Abstract:
Small and medium-sized enterprises (SMEs), especially in the food and beverage
industry, experience great operational inefficiencies due to manual data management, low
inventory tracking, and a shortage of business analytics, resulting in poor product quality,
availability, and customer satisfaction. This research aims to integrate all business
processes into a single, integrated web-based ERP system. Doing so allows for ease of
business analysis and sales forecasting, primarily through artificial intelligence (AI), and
to allow for effective and optimal inventory control. An AI powered, web-based ERP
system was selected as the best course of action, due to its complete automation,
comprehensive integration, and ability to leverage in-depth data analysis and predictions
using AI. The ERP capabilities provide a central location for sales, purchasing, expenses,
production, and inventory, sales analysis, and demand forecasting which utilizes AI,
among other features. Operational automation and inventory control with activity
monitoring and alerting to track live stock levels in real-time and alerts used to
preemptively mitigate stock-outs. Testing for the implementation of the system was
successfully verified with the client as part of their User Acceptance Testing (UAT). The
UAT revealed successful functionality of all features that directly addressed the client's
requirements for an integrated system with analysis, forecasting, and inventory
management. The benefits identified included the implementation of an operational and
management system that supported the business in a single integrated platform,
automating a process, ensuring data accuracy, using data to drive informed decision-
making, and, in turn, assisting in improving the competitiveness of SMEs.
