Mcdonald’s logo

Mcdonald’s Engineering

To enable delicious, feel-good moments for everyone through cutting-edge technology that delivers frictionless customer experiences worldwide

|

To enable delicious, feel-good moments for everyone through cutting-edge technology that delivers frictionless customer experiences worldwide

Strengths

  • PLATFORM: Global digital ordering platform serving 40K+ restaurants
  • SCALE: Massive transaction volume enables unique data insights
  • ADOPTION: 36% of sales now through digital channels
  • INFRASTRUCTURE: Robust cloud infrastructure with 99.9% uptime
  • TALENT: Strong engineering leadership in key technology hubs

Weaknesses

  • LEGACY: Technical debt from legacy restaurant systems
  • INTEGRATION: Fragmented systems across global franchises
  • VELOCITY: Slow deployment cycles for new technology features
  • TALENT: Difficulty attracting top-tier engineering talent
  • ARCHITECTURE: Monolithic architecture limiting innovation speed

Opportunities

  • PERSONALIZATION: AI-driven menu and offer personalization
  • AUTOMATION: Kitchen automation to increase throughput by 30%
  • LOYALTY: Enhanced mobile app loyalty features to drive retention
  • DATA: Leverage vast customer data for operational improvements
  • DELIVERY: Integrated delivery tech to improve last-mile efficiency

Threats

  • COMPETITION: Digital-first QSR competitors taking market share
  • TALENT: Tech giants offering higher compensation to engineers
  • PRIVACY: Increasing global regulations on customer data usage
  • SECURITY: Growing sophistication of cyberattacks on POS systems
  • FRANCHISEES: Resistance to technology adoption investments

Key Priorities

  • PLATFORM: Modernize digital platform architecture
  • PERSONALIZATION: Deploy AI-driven personalization at scale
  • AUTOMATION: Accelerate restaurant automation technology
  • TALENT: Establish engineering excellence program for retention
|

To enable delicious, feel-good moments for everyone through cutting-edge technology that delivers frictionless customer experiences worldwide

MODERNIZE

Build future-proof digital restaurant platform

  • ARCHITECTURE: Complete microservices migration for 80% of digital platform by Q3
  • DEPLOYMENT: Reduce deployment cycle time from 14 days to 3 days for core services
  • PERFORMANCE: Achieve 99.98% uptime and <500ms response time across all digital channels
  • INTEGRATION: Standardize API gateway for 100% of restaurant technology systems
PERSONALIZE

Deliver AI-driven customer experiences

  • RECOMMENDATIONS: Launch AI menu recommendation engine with 20% higher conversion in 25K restaurants
  • DATA: Unify customer data platform capturing 90% of transaction and behavior data
  • TESTING: Implement AI-powered A/B testing framework reducing test cycles by 40%
  • LOYALTY: Deploy personalized rewards increasing program engagement by 30%
AUTOMATE

Accelerate restaurant technology innovation

  • KITCHEN: Deploy AI-powered kitchen management system in 1,000 restaurants reducing waste by 15%
  • VOICE: Expand voice AI ordering to 5,000 drive-thrus increasing throughput by 22%
  • SCHEDULING: Implement AI-optimized staff scheduling in 10,000 locations reducing labor costs by 7%
  • QUALITY: Roll out computer vision quality control to 3,000 restaurants improving accuracy by 30%
ELEVATE

Build world-class engineering organization

  • TALENT: Reduce engineering attrition to <15% through comprehensive career development program
  • SKILLS: Train 90% of engineering staff on AI/ML fundamentals and cloud-native development
  • DIVERSITY: Increase engineering diversity by 25% across gender and underrepresented groups
  • COLLABORATION: Implement engineering excellence program with 85% adoption across global teams
METRICS
  • DIGITAL SALES: 45% of total sales through digital channels
  • DEPLOYMENT FREQUENCY: 50+ production deployments per week
  • ENGINEERING SATISFACTION: 85%+ retention of technical talent
VALUES
  • Customer-obsessed innovation
  • Operational excellence
  • Technical craftsmanship
  • Inclusive collaboration
  • Continuous improvement
Mcdonald’s logo
Align the learnings

Mcdonald’s Engineering Retrospective

|

To enable delicious, feel-good moments for everyone through cutting-edge technology that delivers frictionless customer experiences worldwide

What Went Well

  • MOBILE: App downloads increased 18% driving digital sales growth
  • LOYALTY: MyMcDonald's Rewards program showing 22% higher frequency
  • PLATFORM: Global digital platform achieved 99.9% uptime during peak
  • EXPERIENCE: Self-service kiosk usage up 15% improving order accuracy
  • DELIVERY: Integrated delivery partnerships now in 30K+ restaurants

Not So Well

  • INTEGRATION: Technology integration issues delayed deployment by 2Q
  • PERFORMANCE: App performance issues during promotional campaigns
  • ADOPTION: Lower than expected franchisee technology adoption rates
  • SECURITY: Three significant security incidents requiring mitigation
  • TALENT: Engineering attrition rate reached concerning 22% annually

Learnings

  • ARCHITECTURE: Microservices approach proves more efficient for scale
  • TESTING: Enhanced load testing critical before major promotions
  • DEPLOYMENT: Phased global rollouts reduce operational disruptions
  • FRANCHISEE: Early franchisee involvement crucial for tech adoption
  • AGILITY: Faster iteration cycles lead to improved customer feedback

Action Items

  • PLATFORM: Complete API modernization to enable faster innovation
  • TALENT: Launch engineering excellence program to reduce attrition
  • AUTOMATION: Accelerate kitchen automation pilots in 500 locations
  • DATA: Establish unified data platform for cross-channel insights
  • SECURITY: Implement enhanced security protocols across all systems
|

To enable delicious, feel-good moments for everyone through cutting-edge technology that delivers frictionless customer experiences worldwide

Strengths

  • DATA: Massive customer dataset across billions of transactions
  • SCALE: Global infrastructure to deploy AI solutions at scale
  • ADOPTION: Successful initial AI recommendation engine pilots
  • PARTNERSHIPS: Strategic partnerships with leading AI providers
  • LEADERSHIP: Executive commitment to AI-driven transformation

Weaknesses

  • INTEGRATION: Siloed data limiting comprehensive AI insights
  • TALENT: Limited specialized AI/ML engineering expertise
  • GOVERNANCE: Immature AI governance and ethics frameworks
  • INFRASTRUCTURE: Legacy systems not optimized for AI workloads
  • STRATEGY: Fragmented approach to AI implementation

Opportunities

  • FORECASTING: AI-powered demand forecasting reducing waste 15%
  • EXPERIENCE: Voice AI ordering increasing throughput by 25%
  • OPERATIONS: Computer vision for quality control automation
  • PERSONALIZATION: Hyper-personalized menu recommendations
  • EFFICIENCY: AI-optimized restaurant staffing and scheduling

Threats

  • COMPETITION: Quick-service rivals deploying advanced AI faster
  • REGULATION: Evolving AI regulatory landscape across markets
  • PRIVACY: Customer concerns about AI-driven personalization
  • ADOPTION: Franchisee resistance to AI technology investments
  • TALENT: Fierce competition for limited AI engineering talent

Key Priorities

  • DATA: Unify global data platform for comprehensive AI insights
  • TALENT: Build specialized AI engineering center of excellence
  • EXPERIENCE: Prioritize voice AI and personalization capabilities
  • GOVERNANCE: Establish robust AI ethics and governance framework