Work Experience Robot - use of natural language processing techniques to develop an employee interaction system to measure job satisfaction

• Grant number: 19/09032-9
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Duration: July 01, 2020 - December 31, 2021
• Field of knowledge: Applied Social Sciences - Administration - Business Administration
• Valor Concedido/Desembolsado (R$): 80,213.40 / 0.00
• Amount includ. bound (R$): 199,915.60 / 119,702.20
• Principal Investigator: Isabella de Arruda Botelho Lacerda
• Grantee: Isabella de Arruda Botelho Lacerda
• Host Company: Pin People Tecnologia Aplicada a Pessoas Ltda
• CNAE: Desenvolvimento e licenciamento de programas de computador não-customizáveis ; Seleção e agenciamento de mão-de-obra ; Fornecimento e gestão de recursos humanos para terceiros
• City: São Paulo
• Pesquisadores principais: Frederico de Barros Falcão de Lacerda
• Associated researchers: Caio Alexandre Torres ; Cristiano Roberto dos Santos ; Guilherme Gonçalves de Lima ; Vitor Paz Sales Ximenes Carmo
• Associated scholarship(s): 20/12315-0 - Work Experience Robot: applying natural language processing techniques for development of employees interaction system in order to measure employee satisfaction, BP.TT; 20/12295-9 - Work experience robot: applying natural language processing techniques for development of employees interaction system in order to measure employee satisfaction, BP.PIPE

Abstract

WexBot is an interaction platform between human resources teams and company employees. The product meets a need to know the employee without generating more work for himself. WexBot is, therefore, a tool to aid in team communication, calculating ambiance metrics and indicating points of attention - for human resource analysis - interacting via chat with employees when necessary.As detailed in item 3, the main objective of the project is to develop an integrated system of monitoring the employee's experience through databases that the employee already uses in his work routine. It is hoped to reach this goal using information sources provided by clients, such as corporate communication platforms like Slack, Workplace, or emails, in order to have a continuous flow of information, phrases, that are processed by algorithms of processing of natural language, in order to extract from the same coefficients of non-induced favorability, that is, how favorable the employee is in relation to the work environment. These coefficients are aggregated and presented to the human resources department as a management assistance tool. On the other hand, if there is a reduction in favorability, it may be necessary to contact employees to better understand certain issues. At that point WexBot can send off messages to employees autonomously to collect additional data that can make the HR team more clear.WexBot-linked service is expected to result in a decrease (and even elimination) of the time between the identification of an employee's demand and a specific action on that demand taken by the human resources team. It is expected, therefore, an increase in job satisfaction, measured through eNPS, and improvement in quality of life, reducing turnover, increasing retention of employees (measured by the average time worked by employees in the company).For the market, it is understood that, in the absence of direct competitors, with similar solutions or that deal with the same issue, the true potential market goes from 80 thousand medium and large companies, according to the IBGE, which means that the market can reach to more than R$ 2 billion reais. (AU)