SMARTALLOC : um modelo para alocação de recursos humanos em projetos baseado em aprendizado de máquina

Abstract

The present work presents SMARTALLOC, a model for allocations of human resources in projects that presents two contributions that were not found in any other related work: the possibility of choosing the company’s strategic objective (cost, time or quality) in the definition of allocation human resources; the use of project history and previous human resources using machine learning to make future recommendations. Effective project management has become increasingly important and strategic for organizations that want to achieve their goals. Mistakes made in allocating human resources to perform tasks may compromise the expected result of the project. After a systematic review of works that presented models for allocations of human resources in projects, two gaps were perceived that enabled the development of a model that would bring a new approach to the area. A prototype was implemented and applied in the evaluation by project managers of 2 organizations who answered structured research in the Technology Acceptance Model (TAM) methodology, confirming the usability of SMARTALLOC. Then, the Accuracy calculation of the machine learning algorithm was measured, whose ideal value should be 1. In 6 projects in the first company, the average was 0.77. In the second company, the average was 0.70 in 3 projects. Both project managers considered the SMARTALLOC model to be useful in allocating human resources to projects.