Abstract
Data analytics adoption in small and medium enterprises (SMEs) is receiving much attention, as it represents a major technological opportunity for digital innovation. Recent studies demonstrate the positive impact of data analytics on small firm performance. Paradoxically, the level of successful adoption remains low. SMEs face challenges in building data analytics capability (DAC), namely the ability to analyze data effectively for decision-making and business management. This compromises their ability to create business value from this digital innovation. The existing research, focused on DAC and firm performance, lacks a comprehensive understanding of how SMEs build this capability. The issue lies in the fact that current DAC building models designed from empirical data in larger firms, whereas research explicitly asserts that SMEs have unique characteristics which influence their approach to technology adoption. There's a gap between what research recommends and the reality of the process in SMEs. The study employs a qualitative methodology with 55 semi-structured interviews across 33 SMEs in manufacturing, agriculture and services. Three SME profiles are identified, highlighting the influence of business models and organizational culture on their strategies for data analytics resource acquisition and capability building. The research contributes to entrepreneurship and IS literature by providing insights into the process of DAC building in SMEs and offering a framework illustrating the diverse approaches these firms take in leveraging digital data for business value. The study aims to assist owner-managers in strategically building data-driven capabilities relevant to their business activities.