The Role of Data-Driven Decision-Making in Reducing Project Delays and Cost Overruns in Civil Engineering Projects

Abstract

The scale, complexity, and risks that may cause project delays and cost escalation tend to be characteristic of civil engineering projects. Although they are helpful in many cases, it is common to find that the traditional approaches to project management are not sufficient enough to embrace the multidimensional aspect of contemporary infrastructure development; leading to inefficiencies that cause an overlap in deadlines and costs. As a reaction, data-driven decision-making (DDDM) has become of becoming a phenomenon, and it uses sophisticated analysis tools, past data, and real-time surveillance technologies to maximize project efficacy. Through the incorporation of methodologies related to predictive analytics, Building Information Modeling (BIM), Internet of Things (IoT), and machine learning algorithms, project managers will be able to learn about possible risks and allocate resources more efficiently and ensure stakeholder communication.

This article will explore how DDDM can be used in civil engineering projects to minimize delays and cost overruns focused on the fact that DDDM has the potential to help solve persistent issues, like poor project forecasting, poor resource management and inefficiencies with multi-party coordination efforts. Case-based evidence globally on its projects shows that enterprises that applied data-driven approaches record a measurable value in their projects in terms of incoming project delivery, improving accountability, and cost optimization. Nonetheless, DDDM implementation is not challenge-free, and data-quality-, integration-, organizational-culture-, and upfront-investment-related barriers have been observed. Nevertheless, these shortcomings are balanced with strategic advantages especially in this age where the forces of infrastructure needs are ever increasing and efficiency is a forced challenge.

The paper has concluded that the consequential, disciplined incorporation of DDDM into civil engineering science and practice is not only a strategic requirement but also a door to resilient cost-effective and sustainable delivery of infrastructure.