ERP System for Warehouse and Supply Management
Project Goals
- Develop a real-time inventory tracking tool across multiple warehouses.
- Automate stock management and supply forecasting.
- Integrate the ERP system with an online store for seamless order processing.
Our Solution
We began by mapping out all business processes with the client, analyzing how products move across warehouses, how they are distributed, and when restocking is needed. Based on this analysis, we developed the ERP core, enabling real-time tracking of inventory movements. Each new stock arrival or transfer automatically updates inventory levels, eliminating manual errors. Additionally, we implemented a demand forecasting module using historical sales data and seasonal trends. This allows the system to predict inventory needs, preventing both stock shortages and overstocking. For smooth integration with the online store, we established a bidirectional sync: when an order is placed, the product is automatically reserved in the ERP system, any inventory changes in the ERP are instantly reflected in the online store. All processes are managed through an intuitive admin panel, providing staff with a real-time overview of all warehouses and supply statuses.
Technologies Used
- Java (Spring Boot) (backend)
- Angular (admin panel)
- PostgreSQL (primary database)
- Python + scikit-learn (machine learning for demand forecasting)
Results
- 70% reduction in manual operations
- 85% accuracy in stock level predictions
- Minimized losses due to overstocking or stock shortages
Project Team
- 1. Tech Lead (solution architecture)
- 2. Backend Developer (inventory management & integrations)
- 3. Data Scientist (demand forecasting algorithms)
- 4. Frontend Developer (ERP interface)
- 5. Project Manager (communication & timelines)
Implementation Timeline
5 months
Project Uniqueness
Integrating traditional ERP functionalities with machine learning allowed for dynamic inventory optimization, adapting to seasonal demand fluctuations.
Estimated Cost
From $15,000
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