Data Driven Strategic Decision Making and Its Impact on Agribusiness SME Performances

Abstract

This study aims to explore the implementation of data-driven strategic decision making (DDDM) and its impact on the performance of agribusiness SMEs in West Java, Indonesia, within the broader context of digital transformation and increasing market uncertainty. A qualitative approach with a case study design was employed to capture in-depth insights into the experiences and practices of business actors. Data were collected through semi-structured interviews, participatory observations, and document analysis involving SME owners, managers, and operational staff selected using purposive and snowball sampling techniques. The findings reveal that the adoption of DDDM is still in a transitional stage, characterized by a gradual shift from intuition-based to data-informed decision making, with varying levels of understanding and utilization among participants. Key patterns indicate that while digital tools are increasingly used, their application remains largely operational rather than strategic, and is constrained by limited data literacy, resource constraints, and entrenched organizational cultures. Nevertheless, SMEs that consistently integrate data into decision-making processes demonstrate improved operational efficiency and market responsiveness. These findings contribute to a deeper contextual understanding of DDDM as a socially embedded and capability-driven process, extending existing literature on digital transformation in SMEs. The study implies the need for capacity-building initiatives, supportive digital ecosystems, and policy interventions that emphasize not only technology provision but also human and organizational development. Future research is recommended to adopt mixed-method approaches and broader geographical coverage to enhance generalizability and theoretical development.