MySTOCKS: Multi-Modal Yield eSTimation System of in-prOmotion Commercial Key-ProductS

In recent years, Out-of-Stock (OOS) occurrences have posed a persistent challenge for both retailers and manufacturers. In the context of grocery retail, an OOS event represents a situation where customers are unable to locate a specific product when attempting to make a purchase. This study analyzes the issue from the manufacturer’s perspective. The proposed system, named the “Multi-modal yield eSTimation System of in-prOmotion Commercial Key-ProductS” (MySTOCKS) platform, is a sophisticated multi-modal yield estimation system designed to optimize inventory forecasting for the agrifood and large-scale retail sectors, particularly during promotional periods. MySTOCKS addresses the complexities of inventory management in settings where Out-of-Stock (OOS) and Surplus-of-Stock (SOS) situations frequently arise, offering predictive insights into final stock levels across defined forecasting intervals to support sustainable resource management. Unlike traditional approaches, MySTOCKS leverages an advanced deep learning framework that incorporates transformer models with self-attention mechanisms and domain adaptation capabilities, enabling accurate temporal and spatial modeling tailored to the dynamic requirements of the agrifood supply chain. The system includes two distinct forecasting modules: TR1, designed for standard stock-level estimation, and TR2, which focuses on elevated demand periods during promotions. Additionally, MySTOCKS integrates Elastic Weight Consolidation (EWC) to mitigate the effects of catastrophic forgetting, thus enhancing predictive accuracy amidst changing data patterns. Preliminary results indicate high system performance, with test accuracy, sensitivity, and specificity rates approximating 93.8%. This paper provides an in-depth examination of the MySTOCKS platform’s modular structure, data-processing workflow, and its broader implications for sustainable and economically efficient inventory management within agrifood and large-scale retail environments.