Scientific Bulletin of the Odesa National Economic University 2023, 10, 72-79

Open Access Article

Business analytics - the foundation for innovative transformations in the management component of business

Hostryk Olexey
D. in Economics, Associate Professor, Department of Economic Cybernetics and Information Technologies, Odesa National Economic University, Odesa, E-mail: AlexeyGostrik@gmail.com, ORCID ID: https://orcid.org/0000-0001-6143-6797

Hanevych Margo
4rd year student of the Faculty of Economics and Business Management, Odesa National Economic University, Odesa, E-mail: famma1603@gmail.com, ORCID ID: https://orcid.org/0009-0003-2229-8549

Cite this article:

Hostryk O., Hanevych M. (2023) Business analytics - the foundation for innovative transformations in the management component of business. Ed.: V.V. Kovalenko (ed.-in-ch.) and others [Biznes-analityka - osnova dlia innovatsiinykh peretvoren upravlinskoi skladovoi biznesu; za red.: V.V. Kovalenko (gol. red.)], Scientific Bulletin of the Odesa National Economic University (ISSN 2313-4569), Odesa National Economics University, Odesa, No. 10 (311), pp. 72-79.

Abstract

Today's dynamic environment requires businesses to be flexible, responsive, and able to adapt to change rapidly. Business intelligence plays a central role in the management system, allowing to optimize management decisions, increase the efficiency of operations and enhance competitiveness. The purpose of the article is to assess the main trends in the development of business intelligence in the context of developing a plan for implementing changes in this area. The article examines the key aspects of the business intelligence system, identifies its key areas and tools, and outlines promising areas for its development. The main attention is focused on the impact of business intelligence on the management decision-making processes in a company in today's volatile environment. The role of advanced technologies such as artificial intelligence, machine learning and big data in solving complex business problems is emphasized. The issues of data quality assessment are considered, the low level of which can lead to significant financial losses. The challenges associated with exogenous and endogenous changes that require special attention in terms of business intelligence are analyzed, and the opportunities that open up for managers through the integration of business intelligence with strategic planning and operational activities of companies are identified. Recommendations are provided on the implementation plan for changes in the company's business intelligence, taking into account the key limitations in the organization's resources.

Keywords

data analysis, Big Data, Business Intelligence, key performance indicators (KPIs), artificial intelligence.

JEL classification: M110, M290; DOI: 10.32680/2409-9260-2023-10-311-72-79

UD classification: 303.7:005.3

Лицензия Creative Commons
This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

  1. Schnegg M., Möller K. (2022). Strategies for data analytics projects in business performance forecasting: a field study. Journal of Management Control, 33, С. 241–271.
  2. Yusof E.M., Othman M.S., Yusof A.R., Baharum Z. (2020). A model of determinants for continuous usage of business intelligence in Malaysian manufacturing organizations using theoretical. Indonesian Journal of Electrical Engineering and Computer Science,18, 1439–1445.
  3. Rizqi Anwar M.C., Handayani P.W. (2022). Continuous Use Evaluation of Business Intelligence Implementation in Energy Company. 2022 International Conference on Advanced Computer Science and Information Systems (ICACSIS), 247–252.
  4. Nithya N.S., Kiruthika R. (2020). Impact of Business Intelligence Adoption on performance of banks: a conceptual framework. Journal of Ambient Intelligence and Humanized Computing, 12, 3139–3150.
  5. Heckmann C.S., Maedche A. (2018). IT ambidexterity for business processes: the importance of balance. Business Process Management Journal, 24, 862–881.
  6. Micenko N., Voronko N., Bodnaryuk V., Kabaci B. (2022). Business analytics as strategic resources for the development and implementation of core expertise. Visnik Hmelnickogo nacionalnogo universitetu, 6(2), 129–135 [Іn Ukrainian].
  7. Dmitrishin B., Borovij M. (2020). Business analytics and its role in managing the competitiveness of the enterprise. Centralnoukraïnskiĭ naukoviĭ visnik: Ekonomichni nauki, 5(38), 214–220 [Іn Ukrainian].
  8. Gafiyak A. IT technologies and business analytics (2018). Ekonomika i suspilstvo,15. 933– 937. [Іn Ukrainian].
  9. IBM. Extracting business value from the 4 V’s of big data. Retrieved from https://www. ibm.com/blog/ [Іn Ukrainian].
  10. Omdia. 2022 Trends to Watch: Analytics and Data Management. Retrieved from https:// omdia.tech.informa.com/OM021543/2022-Trends-to-Watch-Analytics-and-Data-Management.
  11. Statista. Big data analytics market revenue worldwide in 2019 and 2025. Retrieved from https://www.statista.com/statistics/947745/worldwide-total-data-market-revenue/.
  12. Gartner. 12 Data and Analytics Trends to Keep on Your Radar. Retrieved from https:// www.gartner.com/en/articles/12-data-and-analytics-trends-to-keep-on-your-radar.
  13. Hostryk О.М. (2022). Use of tools of business analytics in management activities. Ekonomika pidpriyemstva: suchasni problemi teoriyi ta praktiki: materiali odinadcyatoyi mizhnar. naukovo-praktichnoyi konferenciyi, 9-10 veresnya 2022 r. Odesa, ONEU, 225-226 [Іn Ukrainian].
  14. Нostryk О.М. Software tools of business analysis and their application to assess the development of the business environment. Ekonomiko-pravovi aspekti gospodaryuvannya: suchasnij stan, efektivnist ta perspektivi: materiali VIII Mizhnarodnoyi naukovo-praktichnoyi konferenciyi(Odesa, 23-24 veresnya 2022 r). Odesa, 372-373 [Іn Ukrainian].
  15. Shinkarenko V., Hostryk A., Shynkarenko L., Dolinskyi L. А Forecasting the consumer price index using time series models. SHS Web Conf. Volume 107, 2021. EDP Science. 9th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2021). Art. 10002, 6p. Section. Monitoring, Modeling, Forecasting and Preemption of Crisis in Socio-economic Systems. Retrieved from https://doi.org/10.1051/shsconf/202110710002

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