INTEGRATED MODEL FOR ASSESSING FINANCIAL RISKS OF DELAYS IN SCRUM PROJECTS OF IT OUTSOURCING

Abstract

The article is devoted to the development of an integrated model for assessing financial risks of delays in Scrum-based IT outsourcing projects. The relevance of the study is driven by the growing role of IT outsourcing in Ukraine’s export structure and the significant financial losses associated with schedule overruns and violations of Service Level Agreements (SLA). In international outsourcing contracts, project delays directly translate into financial consequences, including additional operational costs, contractual penalties, opportunity costs, and reputational losses, which necessitates a quantitative and economically grounded risk assessment approach.

The study systematizes delay factors in Scrum projects and proposes their classification into technical, organizational, communication-related, and external categories, each associated with early warning indicators. A formal relationship between Scrum team productivity metrics (velocity, sprint burndown deviation, and lead time) and the probability of delay occurrence is established through the development of an integrated Delay Probability Index (DPI). Based on the Cost of Delay concept, a comprehensive model of financial impact is constructed, incorporating direct costs, SLA penalties, opportunity losses, and reputational risks related to potential client churn.

An integral Financial Delay Risk (FDR) indicator is proposed, combining delay probability and financial impact into a single monetary metric. In addition, a decision-making algorithm based on threshold risk levels is developed to support managerial actions ranging from routine monitoring to crisis management. The practical significance of the proposed model lies in its applicability for preventive risk management and early detection of financially critical delays in Scrum-based IT outsourcing projects. The model provides a foundation for reducing financial losses through timely managerial intervention and creates prerequisites for further empirical validation and automation via integration with project management information systems.