As the digital economy integrates deeply into all facets of the real economy and the energy revolution advances, the power sector is at a pivotal juncture for restructuring its supply framework and modernizing its operational models.

Unlike traditional grid operations, the construction of a new-type power system emphasizes the coordinated interaction of source, grid, load, and storage, coupled with multi-energy complementarity. This evolution demands a more complex skillset from the workforce, necessitating enhanced expertise, superior technical proficiency, and rapid response capabilities. Consequently, leveraging human resource management is essential to explore governance strategies that align with the digital transformation trends within the power industry.

Strategic Shift: From Operational Efficiency to Digital Human Capital Appreciation

Historically, human resource management in power companies has prioritized business outcomes. Initial digital initiatives primarily focused on migrating processes online, not yet tapping into the intrinsic value of human capital. Deepening digitalization, power firms should integrate human capital theory to unlock higher-value HR functions, transforming employee knowledge, skills, experience, and innovation into quantifiable, reusable data assets. This shift challenges the conventional view of human resources as a cost center.

This transformation requires evaluation metrics to evolve from simple transactional turnaround times to a full-cycle, dynamic assessment of talent value, covering skill growth rates, project contributions, and innovation potential across different job families. For instance, evaluating production roles could incorporate automatically collected data like live-line work hours, precision in defect identification, or safety protocol compliance. Meanwhile, R&D roles might be assessed on patent conversion rates, implementation contributions to tech upgrades, or response times in rectifying grid faults. By establishing an integrated digital platform, data links between production, operations, and project management systems can be forged. This allows for the automatic aggregation and dynamic updating of these metrics, reducing subjective bias. It turns individual capabilities into measurable human capital units, offering traceable data for informed decisions on talent allocation and development.

Tool Evolution: Adopting Intelligent HR Solutions

The journey of HR tools in power utilities has progressed from basic stand-alone personnel information systems to networked e-HR platforms. Early tools were largely limited to data storage, approval workflows, and standard reporting, often providing only post-hoc summaries that fail to meet the dynamic talent management needs of the new power system. The emergence of generative AI and multimodal interaction technologies provides the necessary support for upgrading HR tools to a more intelligent level.

Smart recruitment systems embedded with large language models can parse resumes against detailed competency frameworks for niche power sector roles. They automatically generate "talent profiles," reducing information screening costs and diminishing human bias. Furthermore, immersive skills training platforms using virtual reality and digital twin technology can replicate high-risk operations, such as substation operations or line maintenance, allowing for safe, hands-on practice and quantitative evaluation of proficiency, while also recommending personalized training modules. Additionally, machine learning-based attrition prediction models can analyze correlations within multi-source data, including job rotation patterns, performance trajectories, and training engagement. This capability enables proactive identification of key-person risk, providing a preemptive basis for developing talent retention strategies.

Organizational Redesign: Moving Towards Flexible and Agile Workforce Models

The traditional HR framework in power companies is embedded within a hierarchical structure, with personnel allocation bound by fixed departmental roles and bureaucratic silos. This often impedes talent mobility, constraining the workforce needed for project-based and cross-regional collaborative efforts that are becoming more prevalent due to market-oriented reforms. A flexible staffing model, enabled by a digital talent-sharing platform, can dismantle these boundaries. It creates a unified talent pool, allowing for dynamic deployment of specialized professionals from different departments, business units, and subsidiaries.

For example, a provincial power company built a digital talent-sharing platform to support intensive smart-grid upgrade projects in county-level distribution networks. By drawing technicians from city power supply companies and research institutes specializing in relay protection and distribution automation, cross-functional project teams were formed without altering formal employment relationships. Performance for these teams is directly tied to project deliverables. The platform tracks task milestones and individual contributions in real-time. This method alleviates structural talent shortages at the grassroots level without additional headcount, while optimizing the utilization of high-end technical expertise across the entire region.