Modelagem de processos: estudo de caso na coordenação de controle acadêmico do IFPB campus Guarabira

Abstract

The current social scene has charged public organizations better performance in relation to public services provision and transparency of information. Aiming to meet these requirements, this study presents tools, aimed at improving processes, which can be used by public and private institutions. With the main objective of modeling the processes of the Academic Coordination Control of IFPB Campus Guarabira, the research presents a descriptive character and qualitative approach, still being classified as a case study. The data were treated in a qualitative way. After identifying the primary processes, ie processes which have a direct relationship with customers internal and external, were identified critical processes and suggested possible improvements to optimize results for critical processes. The main method used to collect data was the interview held at various times with those responsible for the sector. To register the amount of information generated in the interviews, we used two forms prepared by the author. Data analysis was performed in two stages. At first Matrix FC-P (Key Factors versus processes), suggested by Rotondaro (2005), was used to identify the critical processes. In the matrix were assigned scores and weights, the total result permitted the determination of the processes in descending order of importance. The three highest scores were expedition diploma, issuing statements, historical and newsletters, and performing transfer procedure. The identification of elements FEPSC defined the basic requirements for the creation of process models. The flow charts, generated by modeling, were designed in Bizagi. The result of the analysis of these processes culminated in the identification of improvements common to all, such as the need to use an information system and developing a strategic plan that sets goals for the sector, as well as proposals for improvements to each individual, allowing a reduction in runtime optimization of processes and outcomes.