From Small Decisions to Big Performance: How SMEs Leverage Big Data Analytics

Abstract

This paper explores the critical role of big data analytics (BDA) in enhancing decision-making performance and driving SME success. It examines how Small and Medium-sized Enterprises (SMEs) can leverage BDA as a dynamic capability to improve decision-making, leading to better organizational performance outcomes. By conducting a literature review, the study synthesizes findings from recent research to propose a comprehensive framework that identifies big data analytics capabilities (BDAC), as well as the mediators and moderators influencing BDAC and data driven decision-making (DDDM) relationship. Additionally, to complement the literature review and provide practical grounding for our framework, we analyze studies that use a case study approach on SMEs to examine how DDDM influences various aspects of SMEs’ performance. The study highlights key organizational capabilities (mediators) such as organizational culture, technological infrastructure, organizational ambidexterity and agility, collaborative business culture, open innovation practices, governance mechanisms, and dynamic decision-making capability, which facilitate the impact of BDAC on decision-making. Additionally, disruptions (moderators) such as data characteristics, environmental dynamism, and managerial resistance influence the strength of this relationship. Furthermore, we illustrate which aspects of SME performance benefit from DDDMM. This framework offers useful guidance for SMEs looking to improve their decision-making and stay competitive by using big data analytics. What makes it different from earlier models is that it combines core BDAC elements with real-world factors that affect SMEs, like internal capabilities and external challenges. It also adds to the academic conversation by showing how BDAC works as a dynamic capability in the unique context of small and medium-sized businesses.