Cross-Level Stakeholder Alignment in Data Platform Management : A Case Study of Strategic, Tactical, and Operational Perspectives

Abstract

Since data platforms gain importance as organizational enablers for data driven-decision making and shift from purely technical to socio-technical systems involving multiple stakeholders with differing interests and needs, this thesis focuses on examining the challenges faced by organizations when aligning business objectives, technical capabilities and operational realities. Especially misalignment issues between strategic, tactical and operational organizational levels are investigated and an alignment strategy that helps eliminating avoidable and managing unavoidable tensions is suggested. By answering the three research questions, this study aims to gain an understanding of how stakeholder needs and priorities are translated into decisions, what types of misalignments occur, and which practices contribute to sustained alignment. This thesis follows a qualitative, exploratory methodology based on a case study, which allows to identify patterns of stakeholder interaction as well as alignment and its failure. Data is collected through semi-structured interviews with stakeholders from different organizational levels and analysed following an inductive coding and categorization approach. Alignment is found to be a dynamic process that is driven by communication and interaction across different levels. A data platforms technology is found to support and shape alignment based on the utilization of its potential. The biggest threat to alignment is an inconsistent understanding of the strategic vision, unclear governance structures, and limited transparency in the integration and communication of feedback. To counteract the occurrence of misalignment, transparency, continuous communication, and structured stakeholder involvement are suggested.