Abstract
Construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals and supporting enterprise resource planning systems. The construction sector continues to struggle with the management, analysis, and transformation of data into useful information for improved decision-making. While development of data-driven decision support systems for construction would improve the accuracy and relevancy of decision-making processes, several challenges currently limiting the incorporation of dynamic project data into prediction models must first be addressed. An envisioned solution for advancing data-driven decision making in construction using a simulation-based analytics framework capable of overcoming such limitations is presented and discussed. Concept feasibility is demonstrated through the successful completion of a prototype for quality-associated decision support that has been developed using the proposed conceptual framework.
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