Summary
This position paper addresses the challenges of analytics adoption in enterprise environments, focusing on the reasons why Business Intelligence (BI) and Artificial Intelligence (AI) tools often fail to achieve widespread utilization despite significant investments. The document outlines that the primary issue is not a lack of training or skills but rather a product experience problem, particularly related to discoverability. It details ten common failure patterns that hinder adoption, such as tools designed for power users, broken discoverability, and lack of trust in data. The paper argues that organizations that succeed in analytics adoption prioritize making analytics easy to find and trustworthy. It also critiques conventional remedies like additional training and change management, suggesting that these do not address the underlying issues. Furthermore, the paper proposes a framework with five conditions necessary for creating an analytics environment that users will adopt, emphasizing the importance of a unified access point and measurable adoption metrics.
