AWS re:Invent 2025 - Drive Supply Chain Innovation Using AWS Cloud and AI Solutions (IND3307)

Driving Supply Chain Innovation with AWS Cloud and AI Solutions

Cisco's Supply Chain Transformation Journey

Cisco's Supply Chain Overview

• Cisco is the world's largest food distribution company, with:
  • 730,000 customers
  • 500,000 SKUs
  • $81 billion in revenue
  • Presence in 90 countries with 340+ distribution centers
• Cisco has grown through mergers and acquisitions, leading to complex legacy systems and processes.

Challenges with Legacy Systems

• Over 1.5 million lines of legacy code
• Integration with various ERP and warehouse systems
• Outdated UI and database technologies (Oracle Forms, PL/SQL)
• Slow and manual deployment process (2-4 hours per site, weeks to roll out to all 110 sites)
• Difficulty innovating and implementing new capabilities like AI/ML

Modernization Strategy and Approach

• Focus on improving user experience for warehouse associates
• Adopt cloud-native technologies and architecture
• Transition from single-tenant to multi-tenant, region-based deployment
• Optimize costs by moving from Oracle Enterprise to RDS Standard Edition
• Embrace a "strangler pattern" approach to gradually replace legacy systems

Benefits of AWS-powered Modernization

• Migrated all 110 sites in 1 year with zero rollbacks
• Achieved 50x better RTO/RPO metrics compared to on-premises
• Reduced deployment time from 2-4 hours to 8 hours for all sites
• Improved security posture with encryption, certificate management, and password rotation
• Realized 50% cost savings compared to on-premises
• Reduced support costs by moving from Oracle Enterprise to RDS Standard Edition

AI and ML Use Cases

1. Root Cause Analysis and Incident Resolution:
   • Uses LLMs and GitHub Copilot to analyze incident data, identify patterns, and provide proactive resolutions
   • Reduced MTTR by 30 minutes and recovery time by 50%
2. Optimized Route Planning (Router IQ):
   • Uses cloud LLMs, hybrid VRP, and Kafka pipelines to automate route planning for warehouse workers
   • Improves efficiency and delivery times for customers
3. AI-driven Inventory Optimization (ARON):
   • Uses SageMaker to build ML models for predicting stock-outs and optimizing inventory levels
   • Aims to improve customer experience and reduce substitutions

Lessons Learned

1. Empower your team and foster strong partnerships with business stakeholders.
2. Automate everything - deployment, infrastructure, DR testing, etc.
3. Proactively manage and optimize costs throughout the transformation.
4. Continuously innovate and leverage AWS services and capabilities.

McDonald's Global Supply Chain Transformation

McDonald's Supply Chain Overview

• McDonald's operates in over 120 countries, serving approximately 1% of the world's population daily.
• Sourcing food locally in each country leads to a highly distributed and complex supply chain.
• Manages over 2.2 million employees and thousands of developers globally.

Key Supply Chain Challenges

• Ensuring food safety and quality standards worldwide
• Meeting global regulatory reporting requirements (FSMA, EUDR)
• Providing end-to-end supply chain visibility and traceability
• Optimizing supply and demand to support marketing campaigns and promotions

MCD Track: McDonald's Supply Chain Visibility Solution

• Guiding principles:
  • Get data directly from source systems, not through third parties
  • Use McDonald's master data as the single source of truth
  • Achieve near real-time data and ensure security and scalability
• Architecture:
  1. Data Producers layer: Normalizes raw data from 10,000+ suppliers, DCs, and restaurants
  2. Refined layer: Merges and tracks data using Amazon Supply Chain Solution
  3. Insights/Curated layer: Enables reporting, user access, and AI/ML processing

AI and ML Use Cases

1. Data Quality and Validation:
   • Uses rule-based models to ensure data quality and alignment across systems
2. Sales and Operations Forecasting:
   • Leverages IoT data, sales data, and AI models built with SageMaker to improve forecasting accuracy
3. Promotional Impact Analysis:
   • Uses LLM-based models to extract and standardize marketing data
   • Combines with sentiment data to predict promotional impact on supply chain

Key Takeaways

• McDonald's is tackling the challenge of supply chain visibility and traceability across a highly distributed, global network.
• The MCD Track solution, built on AWS, provides a comprehensive data platform to enable end-to-end visibility and leverage AI/ML capabilities.
• McDonald's is using a variety of AI and ML techniques, from rule-based models to LLMs and SageMaker pipelines, to address complex supply chain challenges.
• The transformation is a multi-year journey, but McDonald's is making significant progress in driving supply chain innovation and efficiency.