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Optimization of the Decision-Making Process in an IT Company Using the Hierarchy Analysis Method

Student: Kristina Gorbatenko

Supervisor: Victor Victorovich Marshirov

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Business Informatics (Bachelor)

Final Grade: 9

Year of Graduation: 2024

The topic of the final qualification work: "Optimization of the decision-making process in an IT company using the hierarchy analysis method" The relevance of the work lies in the need to optimize the decision-making process using an effective method and is paramount in the continuous growth of the amount of information, as well as in making informed decisions to improve the quality of project management. There are a sufficient number of foreign articles covering the problems in decision-making in the modern world, however, they involve the use of rather resource-intensive artifacts that experienced IT specialists or expert managers are able to apply. Nevertheless, relevant domestic publications that resolve the difficulties of the decision-making process in the real scenario of the IT team of the project are not enough to resolve the issue. The purpose of the work is to optimize the decision–making process in a team using a method supported by software code and graphical visualization to improve the quality of choosing effective strategies in project work. As a solution to the problem posed on the real case of an IT company, the systematization of this process is proposed using the method of analyzing hierarchies with cloud resource support, alternatives are described, artifact assessments, development environments are carried out, the effects of implementation, scaling options are described. The structure of the work includes 4 chapters, which contain sections that allow you to identify the components of the problem. The structure of the work is compiled according to relevance, novelty, as well as goals and objectives. The total volume of work is 73 pages.

Full text (added May 23, 2024)

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