Smart data, smart communities: how analytics propel SME growth in emerging economies

Purpose This paper aims to examine the impact of data-driven business development (DDBD) on SME performance using the balanced scorecard (BSC) framework, providing empirical insights on DDBD’s influence on financial, customer, internal business process and learning and growth dimensions. Design/methodology/approach A quantitative methodology was employed, collecting data from 198 small and medium-sized enterprises (SMEs) through a structured questionnaire. Partial least squares structural equation modeling (PLS-SEM) analyzed the relationships between DDBD and the BSC perspectives. Findings DDBD significantly impacts all four BSC dimensions, with the strongest effect on learning and growth, followed by internal business process, customer and financial performance. DDBD enables SMEs to leverage data for strategic decision-making, enhancing operational efficiency and competitiveness. Research limitations/implications The research focuses on SMEs within one country, limiting generalizability. Future research should include cross-regional studies and longitudinal analysis to evaluate long-term impacts. Practical implications This paper provides actionable insights for SME managers and policymakers to implement data-driven strategies for performance optimization. Social implications DDBD in SMEs supports economic development by enhancing resilience and fostering job creation. Originality/value This study integrates the resource-based view (RBV) theory with empirical evidence, showcasing DDBD as a critical capability for sustainable growth and competitive advantage, particularly in emerging economies.