AgriRisk and Supply Continuity Methodology in Scenario Planning of Agricultural Holdings

Анотація

The article is devoted to the study of the AgriRisk and Supply Continuity methodology in the context of scenario planning of the activities of agricultural holdings. The purpose of the study is to determine the features of the application of an integrated approach to modeling the financial results of agricultural enterprises, taking into account the complex impact of risks and interrelated factors. In the course of the scientific study, general scientific methods of cognition were used, in particular, analysis, synthesis, generalization, comparison and a systematic approach. The results of the study show that a generalization of modern approaches to modeling the forecasted financial indicators of enterprises has been made, among which deterministic, stochastic, stress-test, behavioral and integrated approaches are distinguished. Their key characteristics and limitations are studied, in particular, orientation on individual factors, focus on extreme events or dependence on management decisions. It is shown that in conditions of growing uncertainty, combined author’s methods that are able to take into account the multifactorial impact of risks on the results of enterprises are of particular relevance. The justification for the use of the AgriRisk and Supply Continuity Methodology as a tool for comprehensive forecasting of the financial results of agricultural enterprises is made. Its focus on assessing profitability is studied, taking into account the interrelationship of numerous factors, which allows for determining the direct impact of risks on economic efficiency. It is shown that the structure of the method includes three interconnected blocks: financial and accounting, agro-economic and logistics and export, each of which performs a separate function in the formation of the final result. Their interaction is studied and it is established that the integration of these blocks provides a holistic view of the impact of risks, increases the accuracy of forecasting and contributes to the adoption of informed management decisions. The practical significance of the study lies in the possibility of using the proposed method to increase the stability and efficiency of agricultural enterprises in conditions of uncertainty.

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