Factor-based big data and predictive analytics capability assessment tool for the construction industry

Abstract

Big data and predictive analytics have huge potential to create value to the construction industry. However, there is a lack of benchmarking system to evaluate organizations' competency to adopt big data and predictive analytics. Hence, this study aims to develop a big data and predictive analytics capability assessment tool that can measure construction organizations' capability in big data and predictive analytics implementation and that also highlights strengths and weaknesses of the organization to provide a benchmark in the process of big data and predictive analytics implementation. 21 determinants were identified and assessed in sense of their impacts on an organization's capability to implement big data and predictive analytics. These determinants were categorized into five determinant groups and assigned weights, to form the basis for the big data and predictive analytics capability assessment tool. The developed tool was then validated with four construction organizations to reflect their big data and predictive analytic capability levels, strengths and weaknesses. The findings of this study contribute to knowledge and practice by identifying the determinants impacting construction organizations' capability to adopt big data and predictive analytics and in the development of a computerized assessment tool which also serves as a benchmarking tool for construction organizations in the implementation of big data and predictive analytics.