Paper Number
ECIS2025-1092
Paper Type
CRP
Abstract
Enterprise-level Digital Transformation (DT) efforts often fall short of their intended outcomes, despite the availability of targeted solutions for individual challenges. This is frequently due to the complex and insufficiently coordinated interplay of initiatives, decisions, and stakeholders – driven in part by ineffective steering mechanisms and fragmented information logistics. Drawing on the revelatory case of OTTO, we demonstrate how enterprise-level steering can be systematically informed and supported through targeted business analytics, facilitated by enterprise architects. We show how business analytics not only inform but also support steering by shaping narratives and enabling timely interventions. Our findings contribute to the literature on steering committees by emphasizing their informational role and the subjective use of data in complex DT. We also outline future opportunities for design-oriented research, to further develop data-driven steering of DT.
Recommended Citation
Lösser, Benedict and Winter, Robert, "Data-Driven Steering of Digital Transformation: Case Insights from OTTO" (2025). ECIS 2025 Proceedings. 1.
https://aisel.aisnet.org/ecis2025/ent_system/ent_system/1
Data-Driven Steering of Digital Transformation: Case Insights from OTTO
Enterprise-level Digital Transformation (DT) efforts often fall short of their intended outcomes, despite the availability of targeted solutions for individual challenges. This is frequently due to the complex and insufficiently coordinated interplay of initiatives, decisions, and stakeholders – driven in part by ineffective steering mechanisms and fragmented information logistics. Drawing on the revelatory case of OTTO, we demonstrate how enterprise-level steering can be systematically informed and supported through targeted business analytics, facilitated by enterprise architects. We show how business analytics not only inform but also support steering by shaping narratives and enabling timely interventions. Our findings contribute to the literature on steering committees by emphasizing their informational role and the subjective use of data in complex DT. We also outline future opportunities for design-oriented research, to further develop data-driven steering of DT.
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