DATA DEMOCRATIZATION THROUGH SELF-SERVICE ANALYTICS: ADOPTION BARRIERS AND PERFORMANCE OUTCOMES

Abstract

This study focuses on the adoption challenges of self-service analytics and how these adoption challenges affect the performance of an organization in the context of data democratization. Self-service analytics is a major method for providing organizations with data access beyond technical departments to support timely and evidence-based decision making. But, there are some organisational and technical conditions that need to be fulfilled if it is to be successful. The barriers discussed in the study are data quality, data governance, data literacy, security, and organizational resistance. It also examines how adoption of self-service analytics can help achieves performance metrics such as decision speed, operational efficiency and organizational agility. A quantitative, cross-sectional research design was adopted and a structured questionnaire was used to collect data from employees, managers, analysts and business users who have experience with analytics based decision-making. The results reveal that data quality, governance, literacy and organizational resistance are all key drivers of adoption, while security concerns have a lesser impact. Also, there is a positive relationship between self-service analytics adoption and organizational performance. In summary, the study suggests that, while data democratization is a key to better organizational effectiveness, it needs good data governance, user capability and data infrastructure.

Keywords: Self-service analytics; data democratization; adoption barriers; data quality; data governance; data literacy; organizational resistance; organizational performance.