Statistical Quality Control for Enhancing Construction Project Performance: Statistician and Quantity Surveyor Perspective

Abstract

Statistical Quality Control (SQC) provides a powerful framework for improving project outcomes by integrating statistical methodologies with construction cost management principles. This paper explores how SQC techniques, such as control charts, process capability analysis, and acceptance sampling, can be applied in construction projects from the dual perspectives of a statistician and a quantity surveyor. From a statistician's standpoint, advanced statistical tools provide insights into process variability, cost optimization, and project timeline management. Meanwhile, the quantity surveyor contributes expertise in cost control, budgeting, and resource allocation. This interdisciplinary approach leverages data-driven decision-making to enhance project performance in terms of quality, cost efficiency, and timely delivery. The study utilizes data from 50 construction projects across Nigeria, employing statistical methods like hypothesis testing, regression analysis, and variance analysis, alongside quantity surveying techniques for budgeting and financial forecasting. The results reveal that integrating SQC with quantity surveying significantly improves project performance by reducing variability in costs and timelines. This collaborative approach demonstrates the complementary roles of statisticians and quantity surveyors in applying SQC techniques to enhance overall construction efficiency. The findings highlight the need for a stronger partnership between statistical and construction management professionals to drive optimal project outcomes. Recommendations for practical application and future research are discussed, with emphasis on bridging the gap between statistical analysis and construction cost management