Project-Lifecycle Data as the Conceptual Basis for Data-Driven Governance in Global IT Programmes
Purpose: This paper presents a case study of a global IT programme in the pharmaceutical industry, demonstrating that a structured data model can serve as a basis of data-driven programme governance. Coherent, accountable, and predictable data flows play an important role in enhancing predictability, transparency, and operational efficiency of large-scale initiatives, the study contends. Design/Methodology/Approach: Qualitative case study design was employed. As an active participant in the programme, the author did participatory observation, information-flow mapping, and data-model design as part of the research. Empirical material consisted of operational data from Jira, Monday.com, ServiceNow, and Google Sheets. Project documentation and meeting records also formed part of the evidence. Findings: The analysis identified severe fragmentation of data sources as well as ambiguity of ownership, with implications for decision time delays, duplication of tasks, and less audit trail. The development yielded a consolidated model that was Single Source of Truth based. It helps to organize roles, processes, and responsibilities along common datasets in which responsibility for decisions is traceable, thereby providing a means of bringing back uniformity and responsibility for decisions made. Practical implications: The proposed methodology can be utilised in another, equally complex programme to reduce coordination cost, build better data stewardship, and allow for evidence-based policy choice. It establishes an approach of logical integration of operational execution with strategic governance through orderly flows of information. Originality/Value: By demonstrating that a data model constitutes a management approach, the research connects the project governance and data governance literature. It provides a repeatable model for converting decentralized project ecosystems into coherent, data-driven governance systems.