This article examines why digitalization often yields limited improvements in public sector governance. It argues that implementing digital technologies fails to automatically enhance organizational control if the document-centric workflow typical of traditional bureaucracy remains unchanged. Transitioning to genuinely data-driven governance requires a fundamental shift not only in information systems but also in how managerial data is conceptualized and structured. Central to this transition is data modeling, which maps administrative activities into interconnected networks of events, roles, states, and outcomes. This approach shifts the operational focus from mere document processing to comprehensive informational support across the entire management cycle. Additionally, the study explores the workforce implications of this digital shift. Structural changes in the information environment demand new competencies from public sector executives and specialists, specifically in data literacy, decision parameterization, and data governance. Ultimately, the practical value of this research lies in its framework for designing data-driven public administration systems and establishing updated competency models for civil servants.
Key words
• public administration • digital transformation • bureaucratic management • data-driven governance • managerial information environment • data modeling • data governance • digital workflow • managerial competencies •
Cherkavskii Aleksandr Grigorevich
expert of GSPM, Presidential Academy, Moscow, Russian Federation
e-mail: cherkavskiy-ag@ranepa.ru
ORCID ID: 0009-0007-1914-0088
ResearcherID: PWG-1061-2026