APPROACHES TO CHOOSING METHODOLOGIES FOR PLANNING IT PROJECTS ACCORDING TO THEIR KEY CHARACTERISTICS

Abstract

The article investigates the peculiarities of planning methodologies in IT project management, focusing on the formation of a system of methods applicable at various planning stages. Due to the rapid development of information technologies and the specific characteristics of software engineering, IT projects increasingly rely on agile approaches that ensure adaptability, stakeholder involvement, and incremental development. The study compares general project management processes described in the PMBOK Guide with those typical for IT development projects, identifying discrepancies in stages, such as implementation and support, which are critical in software life cycles. A classification of key features of both traditional and agile project methodologies, including Waterfall, Scrum, Kanban, Lean, Spiral, RAD, PRINCE2, and V-Model, is presented. Each methodology is evaluated based on multiple criteria such as development duration, budget constraints, flexibility to changes, client interaction, error handling, and team structure. The authors develop a detailed recommendation matrix that aligns specific project characteristics with the most appropriate planning and development methodologies. It is concluded that for most real-world IT projects, a hybrid or situational approach combining elements of different methodologies is often more effective than strict adherence to a single model. Additionally, the article explores existing decision-making tools for methodology selection, such as the analytical hierarchy process (AHP), scoring models, and SWOT analysis, and discusses modern intelligent systems employing machine learning algorithms (e.g., random forest) to support decision-making in dynamic project environments. The research contributes to enhancing the quality of IT project planning by offering a practical, metrics-based framework for selecting methodologies tailored to a project’s unique parameters, ultimately improving project outcomes and minimizing risks.