ИНЖЕНЕРЛІК КОМПАНИЯДАҒЫ ЖОБАЛАРДЫ БАСҚАРУ ЖҮЙЕСІНІҢ ЦИФРЛЫҚ ТРАНСФОРМАЦИЯСЫ

Abstract

In the context of the digital transformation of the economy, improvements in project management efficiency are largely determined by the capacity to integrate data, automate analytical processes, and promptly monitor key performance indicators. Business intelligence tools are particularly important for engineering and project-based companies, as they enable organisations to consolidate fragmented information flows and create an integrated environment for supporting managerial decision-making. The purpose of this study is to substantiate the application of the Power BI analytical platform to improve project management efficiency at WKS LLP. The study employed systems, process-based, comparative, and economic-statistical methods. A comprehensive analysis of project-related business processes was conducted using the AS-IS and TO-BE model, together with a qualitative multi-criteria analysis of Power BI, Tableau, Qlik Sense, SAP BusinessObjects, Oracle BI, and IBM Cognos. The analysis revealed that the existing project management system at WKS LLP, based on Primavera P6 and Imperium, is characterised by insufficient integration between information systems, data fragmentation, a considerable proportion of manual data processing, and limited predictive analytics capabilities. Power BI was proposed as an analytical layer capable of integrating data, automating reporting, visualising KPIs, and facilitating the transition to data-driven management. The economic efficiency calculations showed that the time required to prepare reports could be reduced from 40 to 15 hours per month per employee, generating monthly savings of 125 person-hours for a department comprising five employees. With an investment cost of KZT 6 million, the estimated annual economic effect amounted to KZT 14.06 million, the calculated return on investment was 134%, and the payback period was approximately five months. The practical significance of the study lies in the applicability of the proposed approach to improving project planning, monitoring, and control, increasing the transparency of project activities, and enhancing the quality of managerial decision-making.