Effective supply chain management and stock level balancing represent critical existential hurdles for micro, small, and medium-sized enterprises (SMEs). Overstocking ties down substantial working capital in stagnant physical assets and increases vulnerability to product deterioration, while stockouts directly cause immediate revenue leakage, damage customer acquisition metrics, and erode institutional trust. This comprehensive document details the software architecture, engineering patterns, and deployment configurations of an enterprise-grade, cloud-native web application tailored to resolve these challenges: the Intelligent Inventory Optimisation System (IIOS).

Moving beyond traditional static database setups and client-side prototypes, the proposed solution integrates an advanced multi-tier web development architecture centred around a React.js presentation layer, a resilient Node.js REST API layer, and an active predictive analytics engine driven by structured relational persistence models.

By embedding time-series statistical models directly into production web pipelines, the framework converts inventory control from a purely defensive, historical tracking routine into a predictive, automated orchestration workflow. This system empowers small business entities to optimise resource configurations, maximise transactional efficiency, and secure scalable data security across all operational units.

Keywords

Inventory Management; Predictive Analytics; Demand Forecasting; Supply Chain Optimization; Time Series Analysis; Web Application Architecture.