DATA-DRIVEN DECISION-MAKING IN PROJECT SCHEDULING: THE ROLE OF CPM AND LINEAR SCHEDULING MODELS

Abstract

In order to maximize resource allocation, reduce delays, and guarantee the successful completion of infrastructure and construction projects, effective project scheduling is essential. By contrasting the Critical Path Method (CPM) and the Linear Scheduling Model (LSM), this study investigates the function of data-driven decision-making in project scheduling. The study examines task durations, activity classifications, and resource consumption for both scheduling systems using statistical frequency distribution and mathematical modeling. The findings show that while LSM is beneficial for ongoing, resource-intensive tasks, CPM is better suited for task-based, sequential workflows. Because LSM is sequential, it uses more manpower and machinery, according to the resource usage study, whereas CPM allocates resources in a task-oriented manner. The study offers comparative insights into scheduling efficiency by normalizing resource utilization. The results have important ramifications for planners and project managers, assisting them in choosing the best scheduling strategy depending on execution tactics, resource limitations, and project complexity.