Summary
This position paper documents the challenges and failures associated with self-service analytics in enterprise environments. It identifies seven patterns that hinder effective self-service analytics, including a lack of a unified entry point, difficulties in content discoverability, and absence of trust signals for users. The paper explains that conventional remedies, such as training and replacing BI tools, often fail to address the root causes of these issues. It outlines a framework consisting of five essential conditions for successful self-service analytics, emphasizing the need for a single, intuitive entry point, organization of content by business function, and visible trust signals. The paper also presents the Digital Hive approach, which aims to create a unified access layer for analytics across various platforms, enhancing discoverability and user experience. Recommendations for organizations are provided, focusing on auditing discoverability, establishing governance, and defining success metrics for self-service initiatives.
