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Union Pacific Engineering

To build America's premier railroad by leveraging technology for the safest, most reliable, and environmentally responsible rail network

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To build America's premier railroad by leveraging technology for the safest, most reliable, and environmentally responsible rail network

Strengths

  • INFRASTRUCTURE: Owns 32,000 miles of track across 23 western states
  • EXPERTISE: 160+ years of railroad operations experience and knowledge
  • AUTOMATION: Advanced train automation systems reduce manual operations
  • RELIABILITY: 85% on-time delivery performance across major corridors
  • ANALYTICS: Robust data collection from 8,000+ locomotives and 65k+ cars

Weaknesses

  • LEGACY: Aging infrastructure requiring $2B+ annual maintenance
  • INTEGRATION: Siloed systems lacking unified data architecture
  • SECURITY: Vulnerabilities in expanding digital infrastructure
  • TALENT: Shortage of specialized tech talent in railroad engineering
  • SCALABILITY: Limited ability to quickly scale systems during peak demand

Opportunities

  • DIGITIZATION: Full digital twin of rail network to optimize operations
  • SUSTAINABILITY: Developing fuel-efficient and alternative energy tech
  • AUTOMATION: Expanded autonomous operations reducing human error by 40%
  • PREDICTIVE: Enhanced predictive maintenance reducing downtime by 30%
  • INTEGRATION: Seamless supply chain connectivity with customer systems

Threats

  • COMPETITION: Trucking industry adopting autonomous vehicle technology
  • CYBERSECURITY: Increasing sophisticated attacks on critical infrastructure
  • REGULATION: Evolving compliance requirements for rail tech systems
  • DISRUPTION: Climate events impacting rail infrastructure reliability
  • TALENT: Tech companies attracting engineering talent with higher comp

Key Priorities

  • TRANSFORMATION: Accelerate digital transformation of core operations
  • TALENT: Build specialized tech talent pipeline for railroad innovation
  • INTEGRATION: Develop unified data architecture across all operations
  • AUTOMATION: Expand autonomous capabilities to improve safety and cost
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To build America's premier railroad by leveraging technology for the safest, most reliable, and environmentally responsible rail network

DIGITIZE RAILS

Accelerate digital transformation of core operations

  • ARCHITECTURE: Complete unified data architecture design and roadmap by Q3 with exec approval
  • PLATFORM: Migrate 40% of core operational systems to new cloud platform by Q2 end
  • AUTOMATION: Implement 5 new AI-powered operational automations reducing manual work by 25%
  • VISIBILITY: Deploy real-time monitoring dashboard covering 95% of critical rail operations
TECH TALENT

Build specialized tech talent pipeline for innovation

  • RECRUITMENT: Hire 25 specialized railroad technology engineers from tier-1 tech companies
  • TRAINING: Upskill 150 existing engineers through advanced AI/ML certification programs
  • RETENTION: Improve tech team retention to 90% through enhanced incentive structure
  • CULTURE: Achieve 80%+ positive score on engineering culture survey for innovation metric
DATA FORTRESS

Develop unified data architecture across operations

  • INTEGRATION: Connect 65% of operational data sources to central data lake with standard APIs
  • GOVERNANCE: Implement data governance framework with 100% compliance across 5 key domains
  • QUALITY: Achieve 95% data quality score across top 10 critical operational data streams
  • ANALYTICS: Enable self-service analytics for 500+ business users with 30+ pre-built models
SMART RAILS

Expand autonomous capabilities for safety and efficiency

  • INSPECTION: Deploy AI vision systems on 75 inspection vehicles covering 15,000+ track miles
  • PREDICTIVE: Implement predictive maintenance for 2,500 locomotives reducing breakdowns by 30%
  • OPTIMIZATION: Launch dynamic routing algorithm reducing fuel consumption by 8% network-wide
  • AUTOMATION: Achieve Level 2 autonomous operations capability on 3 key rail corridors
METRICS
  • EFFICIENCY: System efficiency ratio of 56.0% by Q4 2025
  • RELIABILITY: 92% on-time performance across major corridors
  • INNOVATION: 15 new tech-enabled operational improvements generating $75M in value
VALUES
  • Safety - We protect the well-being of each other, our customers, and the communities we serve
  • High Ethical Standards - We uphold the highest standards in all our actions
  • Innovation - We embrace new technologies and creative solutions
  • Environmental Stewardship - We are committed to sustainable practices
  • Customer Focus - We deliver exceptional service and value to our customers
Union Pacific logo
Align the learnings

Union Pacific Engineering Retrospective

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To build America's premier railroad by leveraging technology for the safest, most reliable, and environmentally responsible rail network

What Went Well

  • REVENUE: Achieved 3.2% YoY growth despite challenging economic conditions
  • EFFICIENCY: Operating ratio improved to 58.9%, down 1.2 points from 2023
  • TECHNOLOGY: Successfully deployed PTC system across 100% of required track
  • SAFETY: Reduced reportable incidents by 8% through technology enhancements
  • INNOVATION: Completed autonomous inspection pilot with 94% defect detection

Not So Well

  • DISRUPTION: Weather-related outages increased 12% affecting service levels
  • INTEGRATION: Key systems integration projects delayed by average of 60 days
  • CYBERSECURITY: Experienced three significant security incidents requiring
  • TALENT: Engineering department turnover rate increased to 14.2% from 11.8%
  • COSTS: Cloud infrastructure expenses exceeded budget by 17% or $12.5 million

Learnings

  • RESILIENCE: Need enhanced digital resilience planning for climate events
  • ARCHITECTURE: Current system architecture limits agility and innovation
  • COLLABORATION: Cross-functional teams deliver 30% faster project outcomes
  • PRIORITIZATION: Too many concurrent tech initiatives diluting team focus
  • METRICS: Need improved alignment between tech metrics and business outcomes

Action Items

  • CONSOLIDATE: Reduce tech stack complexity by retiring 15% of legacy systems
  • ACCELERATE: Fast-track cloud migration for core operational applications
  • ALIGN: Establish technology OKRs directly tied to business value metrics
  • UPSKILL: Implement dedicated AI/ML training program for 200+ engineers
  • STANDARDIZE: Create unified data governance framework across all systems
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To build America's premier railroad by leveraging technology for the safest, most reliable, and environmentally responsible rail network

Strengths

  • FOUNDATION: Strong data collection infrastructure across network
  • AUTOMATION: Existing AI implementations in train control systems
  • ANALYTICS: Established data science team with domain expertise
  • INVESTMENT: $500M annual tech budget with growing AI allocation
  • PARTNERS: Strategic partnerships with tech vendors and universities

Weaknesses

  • FRAGMENTATION: AI initiatives scattered across different departments
  • SKILLS: Limited specialized AI engineering talent within organization
  • GOVERNANCE: Underdeveloped AI governance and ethical frameworks
  • LEGACY: Integration challenges between AI systems and legacy tech
  • ADOPTION: Cultural resistance to AI-driven operational changes

Opportunities

  • OPERATIONS: AI-powered optimization could reduce fuel costs by 15%
  • SAFETY: Computer vision systems to detect track/equipment issues
  • LOGISTICS: Predictive routing algorithms to increase network capacity
  • MAINTENANCE: Preventive maintenance AI to reduce breakdowns by 35%
  • CUSTOMER: AI-enhanced service delivery and predictive ETAs

Threats

  • COMPETITION: Tech-forward competitors gaining market advantage
  • REGULATIONS: Evolving AI compliance requirements in transportation
  • SECURITY: AI systems creating new cybersecurity attack vectors
  • PRIVACY: Customer data handling concerns with AI implementations
  • RELIABILITY: AI system failures could cause significant disruptions

Key Priorities

  • UNIFICATION: Create unified AI strategy across all business units
  • TALENT: Accelerate AI engineering capability development
  • GOVERNANCE: Establish robust AI governance and ethics framework
  • OPERATIONS: Prioritize AI projects with highest operational impact