аналитика персонала,
управленческие решения,
цифровая трансформация,
оптимизация кадровых процессов,
организационная эффективность,
управление человеческими ресурсами,
цифровые технологии в менеджменте
Abstract
Problem. The digital transformation of organizations necessitates a re-evaluation of traditional human resource management approaches, which are predominantly based on managerial intuition and expert experience. The existing gap between accumulated Human resources (HR) data volumes and managers' inability to transform this data into informed management decisions leads to a decrease in the effectiveness of human resource management processes. Additional barriers include data fragmentation, low levels of corporate digital maturity, and insufficient readiness of managers to adopt an evidence-based approach to management. Methodology. The research was conducted within the framework of integrating human resource management theory, the concept of data-driven management, and the methodology of people analytics. A comprehensive approach was employed, including systemic, process, and competency analysis. The empirical basis comprised the results of a secondary analysis of people analytics implementation cases in Russian and international companies, data from industry reports, and materials from semi-structured interviews with HR managers and department heads. Research Results. Key areas of analytics application were identified: forecasting employee turnover risks, enhancing the effectiveness of recruitment and training, optimizing labor costs, and increasing organizational performance. It was established that the greatest effect is achieved by transitioning to proactive management, where analytical models complement, rather than replace, managerial intuition. Specific implementation barriers were identified: for Russian companies, critical limitations are human resources and infrastructure constraints, while for international companies, ethical and regulatory challenges related to personal data protection are paramount. Practical application. The research results can be used by organizations in developing people analytics systems and formulating digital HR management strategies. The proposed classification allows for assessing a company's level of readiness for people analytics implementation and developing targeted roadmaps. The materials are applicable in training and professional development programs for managers and HR specialists focused on developing competencies in data-driven decision-making.
