Artificial Intelligence Effects on Inventory Planning of Sensitive Products

Abstract

Pharmaceutical companies invested heavily in research and development, nowadays their funds are mostly allocated in the supply chain management. Inventory forecasting using AI focuses on optimising supply chain processes and mitigating operational risks related to the treatment of sensitive products. The purpose of this research is to comprehensively examine the processes and important factors that influence the implementation of forecasting and optimising inventories. The objectives identify data sources, examine data information flows, review appropriate forecasting models and analyse inventory optimisation-related metrics that could be applied in manufacturing companies. In this paper, the authors review the latest literature in the areas of sales forecasting, inventory optimisation and related forecasting models and metrics, with special emphasis on AI models. The literature review includes publications of scientific research results as well as reports on the development results of the applied inventory optimisation solutions in the industry. The research results will be useful for conducting applied research in a selected company, addressing the complex issue of managing a supply chain, as well as the production and storage of perishable materials and products. Results will be useful in research aimed at improving the forecasting of the inventory of sensitive products and consequentially increasing business efficiency.