Support decision‑making in the management of the educational institution contingent based on Business Intelligence

Abstract

There are a number of strategic tasks in the system of higher education, the solution of which by traditional methods is not possible or very difficult. One of these tasks is the management of the contingent of students. The complexity of this process is determined by the requirement that the university fulfill various key indicators while ensuring the quality of education. The aim of the study is to improve the process of students’ contingent management of the educational institution based on data management. Universities accumulate huge number of various information, the analysis of which is able to provide the decision-making based on data but not on intuition. The analysis of large information array is not possible without the usage of modern products and technologies related to Business Intelligence. This paper sets out the task of creating a decision support system (DSS) for contingent management, a range of questions is described, to which this system will quickly give answers and help an analyst or the head of a university in making decisions. As the research methods used, the methodology for creating a DSS with a description of the main results of each stage, as well as methods of statistical data analysis, is used. The DSS introduction to the daily activities of Higher education institution allows getting the rapid response to changes in academic achievement, forecasting contingent retention and potential budget losses, assessing the number of vacancies and qualitative performance. The system allows the rector of the university to monitor the dynamics of the main indicators on a weekly basis and gives an idea of the university from the founder’s point of view. Further research is aimed at developing the information system by adding advisory functions, as well as expanding the range of questions that the system is able to give a quick answer to – evaluating the activities of the teaching staff by key indicators, estimating the costs of implementing one or another area of training, and others.