Cost estimation and tendering optimization through data science for a multinational construction company

• Main Authors: Bulcke, Richard, Parmentier, Sébastien, Vanzieleghem, Jeroen
• Language: English
• Published: 2022
• Subjects: Princess Elisabeth Base; Antarc*; Antarctica
• Online Access: https://hdl.handle.net/20.500.12127/7214

BESIX, a large multinational contractor, is one of the few companies that is able to build the most extraordinary skyscrapers, hotels, maritime works and other infrastructure works in the world. The examples are countless and range from the Burj Khalifa (i.e., the tallest building in the world) and the Tour Triangle (i.e., the newest state-of-the-art building in Paris) to the Princess Elisabeth Base on Antarctica. Also, Legoland Dubai, Ferrari World Dubai, the Warner Bros Theme park and two of the new stadia for the 2022 Qatar World Cup are constructed by BESIX. Even the very own new campus building of the Vlerick Business School in Brussels is constructed under BESIX’ guidance. Unfortunately, due to a cloudy economic environment with rising material prices and the nature of the industry (i.e., low margin, high volume), the financial performance of the construction industry is lagging. As such, construction companies must find new and alternative ways to help them make a better selection of projects and a better cost estimation. Hence, they will be able to continue constructing such mesmerizing construction works all over the world. The construction industry has arrived late to the digitalization revolution. This means that lots of untouched potential in data-driven decision-making and Machine Learning based optimization have yet to be discovered. Luckily, driven by its mission to create sustainable solutions, BESIX is already quite developed in its data management. The next step is to use this lead and start using data analytics to increase its profitability. The goal of this In-Company Project is to help BESIX choose better tenders and make a better cost estimation by using data science and exploiting the Master Data Management. The project is structured around three business use cases that help keep focus and attain the objectives of increasing BESIX’ profitability and efficiency. The first business use case calculates a probability of winning a tender by using historical tenders and their win rate. By only ...