RISK FORECASTING IN THE MANAGEMENT OF EXTERNAL FACTORS AFFECTING IT PROJECTS UNDER A FIXED BUDGET

Abstract

The study investigates project management methods and risk forecasting in fixed-budget IT outsourcing projects considering the nonlinear dynamics of the external environment. An integrated approach is proposed, combining traditional project management practices with modern risk forecasting techniques, including statistical models, time series analysis, and simulation methods. The research models the impact of market fluctuations, technological uncertainty, and regulatory changes on key project indicators, such as timelines, costs, and final product quality. Results demonstrate that risk forecasting enhances budget and resource planning accuracy, reduces the probability of schedule overruns, and ensures stability in project execution. The proposed methodology encompasses risk identification, quantitative assessment of probability and impact, and adaptation of the project management plan to environmental changes. Modeling outcomes define decision-making priorities and optimal response strategies to unforeseen factors. Practical implementation of this approach allows organizations to increase the efficiency of fixed-budget IT outsourcing projects, minimize financial losses, and improve product quality under variable market conditions. The study also outlines directions for future research, including the application of machine learning and big data to enhance risk forecasting accuracy and automate project management processes.