SUPPORTING DECISION MAKING IN SOFTWARE DEVELOPMENT USING AGILE TOOLS

Abstract

The article examines the significance of Agile tools as a means of supporting decision-making processes in software development under conditions of high uncertainty and rapidly changing requirements. Contemporary software projects are characterized by complexity and the necessity to respond quickly to market trends and customer demands, which makes the decision-making process a critical success factor. Traditional waterfall methodologies often prove ineffective because they require key decisions to be made at the early stages of a project when uncertainty is greatest. The paper analyzes the main types of decisions made by development teams: strategic (technology selection, architectural approaches), tactical (sprint planning, prioritization), operational (daily tasks, technical decisions) and adaptive (responses to changes). It substantiates principles for the effective use of Agile tools: data transparency through visualization and regular ceremonies; collective decision-making enabled by facilitation techniques; an empirical, data- and metrics-driven approach; adaptability and readiness to revisit decisions; and team autonomy for operational choices. Practical recommendations are developed for applying Agile tools depending on team size and project context: for startups and small teams, a minimalist approach focused on Kanban and basic metrics is proposed; for medium-sized teams, a full Scrum implementation with structured ceremonies is recommended; for large organizations, the need for scaling frameworks and centralized metrics systems is justified. The educational aspect of adopting Agile tools is emphasized: the use of digital boards, metrics, sprints and team meetings contributes to the formation of professional competencies in future IT specialists, the development of skills for working with requirements, risk analysis, and collective decision-making. Prospects for further research include studying the impact of artificial intelligence on the automation of decisionsupport and analyzing the effectiveness of Agile practices in distributed teams.