Use of information generated in the subprocesses of the quality management system as a database

Abstract

The Manual of Academic-Administrative Guidelines of the National Technological Institute of Mexico [1] defines the Academy as: a collegiate body that integrates the Head of the Academic Department, professors and professors-researchers who attend the different educational levels and who carry out teaching, research, linkage and academic management activities, these activities according to the same document are fifteen.

The people who make up this instance generate multiple documents in a timely manner, using data that are recorded in isolation and only for the purpose of the document in turn, being that the academies do not have a historical record of all the information produced, additionally a data analysis is not carried out that allows the optimization of their processes.

This paper hypothesizes that the information managed in the Academies can be categorized into variables that allow the generation of databases, using existing guidelines and procedures, to generate new knowledge about the processes that concern them.

The subject of the study was the Academy of Administration Engineering, part of the same educational program, belonging to the Department of Economic and Administrative Sciences of the National Institute of Technology of Mexico-Zacatepec.

This is a qualitative-documentary study, which used as a base document the Opinion of professional residencies, to extract the information, categorize it into variables, treat the data by means of a spreadsheet and using the results in the design of specialties to verify the hypothesis raised, according to the sub-processes and activities marked by the Quality Management System of the National Technological Institute of Mexico-Zacatepec [2].

The results indicate that the information generated in the subprocesses of the Academies' activities can be used in others, concluding that it is possible to define and categorize each data recorded in each of the deliverables, allowing its analysis.