STATISTICAL JUSTIFICATION OF A MANAGEMENT DECISION ON FIXED ASSET ACQUISITION: A CASE STUDY OF A MINING AND METALLURGICAL ENTERPRISE

The article examines a real production situation involving a managerial decision on the feasibility of acquiring fixed assets at a mining and metallurgical enterprise. Emphasis is placed on the use of statistical analysis in combination with financial modeling. The study substantiates the advisability of switching from leasing equipment to purchasing it, through the construction of a financial model based on statistical methods of cost analysis, cost growth dynamics, and payback period calculation. The object of the study is one of the largest metallurgical enterprises in Ukraine, which has not ceased operations even once during the wartime period. Budgeting of alternative scenarios was carried out, taking into account the consistent load on machine and tractor units. Cumulative costs of leasing versus purchasing were graphically visualized. Conclusions were made regarding the economic efficiency of the investments, and tools of internal cost control within the enterprise management system were recommended. As a result of the conducted research, a practical case was formed for making a managerial decision based on cost budgeting and statistical analysis in the context of a mining and metallurgical enterprise. The study confirmed the feasibility of applying a combined approach—integrating economic modeling and the analysis of dynamic indicators–when making decisions about investing in fixed assets. The calculations demonstrate that, under conditions of stable production volume and equipment utilization, the shift from leasing to ownership allows for significant cost reductions in the long term. This is particularly evident in the case of the bulldozer, where the payback period remains within an acceptable range. In contrast, investment in the excavator requires additional conditions and more in-depth economic evaluation. Thus, the implementation of cost budgeting in conjunction with statistical analysis should become an integral part of the internal control system and strategic management of industrial enterprises aiming to improve resource efficiency and resilience to economic risks.