The article analyzes the business processes of forecasting at enterprises of the energy retail sector in the context of the volatility of the wholesale electricity and capacity market (REM). It is proved that traditional forecasting approaches, focused mainly on technical algorithms, are insufficient to ensure the financial stability of companies: errors in applications lead to fines and losses. The theoretical foundations of the process approach to management are considered and six key features of energy marketing activities as an object of forecasting are identified (impossibility of warehousing, volatility of demand, dual market position, etc.). Unlike existing works, the authors propose an original classification of forecasting business processes according to five criteria (time horizon, functional orientation, object, methods, level automation) and a seven-stage structural model of a closed-loop feedback process. Six areas of improvement of predictive activities in the context of digitalization of the industry have been identified, including the introduction of machine learning and the integration of external data. The developed methodological tools can be used to analyze, optimize and improve the accuracy of forecasts in energy marketing organizations.s
business processes, forecasting, energy sales organizations, electric power industry, process approach, classification, structural model, wholesale electricity market, digital transformation
1. Ob utverzhdenii Osnovnyh polozheniy funkcionirovaniya roznichnyh rynkov elektricheskoy energii : postanovlenie Pravitel'stva RF ot 04.05.2012 № 442 (red. ot 29.12.2023) // SPS «Konsul'tantPlyus».
2. O funkcionirovanii optovogo rynka elektricheskoy energii i moschnosti : postanovlenie Pravitel'stva RF ot 27.12.2010 № 1172 (red. ot 29.12.2023) // SPS «Konsul'tantPlyus».
3. Ob utverzhdenii Energeticheskoy strategii Rossiyskoy Federacii na period do 2035 goda : rasporyazhenie Pravitel'stva RF ot 09.06.2020 № 1523-r // Oficial'nyy internet-portal pravovoy informacii.
4. Otchet o funkcionirovanii EES Rossii v 2023 godu / Sistemnyy operator Edinoy energeticheskoy sistemy. – Moskva, 2024. – 156 s. – URL: https://www.so-ups.ru [data obrascheniya: 15.01.2026].
5. GOST R ISO 9000-2015. Sistemy menedzhmenta kachestva. Osnovnye polozheniya i slovar'. – Moskva : Standartinform, 2015. – 54 s.
6. Blinov A. O., Ugryumova N. V. Biznes-process kak osnova processnogo podhoda v upravlenii // Vestnik Saratovskogo gosudarstvennogo social'no-ekonomicheskogo universiteta. – 2014. – № 1 (50). – S. 32–36.
7. Klyuev R. V., Gavrina O. A., Sokolov A. A. Prognozirovanie planovogo potrebleniya elektroenergii dlya ob'edinennoy energosistemy s pomosch'yu mashinnogo obucheniya // Zapiski Gornogo instituta. – 2023. – T. 261. – S. 392–402.
8. Naugol'nova I. A. Processnyy podhod k upravleniyu: evolyuciya, sovremennye vyzovy, innovacii // Kreativnaya ekonomika. – 2023. – T. 17, № 6. – S. 2175–2192.
9. Repin V. V., Eliferov V. G. Processnyy podhod k upravleniyu. Modelirovanie biznes-processov. – Moskva : Mann, Ivanov i Ferber, 2013. – 544 s.
10. Hammer M., Champi D. Reinzhiniring korporacii: manifest revolyucii v biznese / per. s angl. – Sankt-Peterburg : Izd-vo S.-Peterb. un-ta, 1997. – 332 s.
11. Homutov S. O., Stashko V. I., Serebryakov N. A. Povyshenie tochnosti kratkosrochnogo prognozirovaniya elektropotrebleniya // Omskiy nauchnyy vestnik. – 2020. – № 4 (172). – S. 58–64.
12. Shelehov I. Yu. Prognozirovanie potrebleniya elektricheskoy energii promyshlennym predpriyatiem s pomosch'yu metodov mashinnogo obucheniya // Izvestiya Tomskogo politehnicheskogo universiteta. – 2022. – T. 333, № 5. – S. 135–146.
