Proceedings of the 70th International Academic Conference, Madrid

OPTIMAL SELECTION AND MANAGEMENT OF AN IT TEAM BASED ON MULTIFUNCTIONAL SPECIALISTS

SERGO TSIRAMUA, TAMAR TEVZADZE

Abstract:

Optimal Selection and Management of an IT Team Based on Multifunctional Specialists Sergo Tsiramua1, Sulkhan Sulkhanishvili1, Tamar Tevzadze1, George Tsiramua2 (1) The University of Georgia, Tbilisi, Georgia (2) Business Technology Department of Toyota Caucasus, Tbilisi, Georgia The development and efficiency of economic and financial institutions significantly depend on the smooth operation of IT services and IT transformation processes. The spectrum of IT directions is multifaceted, including IT infrastructure development, computer network and hardware, operating systems, security and data protection. In terms of development - system and business analysis, service planning, project management, data management, software, application development and support, quality management and testing. Based on the above, it is important that the implementation of an IT transformation is qualified as a significant strategic project and its implementation is carried out considering the best practices and methodologies of project management. One of the most important in this process is the formation and management of a resilient IT project team. We present logical-combinatorial and logical-probabilistic models of machine learning applied to complex reconfigurable systems. Structural reconfiguration is achieved through the multifunctionality of system elements, enabling interchangeability and replacement in cases of partial or complete failure. This increases adaptability, flexibility, reliability, and fault tolerance, which are quantitatively evaluated using logical-probabilistic methods. The methodology is implemented in OptiCrew - a platform which helps organizations in building resilient teams. Each team member is assessed across all potential roles, and optimization algorithms identify the best team configuration and role allocation. Scenario-based simulations—unavailability, performance dips, and scope changes—evaluate team robustness under stress. Teams with interchangeable personnel demonstrate higher reliability and reduced need for external replacements. Additionally, AI and natural language processing convert behavioral data into quantitative indicators, while Generative AI identifies skill gaps and provides targeted recommendations to improve team adaptability and performance.

Keywords: Multifunctional Personnel, Optimization Methods, Logical-Combinatorial and Probabilistic Modeling, Flexibility, Reliability, Team Resilience Acknowledgments The work was supported by the Shota Rustaveli National Science Foundation of Georgia. Grant #SC-24-753.

DOI: 10.20472/IAC.2026.070.019

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