Data-Driven Public Budgeting: Business Management Approach and Analytics Methods Algorithmization

Digital data processing tools have enabled progress toward improving solutions for complex systems, such as state budget systems. The creation of general budgeting systems, specifically in regional communities, has shown results for data-driven budgeting using a set of decision analysis methods. Increasing public awareness of digitalizing public services is achieved through participation in the evaluation of expenditure budget results using online tools. A review of scientific works on information asymmetry has shown its significant influence on the quality and consequences of budget decision-making during the budget process. Furthermore, most data analysis methods focus on the scattered problem areas of budgeting. The aim of the publication is the formation of a data-driven budgeting system based on the quality conditions of digitized data collected and the support of the interaction of all budgeting participants, including citizens. The latest data-driven budgeting technology combines transparent data for decision-making, a business approach to achieving goals, and mutual involvement of authorities, executors, and citizens in the formation of the most perfect of the adopted decisions regarding public budgets through adjusting and feedback. For decision-making based on data, MCDM methods have been separated, and simulations of their use have been carried out to predict results. The findings of the research include both favorable and hindering prerequisites of using information for public budgeting based on gathered data. Limitations and possibilities for the methods of data analysis by algorithmization have been systematized. Based on business data management methods, prospects for data-driven decisions in public budgeting have been highlighted.