Implementation of strategic tools in the process of financial security management of industrial enterprises in Ukraine

Abstract

The results reported in this paper proved the need to develop strategic measures of the financial security management of enterprises. Approaches to understanding the essence of "management" and "financial security of an enterprise" concepts were analyzed; the author's vision of the essence of "management of the financial security of an enterprise" concept was generalized. Trends in the development of industrial enterprises were studied in order to identify the main indicators that determine the safety level of enterprises in the industry. Strategic directions in the financial security management of industrial enterprises were investigated. It was established that the construction of a regression model would allow an enterprise management to track the effect of deterministic factors on a change in the level of financial security of the enterprise and adjust the process of making managerial decisions related to the financial security of the enterprise. Given this, it became possible to build a tree of goals, which grouped and divided the strategic measures to manage the financial security of an enterprise. A strategic map was built, which reflected the relationship of all the processes at an enterprise and contributes to improving the level of management of the financial security of the enterprise. An expert study into the search for an optimal approach ensuring the financial security of an enterprise was conducted. It is confirmed that in order to improve the level of financial security management of an enterprise, it is necessary to optimize the trade and technological process in order to obtain maximum profit in the future, which could improve the state of all elements of the financial security management system of an enterprise. Thus, there is reason to assert that it is appropriate to define the strategic directions for managing the financial security of industrial enterprises by using regression and hierarchy models.