The introduction of neural network technologies as a factor in improving the effectiveness of management decisions in small businesses

the article is devoted to the feasibility of introducing artificial neural networks into key business processes of EasyNeon. The purpose of the presented study is to evaluate the effectiveness of using neural network technologies to improve the effectiveness of management decisions. The main objectives of the research are the company's business processes for design and sales. The data for several months of the company's operation before and after the introduction of artificial neural networks was analyzed, the data was prepared and structured for further analysis. The methods of Difference-in-Differences, calculation of the wage fund ROI and acceleration coefficient were applied, which allowed us to build a model for assessing the economic and operational performance of the company. Based on the analysis, the dynamics of unit personnel costs, the profitability of the wage fund and the speed of processes when using both traditional methods of work and using artificial intelligence technologies are investigated. The scientific hypothesis about the expediency of using artificial neural networks to optimize business processes and make managerial decisions has been confirmed. The conclusion is made about the importance of using neural networks to optimize the business processes of an enterprise and make management decisions, and its effectiveness in reducing costs, increasing profitability and significantly speeding up key business operations is confirmed.

artificial neural networks, business automation, design visualization, digital manager, cost optimization, efficiency of management decisions