Data-Informed Decision-Making within Construction; Definition, Practices and Challenges

Abstract

The construction industry has historically relied on experience and intuition rather than structured data when making decisions, despite increasing digitalisation and growing access to data. At the same time, the industry continues to face recurring challenges such as delays, cost overruns and projects failing to meet expectations. This study investigates how decision-makers within a large Swedish contractor define and use data-informed decision-making, as well as the barriers and opportunities associated with its implementation. A qualitative research design with an abductive approach was adopted, based on 15 semi-structured interviews with employees from different roles and departments within the case company. The empirical findings were analysed using thematic and narrative analysis and interpreted in relation to decision theory and existing literature on data use in construction. The findings show that data-informed decision-making is primarily viewed as a situational process in which data and human judgement are combined, where data is used to support, verify and challenge human judgement when evaluating alternatives and making decisions, rather than replacing it. The study also identified opportunities to improve decision-making through better utilisation of existing data and increased use of data on historical outcomes and processes. The findings suggest that such improvements could strengthen decisionmaking in several ways. However, structural, cultural and knowledge-related barriers were found to limit the implementation of more data-informed practices. The study concludes that data-informed practices have the potential to strengthen decision-making within the studied organisation, but that realising this potential depends on addressing organisational barriers rather than simply increasing the amount of available data.