Making Management Decisions of The Prediction System in Objects

Abstract

This scientific work deeply studies the importance, principles and practical application of the predicting system in the process of making management decisions. In order to increase the efficiency of management in objects (enterprises, organizations, structural units), decision-making mechanisms based on predicting models are analyzed. The possibilities of developing strategic and operational plans for a certain period using the predicting system and forming optimal management decisions under conditions of uncertainty are considered. The study analyzes decision-making models based on deterministic and stochastic methods, predicting approaches using artificial intelligence tools. The integration of data analysis, machine learning algorithms and statistical predicting methods into management systems is also considered, and their impact on efficiency is illustrated through practical examples. The scientific work demonstrates how to use predicting results in making management decisions, and the role of modern technologies in improving the quality and speed of decisions, using the example of real sector objects. At the same time, the methodological foundations of the development and implementation of information systems supporting decision-making are also considered. This study may be useful for professionals and researchers working in the fields of control systems, economic modeling, information technology, and decision theory.