8%
Operational time improvement
$25M
Previous annual penalties
$14M
Demonstrated cost savings
12M
Month implementation timeline
The challenge
Overcoming costly delivery delays in complex supply chains
A leading multinational CPG company was facing significant financial penalties from delayed deliveries, amounting to $24 million annually. The challenge was to optimize complex logistics operations and maximize on-time deliveries to reduce these penalties.
Key challenges
Complex multi-stage outbound shipment processes and tracking
Significant recurring financial penalties for delays
High volume of daily deliveries across networks
Multiple stages in shipment tracking
The solution
Azure-powered predictive analytics platform
Intelligent modeling
Predictive risk assessment
Bayesian inference modeling
Real-time analytics integration
ERP and TMS system integration
Implementation framework
Azure cloud platform deployment
Comprehensive tracking system
Cross-departmental coordination
Automated decision support
Implementation approach
1
Discovery and planning
Source system identification
Stakeholder requirements gathering
Process analysis and mapping
Infrastructure planning
2
Development
Predictive model creation
Azure cloud integration
System testing and validation
Performance monitoring
3
Deployment
Phased implementation
System integration
North America rollout
Continuous optimization
The impact
Fundamentally transformed delivery performance metrics
Delivery efficiency
8%
Enhanced delivery tracking
Improved information retrieval
Reduced delays
Improved timing accuracy
Financial impact
$14M
Operational cost reduction
Reduced delivery penalties
Operational savings
Enhanced efficiency
Performance monitoring
Operational excellence
100%
Process optimization
Unified tracking system
Streamlined workflows
Cross-department collaboration
Looking ahead
Enhanced analytics
Unlocking advanced predictive capabilities
Expanded deployment
Seamlessly scaling across broader markets
Continuous improvement
Driving further efficiency optimization
