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The SSBI Validation Paradox

Oléhn, Rasmus LU and Mandl Aslan, Julian LU (2026) INFM12 20261
Department of Informatics
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
Oléhn, Rasmus LU and Mandl Aslan, Julian LU
supervisor
organization
alternative title
Exploring how Business Users Validate Conflicting Outputs in SSBI Dashboards
course
INFM12 20261
year
type
H1 - Master's Degree (One Year)
subject
keywords
Self-Service Business Intelligence (SSBI), Validation Paradox, Business Users, Data Democratization, Shadow BI, Semantic Gap, Work System Theory, Data Governance, Informal Validation Practices
language
English
id
9239419
date added to LUP
2026-06-16 12:35:58
date last changed
2026-06-16 12:35:58
@misc{9239419,
  abstract     = {{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.}},
  author       = {{Oléhn, Rasmus and Mandl Aslan, Julian}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{The SSBI Validation Paradox}},
  year         = {{2026}},
}