Statistical Analysis of the External Environment as a Basis for Forming an Enterprise’s Investment Policy

Abstract

The purpose of the article is to substantiate a methodological approach to developing an enterprise investment policy through systematic statistical assessment of external conditions and to demonstrate an applied mechanism for transforming analytical findings into substantiated managerial decisions. The authors’ contribution consists in developing an integrated analytical framework that combines environmental monitoring, construction of a relevant indicator system, time-series assessment, correlation and regression modelling, scenario forecasting, sensitivity analysis, stress testing, multi-criteria ranking of project alternatives, portfolio balancing, and continuous performance control. The proposed approach was applied to data describing Prydniprovska Hospital and its operating conditions during 2020–2025. The empirical assessment identifies demand dynamics and consumer income as the factors with the strongest positive influence on revenue, while inflationary pressure and the cost of capital constrain investment capacity and reduce real profitability. The analysis demonstrates the necessity of coordinating projects aimed at expanding demand and improving service quality with projects focused on operating efficiency, digital transformation, energy efficiency, and cost control. Three alternative development scenarios are used to assess portfolio resilience under different combinations of demand growth, inflation, and financing costs. The proposed portfolio includes digitalization of service processes, renewal of medical equipment and infrastructure, expansion of service lines, and energy-efficient modernization. Its scenario-weighted expected net present value amounts to 5.06 million Ukrainian hryvnias, supporting implementation of the program provided that adaptive risk-management mechanisms and an adequate financial buffer are maintained. The practical significance of the results is determined by the possibility of using the proposed indicator system, project-selection criteria, performance measures, risk-management instruments, scenario procedures, and implementation road map in managerial practice. A phased implementation period of twelve to eighteen months is proposed, covering preparation of the analytical framework, development of models and decision procedures, pilot portfolio testing, scaling, and integration into the budgeting and controlling system.