Curating the underlying dynamics of successfully aligning big BIM data: a strategic alignment approach

Purpose This study unpacks how big BIM data (BBD) can effectively transform vast volumes of information into actionable insights, focusing on process automation, cognitive insight and cognitive engagement through the use of strategic alignment model (SAM). It aims to identify the critical success factors (CSFs) that enable organisations to leverage BIM-driven intelligence to enhance stakeholder interactions, optimise decision-making and align digital transformation with specific business needs in the architecture, engineering and construction (AEC) sector. Design/methodology/approach Semi-structured interviews were conducted with 20 BIM experts from academia and industry, selected through purposive and snowball sampling via an industry panel and online platforms. They were complemented by secondary data sources for triangulation. These include documentation from online sources and non-participant observation, such as marketing materials, offering valuable insights into the organisation’s identity, culture and decision-making processes. Data were systematically analysed using deductive thematic analysis based on the SAM framework in NVivo 12. Findings The study identifies 36 CSFs associated with BBD in automating processes, enhancing cognitive insight and improving cognitive engagement by aligning BIM and big data strategies. It also identifies challenges such as fragmented workflows, resistance to change and strategy alignment complexities. Practical implications The study engenders actionable guidance for aligning technical capabilities with strategic objectives, offering insights for practitioners into enhancing operational efficiency and strategic alignment in AEC organisations. Originality/value The contribution of this study is threefold, namely, (1) theoretically expanding SAM, a well-established but underutilised model in the AEC sector, to provide novel insights into its relevance for strategic alignment within the industry; (2) contextualising BBD attributes for practice in AEC organisations to engender actionable implications for aligning technical capabilities with strategic objectives and (3) setting forth a platform for future research to advance understanding of analytical techniques across different alignment perspectives.