Date of Award
Master of Science in Civil Engineering (MSCE)
Committee Member 1
Committee Member 2
Due to the unique nature of construction projects and the need for leaders in the business to have knowledge from multiple fields, it has become difficult for decision makers to confidently make choices in their complex working environment. Over time, data availability and computational power have both improved. Moreover, technological advancements from the past few years have overwhelmed the industry by generating a diverse amount data from various sources. This large amount of data makes it possible to find nuggets of information. However, in this digital era, collecting data is not the problem, but how to extract useful information is a big challenge. Existing analytics methodologies do not fulfill the needs of the construction industry because of its unique nature. The involvement of multidisciplinary participants is essential for sound decisions to be made in the industry. There are no integrated or unified solutions for the construction industry. In the absence of such solutions, people are making biased decisions based on their personal experiences. Poor information management is a long-standing problem for the construction industry because most data is buried in papers spread across different departments. Therefore, a new paradigm is needed to facilitate decision-making processes in the construction industry and build an analytical culture for organizations. This thesis presents the State-of-the-Art and State-of-the-Practice of analytics in different industries. However, existing analytical models and frameworks cannot resolve the construction industry’s data-and information-related challenges. Therefore, a new protocol is developed after understanding the specific needs of the construction industry. Later, to understand and implement the protocol, two case studies were solved using real-world data of the construction industry. This work serves as a foundation of analytics in the construction industry by providing a common platform for industry leaders. This platform will also help organizations overcome their individual, managerial, and cultural barriers.
Jain, Ashwini, "Analytics protocol for data-driven decision-making in the construction industry" (2017). Open Access Theses. 1290.