Abstract
In the dynamic business environment, the development of forecasting skills in future managers has become an increasingly pressing issue that requires serious research and analysis. This relevance arises from the need for enterprises to adapt to constant changes in the business landscape and global economic challenges. The primary aim of this study was to examine the factors influencing the effectiveness of creating forecasting strategies for prospective corporate leaders. The research employed a complex of various scientific methods. These included analytical, synthetic, comparative, abstraction, generalisation, systematisation, and theoretical modelling methods. Empirical data was obtained through testing, including verbal and projective methods. Questionnaires and trainings were also conducted. The “cross-sectional study” approach was used to organise the obtained information. Mathematical methods were applied to process the statistical data. The results of this study highlight the importance of systematic assessment and evaluation of potential leaders for the successful forecasting of future managers. This process involves identifying individuals with strong leadership qualities and assessing their strengths and weaknesses. A key step is also the careful planning and tailored preparation of prospective leaders. The research emphasises that developing leadership skills, communication abilities, and strategic thinking are essential components for future managers to successfully fulfil their roles. Additionally, the findings indicate that the active use of modern tools and technologies, such as data analytics and artificial intelligence, can significantly enhance the processes of forecasting and staff development. These technologies enable the collection and analysis of large volumes of data, contributing to more accurate identification of potential leaders and personalised development plans. In conclusion, the research findings provide educational institutions with the opportunity to more effectively prepare future leaders, ensuring their competitiveness
Keywords
advanced tools; business environment; management levels; strategic planning; communication
References
[1] Beckmann, J., & Czudaj, R.L. (2020). Professional forecasters’ expectations, consistency, and international spillovers. Journal of Forecasting, 39(7), 1001-1024. doi: 10.1002/for.2675.
[2] Bharthvajan, R., Fabiyola Kavitha, S., & Hussain, J. (2018). A study on effectiveness of recruitment & selection process: Hinduja Global Solutions Ltd. International Journal of Pure and Applied Mathematics, 119(12), 2027-2039.
[3] Bloom, N., Kawakubo, T., Meng, C., Mizen, P., Riley, R., Senga, T., & van Reenen, J. (2022). Do well managed firms make better forecasts? Retrieved from https://cep.lse.ac.uk/pubs/download/dp1821.pdf.
[4] Boylan, J.E., & Syntetos, A.A. (2021). Intermittent demand forecasting: Context, methods and applications. Retrieved from https://www.wiley.com/en-us/Intermittent+Demand+Forecasting%3A+ Context%2C+Methods+and+Applications-p-9781119976080.
[5] Declaration of Helsinki. (2013). Retrieved from https://www.wma.net/what-we-do/medical-ethics/ declaration-of-helsinki/.
[6] Dudchak, H. (2020). Promising concepts of updating the professional training of future managers of the educational sector. Pedagogy of Creative Personality Formation in Higher and Secondary Schools, 73(2), 14-18. doi: 10.32840/1992-5786.2020.73-2.2.
[7] Future of professional’s report. (2023). Retrieved from https://www.thomsonreuters.com/content/dam/ ewp-m/documents/thomsonreuters/en/pdf/reports/future-of-professionals-august-2023.pdf.
[8] Hyndman, R.J., & Athanasopoulos, G. (2021). Forecasting: Principles and practice. Melbourne: OTexts.
[9] Kalyan, N.B. (2020). Emerging and management issues and challenges. Brussel: EPFRA.
[10] Kraus, S., Durst, S., Ferreira, J., Veiga, P., Kailer, N., & Weinmann, A. (2022). Digital transformation in business and management research: An overview of the current status quo. International Journal of Information Management, 63, article number 102466. doi: 10.1016/j.ijinfomgt.2021.102466.
[11] Lutsenko, E. (2020). Readiness of future managers for facilitation in their professional activity: Pedagogical conditions of its formation. Pedagogy of Creative Personality Formation in Higher and Secondary Schools, 2(72), 86-90. doi: 10.32840/1992-5786.2020.72-2.17.
[12] Murphy, K.R. (2020). The past, present, and future of performance management. In Performance management transformation: Lessons learned and next steps (pp. 318-342). Oxford: Oxford University Press. doi: 10.1093/ oso/9780190942878.003.0016.
[13] Nikolopoulos, K.I., & Thomakos, D.D. (2019). Forecasting with the theta method: Theory and applications. London: John Wiley & Sons. doi: 10.1002/9781119320784.
[14] Nunes, V.B., & de Souza, L.L. (2018). Ethical formation in professional, scientific and technological education. Educação & Realidade, 43(2), 711-726. doi: 10.1590/2175-623667554.
[15] Ogolo, J. (2019). Planning as a management function in business organisations. Retrieved from http://surl. li/ofvex.
[16] Petropoulos, F., et al. (2022). Forecasting: Theory and practice. International Journal of Forecasting, 38(3), 705-871. doi: 10.1016/j.ijforecast.2021.11.001.
[17] Poleshchuk, L. (2020). Pedagogical conditions of formation professional-significant qualities education manager. Youth and Market, 6-7, 157-162. doi: 10.24919/2308-4634.2020.225799.
[18] Poleshchuk, L. (2021). Formation of professionally significant qualities of future educational managers: Competence aspect. Innovative Pedagogy, 31(1), 144-148. doi: 10.32843/2663-6085/2021/31-1.30.
[19] Shevchuk, М. (2023). Pedagogical conditions for formation of strategic thinking of future managers in the field of education. Proceedings. Series “Psychological and Pedagogical Sciences”, 3, 86-92. doi: 10.31654/26634902-2022-PP-3-86-92.
[20] Varmus, M., Kubina, M., & Adámik, R. (2021). From management to sport management. In Strategic sport management (pp. 3-34). Cham: Springer. doi: 10.1007/978-3-030-66733-7_2.
[21] Virna, Zh., & Shkarlatiuk, K.I. (2011). Professional forecast: Methodology and practice. Psychology of Professional Activity, 43(1), 122-138.
[22] Zhang, L., Shen, S., Guo, Y., & Fang, Y. (2021). Forecasting future demand of nursing staff for the oldest-old in China by 2025 based on Markov model. International Journal of Health Policy and Management, 11(8), 15331541. doi: 10.34172/IJHPM.2021.63.
