Abstract
Given the importance of team quality in the success of a project, this chapter presents a summary of the results obtained in 10 years of work, dedicated to the study and development of models and tools for the formation of project teams, from identifying the diversity of factors that can be taken into account in different contexts. The main characteristics of a model and versions of a configurable tool that support the model are described, which facilitates its application in different contexts and allows experimenting with different algorithms and solution methods to identify those that offer the best results.
TopBackground
The last decade has seen an increase in work related to team formation as a whole, mainly since the research of Zakarian & Kusiak (1999), which identifies team formation as an optimization problem. Previously, many works considered only individual factors such as: staff competences or workload.
Research in this area addresses different aspects, including: the application context, the number of formed teams, the techniques, algorithms and approaches used in the solution, the development of tools to support the proposals and the factors to be considered.
The proposed solutions are associated to different contexts. Most of them focus on team formation of social network experts and student teams. Some allow to form one and others, multiple teams. Among the main techniques used are: the multi-criteria technique, exact techniques such as integer programming and approximate techniques such as heuristic and metaheuristic algorithms to solve optimization problems, in some cases with a monobjective approach and in others, with a multiobjective approach. There are investigations where support tools for the solution are documented.
Figure 1 shows the main factors taken into account in the analyzed works that address team formation.
Figure 1.
Individual and collective factors considered in team forming
Most of the analyzed investigations use a professional approach, because they take into account factors such as: the competences, experience and interest of people to perform tasks, roles or projects.
Key Terms in this Chapter
Myers-Briggs Type Indicator: This test measures four different dimensions of human preferences: Extroversion (E), Introversion (I), Intuition (N), Sense (S), Emotion (F), Thinking (T), Judgment (J), and Perception (P). From the values of each dimension, identify the psychological type of the person among the 16 possible types.
Technical Competences: These are associated with specific technical knowledge and skills of each position or role.
Feasible Solution: It satisfies the entire restrictions foreseen in the optimization problem. When at least one restriction of the problem is not met, the solution is considered not feasible.
Generic Competences: These are also called transversal and define characteristics referring to the general behavior of the person, independently of the specific technical knowledge. For example: communication skills and analytical skills.
Belbin Test: It allows to identifying the preferred and avoided team roles of each person, among the nine defined roles, which are grouped into three categories: mental roles (Plant, Monitor Evaluator and Specialist), action roles (Shaper, Implementer, and Completer Finisher) and social roles (Coordinator, Resource Investigator, and Teamworker).