State Planning in Russia: Challenges of Aligning Strategic Priorities with Budgetary Constraints and Pathways to Solutions

This paper examines the system that integrates two types of planning: strategic (long-term goals) and budgetary (resource allocation). The aim of the study is to identify existing challenges and propose solutions for effectively coordinating these two planning types, based on an analysis of the evolution of state planning in the Russian Federation from 1991 to 2024. The research methodology includes systems analysis, evaluation of regulatory documents, and expert data, drawing on the concepts of program-targeted management and digital transformation. The empirical basis consists of reports from the Accounts Chamber of the Russian Federation, PEFA instruments, and IMF recommendations on the digitalization of public financial management. The results show that, despite the reforms implemented between 2004 and 2021, misalignment between strategic and budgetary indicators persists, along with departmental fragmentation, vulnerability to external shocks, digital threats, regulatory inconsistencies, and a shortage of qualified personnel. To address these imbalances, the author proposes improving indicator development through multi-level KPIs supported by machine learning and blockchain; establishing an interdepartmental scenario modeling platform based on artificial intelligence; implementing adaptive budgeting; and unifying the regulatory framework through a State Planning Code. The findings highlight that successful modernization depends on the synchronized development of technology, institutions, and human capital. However, even with the implementation of the proposed measures, complete resolution of the issues is unlikely due to systemic inertia and external risks. The paper emphasizes the need for a comprehensive approach that combines digitalization, regulatory reform, and the strengthening of data-driven governance. Solving the identified problems also requires overcoming structural imbalances and investing in institutional capacity-building, particularly under conditions of ongoing uncertainty. The study is intended for government program developers, digital architects in the public sector, and institutional reform experts seeking to bridge the gap between long-term strategies and budgetary realities through the integration of advanced technologies (AI, blockchain) and adaptive management practices.

Authors

Institutions

Publication Details

Journal
Management Sciences
Published
2025-06-24
DOI
https://doi.org/10.26794/2304-022x-2025-15-2-37-52
Primary Topic
Regional Socio-Economic Development Trends
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

State Planning in Russia: Challenges of Aligning Strategic Priorities with Budgetary Constraints and Pathways to Solutions

V. A. Beloglazova
Management Sciences
Regional Socio-Economic Development Trends
article

State Planning in Russia: Challenges of Aligning Strategic Priorities with Budgetary Constraints and Pathways to Solutions

V. A. Beloglazova
article en

Abstract

This paper examines the system that integrates two types of planning: strategic (long-term goals) and budgetary (resource allocation). The aim of the study is to identify existing challenges and propose solutions for effectively coordinating these two planning types, based on an analysis of the evolution of state planning in the Russian Federation from 1991 to 2024. The research methodology includes systems analysis, evaluation of regulatory documents, and expert data, drawing on the concepts of program-targeted management and digital transformation. The empirical basis consists of reports from the Accounts Chamber of the Russian Federation, PEFA instruments, and IMF recommendations on the digitalization of public financial management. The results show that, despite the reforms implemented between 2004 and 2021, misalignment between strategic and budgetary indicators persists, along with departmental fragmentation, vulnerability to external shocks, digital threats, regulatory inconsistencies, and a shortage of qualified personnel. To address these imbalances, the author proposes improving indicator development through multi-level KPIs supported by machine learning and blockchain; establishing an interdepartmental scenario modeling platform based on artificial intelligence; implementing adaptive budgeting; and unifying the regulatory framework through a State Planning Code. The findings highlight that successful modernization depends on the synchronized development of technology, institutions, and human capital. However, even with the implementation of the proposed measures, complete resolution of the issues is unlikely due to systemic inertia and external risks. The paper emphasizes the need for a comprehensive approach that combines digitalization, regulatory reform, and the strengthening of data-driven governance. Solving the identified problems also requires overcoming structural imbalances and investing in institutional capacity-building, particularly under conditions of ongoing uncertainty. The study is intended for government program developers, digital architects in the public sector, and institutional reform experts seeking to bridge the gap between long-term strategies and budgetary realities through the integration of advanced technologies (AI, blockchain) and adaptive management practices.

Management SciencesVol. 15(2)
Saint Petersburg University of Management and Economics (RU)
Openalex Percentile: Top 75%
Regional Socio-Economic Development Trends
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.