 30414 (Human Capital Reporting), IEEE Std. 830–1998 (Software Requirements Specification), Thailand’s PDPA (Personal Data Protection Act), and ISO/IEC 27001 (Information Security Management), ensured compliance, interoperability, and data protection. Artificial Intelligence (AI)-driven analytics and digital HR best practices were incorporated to enhance predictive capabilities and operational efficiency. System modeling defined both functional and non-functional requirements, while expert validation confirmed the framework’s practicality, robustness, and strategic alignment with institutional goals.
Main Results: The proposed Talent Management and Succession Planning (TMSP) framework comprises six interrelated modules: Talent Identification and Development, Performance Management, Learning and Development, Succession Planning, Career Pathing and Internal Mobility, and Analytics and Strategic Insights. Functional capabilities include automated competency assessment, predictive succession simulations, Key Performance Indicator (KPI) and Objectives and Key Results (OKR) tracking, real-time dashboards, and AI-augmented analytics. Non-functional requirements emphasize security, usability, scalability, interoperability, and compliance with ethical and regulatory standards. The framework was underpinned by a three-tier architecture ensuring secure communication, seamless data integration, and adaptability to institutional growth and increasing complexity.
Discussions: The framework effectively bridges the gaps in traditional HR systems by integrating predictive analytics, modular interoperability, and alignment with both national and international standards. It enhances strategic decision-making, promotes transparency and accountability, and supports continuous learning and workforce development. Real-time monitoring, scenario-based simulations, and interactive dashboards enable proactive HR management, data-driven talent development, and institutional resilience in response to digital transformation.
Conclusions: The proposed TMSP framework offers a conceptually rigorous, technically feasible, and strategically aligned solution for higher education institutions. Through the integration of AI, analytics, and digital HR practices, it supports talent development, succession planning, and workforce sustainability while ensuring compliance, data security, and operational efficiency. This intelligent digital framework provides a robust foundation for advancing HR digital transformation, strengthening institutional capacity, and aligning human capital strategies with long-term organizational objectives and Thailand’s higher education reform goals.
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