DETERMINATION OF A PROMISING BUSINESS AND MODELING OF THE OPTIMUM STRATEGIC SETS FOR THE ENTERPRISES THROUGH MORPHOLOGICAL ANALYSIS USING THE CAPABILITIES OF ARTIFICIAL INTELLIGENCE

Abstract

Decision-making in current conditions of uncertainty has become a real challenge for most business organizations. Therefore, the permanent analysis of all possible and the selection of the most likely scenarios for the development of the business environment and business of the enterprise based on large data sets about the external and internal environment of the enterprise and the processes, which take place there, becomes necessary for the justification of effective management decisions by managers of entrepreneurial organizations and individual business projects. The analysis of possible scenarios of the development of events, the so-called "What if", creates with the help of artificial intelligence (AI) a simulated environment, where it is possible to test various changes in the conditions (opportunities and threats, advantages and disadvantages) of the business, see their impact and, accordingly, make the best possible strategic and tactical management decisions to ensure the success of the business organization in its business activities. In the article, we propose the architecture of the model of applying the concept of artificial intelligence (AI) and artificial neural networks (ANN) to create a data-driven business organization, in particular, in matters of choosing a promising business and developing a strategy for its development in modern dynamic conditions. To perform this task within the framework of ANN, it is proposed to apply the method of morphological analysis of Fritz Zwicki, the essence of which is to structure and study the general set of connections contained in multidimensional, non-quantitatively defined, problematic complexes. In the context of the development of IT, primarily such as ANN, "Big Data" and "Data mining", this method is becoming more relevant than ever and received a new lease of life, in particular, in matters of choosing promising business areas from the point of view of ensuring future profitability and developing strategies for their development and ensuring competitiveness. The use of computer morphological analysis for structuring such complex issues as the choice of a promising business in the future and the generation of strategic alternatives for this business on the basis of data significantly improves, elevates to a higher level the planning, development of scenarios and strategies for the development of the enterprise. Artificial intelligence and machine learning algorithms can be effectively applied through the application of morphological analysis to analyze the large volumes of data that are embedded in every decision, interaction and process in an enterprise in real time, and thus discover patterns that would be impossible to uncover using traditional methods, and then use this information to make both strategic and tactical management decisions.