Building an effective system of information and analytical support for enterprise management: tasks and challenges

Purpose. The purpose of this study is to identify key challenges and areas for improvement in establishing an effective information and analytical support (IAS) system for enterprise decision-making. The research examines critical issues necessary for optimizing information flows and explores how current challenges impact IAS functionality in today’s dynamic business environment. Design / Method / Approach. A decomposition approach is applied to break down the IAS process into specific challenges, focusing on subject-oriented and organizational aspects. Systems analysis is used to assess interdependencies within IAS and map out interactions between departments involved in data handling. Findings. The study identifies essential IAS effectiveness criteria, such as relevance, timeliness, and comparability of information, along with the ability to analyze data in detail. It also highlights modern challenges like large data volume management, adapting to rapid market changes, and maintaining data security. The success of IAS implementation is shown to depend on interdepartmental cooperation and clear alignment of responsibilities. Theoretical Implications. This work enhances theoretical understanding by modeling the IAS process as a structured component of enterprise management, where interdepartmental processes are essential for success. Practical Implications. Insights from this study support managers in structuring IAS processes that are more responsive, data-driven, and resilient. It also serves as a guide for companies transitioning from outdated systems to more flexible platforms. Originality / Value. This study provides a comprehensive approach to IAS challenges by integrating theoretical models with real-world constraints, offering a framework for incorporating big data, AI, and machine learning into IAS for effective decision-making. Research Limitations / Future Research. Further and more in-depth analysis is required for substantive and organizational-methodological issues of responding to the challenges identified in the research.