Examination of the application of decision-making systems in planning the dispensing of sheep in farms

Abstract

The research investigated the possibilities and effectiveness of applying decision support systems (DSS) in the planning of dispensary processes in 24 individual sheep farms operating across six regions of Azerbaijan. Thirteen sheep breeds native to Azerbaijan are bred in these farms. The purpose of the study is to develop a functional DSS model that will ensure monitoring of sheep health status, forecasting of risks, optimization of preventive measures, and rational decision-making at the farm level.

Field research and empirical observations revealed that the dispensary process in most farms is still carried out through traditional methods—paper-based records and subjective observations—which complicates early diagnosis and leads to errors. In farms where DSS was applied, treatment and prevention costs decreased on average by 22.4%, livestock losses by 28.6%, while milk and meat productivity increased by 18.3% and 14.8%, respectively. The system’s ROI (Return on Investment) indicators were 62.3%, 77.3%, and 89.9% in small, medium, and large farms, respectively.

The DSS model proposed within the study includes several key functional blocks: data collection (from sensor and manual sources), an analytical engine (statistical and AI-based analysis), a risk assessment module, and a user interface (mobile application, web panel, reporting mechanisms).

As a scientific novelty, this research presents the complex integration of decision support systems into dispensary processes in sheep farming, which is significant both theoretically and practically.