A Data-Driven Decision Support System to Enhance Progress Control Accuracy and Decision-Making in Construction Planning
Creators: Pourrahimian, Elyar
Publisher: name: University of Alberta Library
Year: 2024

<p>Planning and control are the two pillars of a construction production system. A project monitoring and control system aims to minimize deviations from project plans by identifying and reporting the project’s status, comparing it to the plan, analyzing deviations, and taking corrective actions. While a single control method may be suitable for early project phases, it can be ineffective in later phases or more detailed levels. Traditional construction management methodologies often fail to address unforeseen challenges and uncertainties. Projects can exist in various states—often unidentified by project managers—that necessitate different approaches, highlighting that one-size-fits-all methods are insufficient. The complex and dynamic environment of construction projects is influenced by unexpected weather conditions, sudden material shortages, labor disputes, and unanticipated technical difficulties, which can significantly impact project timelines and costs. The dynamic interplay of these factors creates an environment where traditional control methods often fail to accommodate the non-linear and stochastic nature of construction processes. Indeed, traditional methodologies, which typically rely on rigid planning and control mechanisms, often lack the flexibility and adaptability to respond effectively to such disruptions. The complexity and unpredictability inherent in construction project management underscore the necessity for adaptive management techniques to respond effectively to sudden changes and disruptions. <br>
Accordingly, this research aims to enhance project control accuracy and decision-making in construction planning by developing a data-driven decision support system that integrates multidimensional project control methods. Specifically, the study emphasizes the importance of adaptive management techniques that address the complexities and uncertainties inherent in construction projects. The research highlights the transformative potential of combining traditional and innovative control methods to improve project outcomes. Three major objectives are outlined as follows: 1) understand how a multidimensional control approach can mitigate limitations of single-method frameworks, improve decision-making, and enhance project outcomes in the face of uncertainties and variations; 2) develop a progress control framework for better project evaluation, analytics, and sense-making; and 3) develop a decision support system to evaluate recovery plans by including situated-based data. In addition to these objectives, a portion of this research is dedicated to validating the proposed framework through a detailed case study and expert consultations. <br>
By offering innovative frameworks that incorporate multiple perspectives, this thesis aims to improve decision-making, enhance progress control accuracy, and ultimately contribute to more successful construction project management. Through these multidimensional approaches, project managers can better understand project dynamics, better anticipate potential issues, and implement more effective control strategies, leading to improved project outcomes and efficiency.</p>