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Data Analytics

Real-Time Supply Chain Analytics Dashboard

Created a comprehensive analytics platform providing real-time visibility into supply chain operations, reducing inventory costs by 25% and improving delivery times by 40%.

July 2024
Manufacturing Company
5 months
6 Engineers

Overview

Created a comprehensive analytics platform providing real-time visibility into supply chain operations, reducing inventory costs by 25% and improving delivery times by 40%.

Key Results

25%Inventory Reduction
-40%Delivery Time
92%Forecast Accuracy
$1.2M/yearCost Savings

The Challenge

The manufacturing company lacked real-time visibility into their supply chain, relying on manual reports that were often outdated by days. This led to inventory stockouts, overstock situations, delayed shipments, and inability to quickly respond to disruptions. Decision-makers needed immediate access to actionable insights across multiple facilities and suppliers.

Our Solution

We designed and built a real-time analytics dashboard that aggregates data from multiple sources including ERP systems, warehouse management systems, shipping providers, and IoT sensors. The platform features predictive analytics for demand forecasting, automated alerts for anomalies, and customizable KPI tracking.

Implementation

1. Data Pipeline Architecture

Built a scalable data pipeline processing 1M+ events daily from 20+ different sources with real-time streaming and batch processing.

2. Analytics & ML Models

Developed predictive models for demand forecasting, inventory optimization, and delay prediction using historical data.

3. Dashboard Development

Created an intuitive dashboard with customizable views for different roles, from executives to warehouse managers.

4. Integration & Deployment

Seamlessly integrated with existing systems without disrupting operations, with phased rollout across facilities.

Results & Impact

  • Reduced inventory holding costs by $800,000 annually
  • Improved on-time delivery rate from 75% to 96%
  • Decreased stockouts by 85% through predictive replenishment
  • Enabled proactive response to supply chain disruptions
  • Reduced manual reporting time by 90%

Technologies Used

ReactD3.jsPythonApache KafkaPostgreSQLTimescaleDBAWSDocker

Conclusion

This analytics platform provided unprecedented visibility into supply chain operations, enabling data-driven decision making at all levels. The system has become a critical tool for operational excellence and competitive advantage.

Future Enhancements

Future enhancements include supplier performance scoring, carbon footprint tracking, and AI-powered route optimization for logistics.

Have a Similar Project in Mind?

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