The SSBI Validation Paradox

Sammanfattning

Organizations increasingly use Self-Service Business Intelligence (SSBI) to democratize access to data and analytics. While this enables greater analytical autonomy for business users, it also creates situations where different dashboards and reports present conflicting analytical outputs. This study investigates how business users validate such conflicts in practice, as well as the counterintuitive consequence of using more analytical technology to simplify decision-making while simultaneously increasing complexity and uncertainty, a phenomenon referred to as the Validation Paradox. The study adopts a qualitative interpretivist approach based on six semi-structured interviews with business users across Swedish organizations. Using Work System Theory as a socio-technical lens, the findings show that validation is not primarily a formal or technical process, but an informal and reactive practice shaped by organizational context, user experience, and system limitations. The findings identify three recurring validation practices: domain-based anomaly detection, manual cross-checking through Shadow BI practices, and social escalation to technically capable colleagues. The study contributes to SSBI research by reframing Shadow BI as a validation mechanism rather than solely a governance risk, and by highlighting the importance of semantic governance and interpretive alignment for establishing trust in analytical outputs.