ОПИСАНИЕ ЭТАПОВ ВНЕДРЕНИЯ МОДЕЛИ ПРОГНОЗИРОВАНИЯ БИЗНЕС-ПРОЦЕССОВ ЭНЕРГОПРЕДПРИЯТИЙ

Abstract:
The issue addressed in this study is that for the effective operation of energy sector enterprises in terms of business process management, the forecasting model for key financial and production indicators (electricity generation, revenue, and net profit) was implemented competently and step by step, taking into account all external factors. To this end, it is necessary to analyze and describe all the stages. The scientific novelty lies in the fact that the author’s model for predicting the activities of companies in the energy sector is of particular value, as it incorporates a hybrid approach that includes scenario analysis and machine learning methods, and the stages of testing this approach are proposed using the example of three enterprises: PJSC TGK 1 and PJSC TGK 2. The theoretical review presents an analysis of the authors’ scientific approaches to the essence of forecasting and the changes in business processes under current conditions. The need to use a comprehensive approach to forecasting in order to substantiate and make more effective decisions in conditions of market instability is emphasized. The research employed general scientific and specific methods, namely, analysis, synthesis, deduction, modeling, and generalization of the obtained results. The practical significance lies in the fact that the conclusions can be useful for specialists, analysts, economists, and experts who are engaged in forecasting indicators under conditions of uncertainty and crisis. For energy enterprises, in particular, PJSC “TGK 1” and PJSC “TGK 2”, the stages of implementing the author’s model are effective when industrial companies face difficult to predict fluctuations in demand, disruptions in supply chains, and volatility in raw material prices. The conclusions indicate that the effect of implementing the model is manifested in a reduction of the production cycle, which will directly affect capital turnover and, consequently, the companies’ financial performance.