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Development of an Automated Data Management and Analytics Platform for Manufacturing Supply Chain Optimization
  1. case
  2. Development of an Automated Data Management and Analytics Platform for Manufacturing Supply Chain Optimization

Development of an Automated Data Management and Analytics Platform for Manufacturing Supply Chain Optimization

radixweb.com
Manufacturing

Supply Chain Data Fragmentation and Lack of Real-Time Visibility

The manufacturing organization faces challenges in consolidating diverse supply chain data sources, resulting in limited real-time visibility into inventory, logistics, and supplier performance. This impairs quick decision-making and disrupts operational workflows, necessitating an integrated data management solution.

About the Client

A mid-to-large manufacturing company aiming to enhance supply chain visibility, data-driven decision-making, and operational efficiency.

Goals for Supply Chain Data Integration and Insight Generation

  • Develop an automated data collection system consolidating multiple supply chain sources into a unified platform.
  • Implement real-time dashboards providing actionable insights on inventory levels, logistics status, and supplier metrics.
  • Enhance data accuracy and consistency through automated validation and processing.
  • Improve supply chain responsiveness, reducing downtime and operational delays.
  • Achieve scalability to accommodate increasing data volumes and additional data sources over time.

Core Functionalities for Supply Chain Data Platform

  • Automated data ingestion from ERP systems, logistics providers, and supplier databases.
  • Real-time dashboards displaying key supply chain KPIs and alerts.
  • Data validation and cleansing modules to ensure accuracy.
  • Role-based access controls for secure data access.
  • Custom report generation and export capabilities.
  • Scalable architecture to support increasing data flows.

Technology Stack and Architectural Preferences

Cloud-based infrastructure (e.g., AWS, Azure) for scalability and reliability.
Microservices architecture for modular development.
Real-time data processing platforms (e.g., Kafka, Spark).
Data visualization tools integrated with dashboards.
Secure APIs and authentication protocols.

External Systems and Data Source Integrations

  • ERP systems for inventory and order data.
  • Logistics and transportation management systems.
  • Supplier databases and third-party logistics APIs.
  • Analytics and reporting tools.

Non-Functional System Requirements and Performance Metrics

  • System scalability to support a 50% increase in data volume annually.
  • Dashboard update latency less than 2 seconds for real-time data.
  • 99.9% system uptime with automated failover.
  • Data security complying with industry standards and encryption.

Projected Business Benefits and Impact of the Supply Chain Platform

The implementation of this integrated data platform is expected to streamline supply chain operations, reduce decision-making time by 40%, enhance data accuracy, and cut logistical delays by 25%. Ultimately, this will lead to increased operational efficiency, cost reductions, and improved customer satisfaction.

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