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International Paper Engineering

To build innovative digital systems that transform renewable resources into sustainable products people depend on globally

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To build innovative digital systems that transform renewable resources into sustainable products people depend on globally

Strengths

  • INFRASTRUCTURE: Robust cloud infrastructure supporting global operations
  • TALENT: Strong engineering team with deep industry expertise
  • AUTOMATION: Advanced manufacturing automation systems in place
  • DATA: Extensive operational data collection across facilities
  • SECURITY: Comprehensive cybersecurity framework protecting assets

Weaknesses

  • INTEGRATION: Legacy systems hindering digital transformation
  • ANALYTICS: Underdeveloped data analytics capabilities
  • AGILITY: Slow technology deployment cycles averaging 9+ months
  • TALENT: Skills gap in emerging technologies like AI/ML
  • COLLABORATION: Siloed technology teams across business units

Opportunities

  • OPTIMIZATION: Process optimization through IoT and edge computing
  • SUSTAINABILITY: Digital tools to measure and improve ESG metrics
  • ANALYTICS: Predictive maintenance to reduce downtime by 30%
  • AUTOMATION: End-to-end supply chain digitalization
  • INNOVATION: Creating digital products from sustainability initiatives

Threats

  • SECURITY: Increasing cybersecurity threats to operational systems
  • COMPETITION: Digital-native competitors disrupting market share
  • TALENT: Difficulty attracting top tech talent to paper industry
  • REGULATION: Evolving compliance requirements for data privacy
  • COST: Rising technology infrastructure and maintenance costs

Key Priorities

  • MODERNIZATION: Accelerate core systems modernization initiative
  • ANALYTICS: Develop advanced analytics capabilities for optimization
  • TALENT: Upskill workforce and recruit specialized digital talent
  • SECURITY: Enhance cybersecurity posture across digital footprint
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To build innovative digital systems that transform renewable resources into sustainable products people depend on globally

MODERNIZE

Transform legacy systems into future-ready platforms

  • ARCHITECTURE: Define and implement enterprise API strategy connecting 75% of critical systems by Q4
  • CLOUD: Migrate remaining 60% of on-premises applications to cloud environment with 99.9% reliability
  • AUTOMATION: Implement CI/CD pipeline reducing deployment time from 14 days to 2 days for core apps
  • TECHNICAL DEBT: Reduce legacy system maintenance costs by 25% through rationalization
ANALYZE

Unlock operational insights through advanced analytics

  • PLATFORM: Deploy enterprise data analytics platform with real-time dashboards for all mills
  • INSIGHTS: Deliver predictive maintenance models for critical equipment reducing downtime by 20%
  • ADOPTION: Achieve 80% adoption rate of data-driven decision making among operations leaders
  • VALUE: Generate $15M in operational savings through analytics-driven process optimization
SECURE

Protect digital assets against evolving threats

  • FRAMEWORK: Implement zero-trust security architecture across 100% of digital infrastructure
  • COMPLIANCE: Achieve 100% compliance with updated cybersecurity policies and standards
  • DETECTION: Reduce mean time to detect security incidents from 96 hours to 4 hours
  • TRAINING: Train 100% of technology team on security-by-design principles with 90% pass rate
ENABLE

Build world-class digital engineering capabilities

  • TALENT: Hire 15 specialists in AI, cloud architecture, and cybersecurity with 90% retention
  • UPSKILLING: Complete digital skills assessment and training for 100% of engineering team
  • AGILE: Implement agile delivery methodology across all technology teams with 85% maturity score
  • INNOVATION: Launch engineering innovation lab generating 5 validated proofs-of-concept
METRICS
  • ADOPTION: Digital transformation adoption rate: 85%
  • EFFICIENCY: Technology-enabled operational cost savings: $25M
  • RELIABILITY: Critical systems uptime: 99.95%
VALUES
  • Safety
  • Ethics
  • Stewardship
  • Inclusion & Respect
  • Strength in Teamwork
  • Commitment to Excellence
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Align the learnings

International Paper Engineering Retrospective

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To build innovative digital systems that transform renewable resources into sustainable products people depend on globally

What Went Well

  • IMPLEMENTATION: Successfully deployed IoT sensors in 3 mills with 98% uptime
  • SECURITY: Zero major security incidents despite 27% increase in attempts
  • COSTS: Achieved 12% reduction in IT operational costs through automation
  • CLOUD: Completed migration of 40% of workloads to cloud ahead of schedule
  • RELIABILITY: Achieved 99.8% uptime for critical manufacturing systems

Not So Well

  • PROJECTS: 35% of digital transformation projects behind schedule
  • INTEGRATION: Legacy system integration challenges delaying modernization
  • TALENT: 18% turnover in engineering team, higher than company average
  • ADOPTION: Only 62% user adoption rate for new digital tools vs 75% target
  • ANALYTICS: Data analytics platform implementation delayed by 3 months

Learnings

  • CHANGE: Need stronger change management for technology deployments
  • AGILE: Traditional waterfall approach limiting delivery speed and value
  • RESOURCES: Need dedicated resources rather than part-time assignments
  • TRAINING: Insufficient training causing low adoption of new technologies
  • MEASURING: Better ROI metrics needed to justify technology investments

Action Items

  • AGILE: Implement agile delivery methodology for all technology projects
  • TALENT: Launch digital skills development program for engineering team
  • GOVERNANCE: Establish technology steering committee with business units
  • ARCHITECTURE: Develop API strategy to address integration challenges
  • ROADMAP: Create clear 3-year technology roadmap with business alignment
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To build innovative digital systems that transform renewable resources into sustainable products people depend on globally

Strengths

  • DATA: Massive operational data sets across manufacturing facilities
  • INFRA: Established cloud infrastructure supporting AI deployment
  • PILOTS: Successful AI pilot programs in quality control
  • LEADERSHIP: Executive commitment to AI transformation
  • PARTNERS: Strategic technology partnerships with AI vendors

Weaknesses

  • EXPERTISE: Limited internal AI expertise and talent bench
  • INTEGRATION: Difficulty integrating AI with legacy systems
  • GOVERNANCE: Underdeveloped AI governance framework
  • DATA: Poor data quality and inconsistent standardization
  • ADOPTION: Cultural resistance to AI-driven decision making

Opportunities

  • OPTIMIZATION: AI-powered process optimization reducing waste 15%
  • QUALITY: Computer vision for defect detection improving yield
  • FORECASTING: Predictive demand forecasting reducing inventory
  • SUSTAINABILITY: AI optimization of energy and resource usage
  • MAINTENANCE: Predictive maintenance reducing downtime by 30%

Threats

  • INVESTMENT: High implementation costs with uncertain ROI
  • COMPETITION: Industry competitors advancing AI capabilities faster
  • COMPLEXITY: Technical complexity of AI integration with OT systems
  • ETHICS: Emerging ethical concerns and regulatory requirements
  • DEPENDENCE: Over-reliance on external AI expertise and vendors

Key Priorities

  • STRATEGY: Develop comprehensive AI strategy and roadmap
  • TALENT: Build internal AI expertise through hiring and upskilling
  • USE-CASES: Prioritize high-impact AI use cases in operations
  • GOVERNANCE: Establish robust AI governance and ethics framework