A DATA-DRIVEN APPROACH TO SUPPLIER SELECTION IN INDUSTRIAL CONSTRUCTION PROJECTS
Abstract
The process of selecting suppliers is a formidable challenge in managing industrial construction projects. Construction companies generate a huge amount of data that is spread across multiple databases, but this data is not used to support decisions for future projects. To address this issue, a data warehouse was developed specifically for construction companies which are specializing in industrial projects. The proposed data warehouse utilizes operational databases from past projects, including planning and execution details, to organize and analyze data for supplier selection decisions in ongoing and future projects. The warehouse's dimensional model was built to meet the requirements of construction enterprises and the available data. The methodology employs Online Analytical Processing (OLAP), which enables direct queries and generates relevant reports to support construction management decisions and evaluate suppliers for different types of work. By adopting this approach, construction companies can make more informed decisions about which suppliers to choose for their projects, ultimately improving their economic performance. By leveraging the data available to them, these companies can enhance the quality of their decisions and improve outcomes for their industrial construction projects.
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References
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