Cloud-native logistics dashboard improving SLA prediction
Built a real-time platform for operations teams with better forecasting and performance tracking, enabling proactive decision-making.
Client
Logistics & Supply Chain Company
Industry
Transportation & Logistics
Duration
4 months
Impact
40% improvement in SLA prediction accuracy
The Challenge
The operations team relied on disparate systems and manual spreadsheets to track shipments and predict delivery times. This led to poor SLA adherence, reactive firefighting, and lack of visibility into performance trends. Existing tools couldn't handle real-time data processing at scale.
Our Solution
Architected a cloud-native platform on AWS that ingests data from 15+ sources in real-time.
Built predictive models using historical delivery data, weather patterns, traffic data, and carrier performance to forecast SLA risks.
Created an intuitive operations dashboard with customizable views for different team roles (dispatchers, account managers, executives).
Implemented automated alerting for at-risk shipments with recommended actions.
Designed the system for horizontal scalability to handle peak volumes without performance degradation.
Results & Impact
SLA prediction accuracy improved from 60% to 84%
On-time delivery rate increased by 23%
Operations team response time to issues reduced by 65%
Customer complaints about late deliveries dropped by 45%
System processes 500K+ shipment events per day with sub-second latency
Technology Stack
"This platform gave us visibility we never had before. We're now proactive instead of reactive, and our customers notice the difference."
Michael Rodriguez
Director of Operations