Advances in Consumer Research
Issue 3 : 614-624
Original Article
Decoding Linkage of Business Intelligence Systems with Organizational Performance of MSMEs in an Uncertain environment
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1
Indian Institute of Foreign Trade, B 21 Qutab Institutional Area, New Delhi, India.
2
Professor, Indian Institute of Foreign Trade, New Delhi
Abstract

The small and medium enterprises (Micro, Small and Medium Enterprises) is a vital part of the economy of the developed and developing world, as it generates jobs and innovations. Nonetheless, MSMEs tend to be in very uncertain environment with technological disruptors, volatile market, and ever evolving customer tastes. Business Intelligence (BI) systems have become the potent tools that help organizations to convert raw data into actionable information and help them make strategic decisions in such contexts. The purpose of the review paper is to crack the code of the connection between Business Intelligence systems and organizational performance of MSMEs that are working in uncertain environments. The research synthesizes recent publications published in 2021 to 2025 to assess the impact of the BI adoption on strategic decision-making, operational efficiency, competitive advantage, organizational agility, and learning capabilities. The results show that the effectiveness of the BI systems implementation depends on various dimensions, such as strategic alignment, organizational preparedness, technological infrastructure, environmental conditions, and the systematic adoption. All these factors define the extent to which MSMEs can use BI technologies to improve performance and resilience. The research offers a detailed conceptual model that describes the contribution of BI adoption into better performance in organizations in uncertain situations. The results indicate that insights facilitated by BI can help MSMEs to predict risks, streamline activities, and react to changing market environments in advance. The paper will add to the body of existing literature because it offers a combined interpretation of BI adoption and MSME performance as well as provides future research guidelines on digital transformation and data-driven decision-making

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Volume 3, Issue 3
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