IT practices that optimize management processes and enhance business profitability

Abstract

The purpose of the article is a comprehensive study of IT practices as a tool for optimizing managerial processes and improving business profitability, identifying the mechanisms of their influence on key financial and operational performance indicators, and forming scientifically grounded approaches to the selection and implementation of digital solutions in managerial activities.

The study is based on comparative analysis, systematization of empirical data from international cases, analysis of industry reports from leading analytical agencies, and quantitative assessment of the impact of IT practices on managerial and financial performance indicators. The theoretical foundation of the study is the Data-Driven Management paradigm, which treats data as a strategic management resource, as well as the concept of digital transformation of managerial processes.

The steady growth of global IT spending confirms the irreversibility of digital transformation as the dominant development vector of contemporary management. It has been established that the implementation of robotic process automation (RPA) reduces operational costs by 22–25%, lowering transaction costs from $15–20 to $3–5. AI tools have been found to improve managerial forecasting accuracy from 60–70% to 85–95%, while supply chain automation reduces inventory levels by 20–30%. CRM systems combined with AI analytics increase customer retention by 27% and improve the LTV/CAC ratio from 3:1 to 5:1. ERP platforms reduce management reporting time by 40–60% and decrease human error rates by up to 80%. A comparative analytical model of traditional versus IT-oriented management has been constructed, clearly demonstrating the advantages of the digital approach across six key criteria. Key performance metrics of IT practices across managerial functions have been systematized.

It has been proven that the maximum effect from IT implementation is achieved not through the isolated use of individual technologies, but through their systemic integration into a unified data-driven management architecture. A promising direction for further research is the development of industry-differentiated ROI assessment models for digital transformation, taking into account the specifics of SMEs and developing economies, particularly under conditions of military economy and limited investment resources.