The construction industry works through projects; each project needs people who make its realization possible, and these people relate to each other, forming work teams. Thus, there is an important relationship between the projects and the team members of a construction project, who must be selected based on competencies that allow them to satisfactorily perform their role in the project and thus contribute to the project's success. This research aims to provide a systematic approach while also providing decisionmakers with best practices by demonstrating the application of the Choosing By Advantages (CBA) system tabular method in selecting a member of the project team. To this end, the research begins with a bibliographic compilation to consolidate the main factors that allow us to choose a new member of the project team. Later, the team is trained in the CBA system. The choice is determined by applying the Tabular CBA method to support a collaborative virtual platform and a remote communication program. Finally, the team decided and chose the new member to be part of the project team in the Project Control area.

Construction projects rely on the people in the project team; people are selected to perform their role satisfactorily in the project and contribute to its success. However, the selection in the hiring process has different biases that are often not perceived by those who decide to hire people. This research aims to present a study applying the Choosing By Advantages (CBA) Tabular method for the hiring process of a new team member, aligning the structure of the selection process with the five phases of the CBA system. The selection process is divided into two parts to reduce bias in decision-making: the first preliminary part uses information associated with objective data from the applicants' CVs without knowing their identities. The second part complements information knowing their identities obtained from personal interviews. In this research, we use a practical approach called the SEEDS Model®, represented in five categories of biases present in everyday thinking (similarity, expedience, experience, distance, and safety). Furthermore, the results demonstrate that CBA and SEEDS Model® help reduce bias in the selection process and choose people for their attributes representing their capacities, avoiding bias in the selection.