METHODS AND MODELS OF BUSINESS ANALYSIS IN THE IT INDUSTRY
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The article describes the theoretical and methodological approaches to conducting business analysis of IT projects. The state of development of the IT industry in the world and in Ukraine is analyzed. The technology and business of selling it have become much more complicated. As a result of this complexity, the work of integration and security issues has increased, making IT more and more complex. But with the challenges come opportunities. Looking ahead to 2021, firms that managed to survive the COVID-19 pandemic will invest in training qualifications, expanding their market to reach new customers and verticals, working with potential competitors and embracing new technologies.
It is noted that the IT industry is the driver of the Ukrainian economy. Business analysis is considered as an important component of project management in the field of IT. Methodical principles of conducting business analysis are described with an emphasis on the analysis of project requirements. The methodologies of business modeling and business processes (Business Model Canvas, IDEF, UML) are highlighted and their use in the process of business analysis is illustrated on the example of an IT project. The article proposes to determine the success of an IT project depending on the completeness of the stages of business analysis by fuzzy logic. Thus, for fuzzy inference, the paper presents a base of production logic rules, based on which the result of the possible success of the project is obtained. Given the high level of input linguistic variables, the success of the project will be 0.796, ie be at a high (high) level. However, given the values for Business Model Canvas — 0.75 and UML — 0.25, the possible success of the project will be only 0.604, ie be at the medium level, which confirms the importance of business analysis, including the stage of modeling and creating UML-chart. The prospect of research on this topic is the further implementation of IT projects using best practices of business analysis, which can significantly increase the likelihood of successful product launch on the information technology market, as well as improving the model of fuzzy inference depending on the business analysis.
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