This study examines the role of Big Data Analytics (BDA) in supporting Management Control Systems (MCS) within the Irish agri-food and beverage sector. Using qualitative data gathered through semi-structured interviews with financial controllers, management accountants, and IT managers, the study investigates how BDA is implemented to improve organisational control and decision-making. The analysis is grounded in Strong Structuration Theory (SST), offering a detailed perspective on the dynamic relationship between technological capabilities and organisational structures. The findings highlight the transformative potential of BDA in fostering more responsive and strategically aligned MCS. Theoretically, this study emphasises the importance of organisations developing the ability to extract information from diverse data sources to support decision-making and other organisational functions. It offers specific insights into factors that influence the effective use of BDA to ensure a robust MCS, which have not been previously documented in the literature, thus making a significant contribution. BDA helps organisations stay aligned with their strategies, thereby increasing the chances of achieving their primary goals. It highlights that both external factors (such as regulations and market demands) and internal structures (like organisational strategies and employee capabilities) influence the effective integration of BDA into MCS. Using SST, the research provides a framework to analyse how managers, technologies, and organisational contexts interact to shape outcomes. Practical contributions emphasise recommendations that show how the challenges of implementing MCS can be mitigated by using BDA technologies. Practically, the study shows that BDA improves traceability, compliance, and sustainability while enabling more accurate forecasting and real-time decision-making. Ultimately, it emphasises the importance of strong communication between IT and operational teams to fully realise the benefits of data-driven management control. The study illustrates how BDA helps monitor productivity, optimise resource allocation, and reduce waste throughout the value chain. While there are limitations to the study, the research provides strong theoretical and practical contributions and lays a clear foundation for a stream of research on how BDA affects MCS, and how MCS affects the use and operationalisation of BDA.