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Procter & Gamble Engineering

To transform consumer experiences through innovative technology by building superior product and digital platforms that power P&G's growth to $100B by 2035

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Align the strategy

Procter & Gamble Engineering SWOT Analysis

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To transform consumer experiences through innovative technology by building superior product and digital platforms that power P&G's growth to $100B by 2035

Strengths

  • PLATFORM: Robust enterprise technology platforms scaling across brands
  • TALENT: World-class engineering talent in key consumer technology areas
  • INFRASTRUCTURE: Enterprise-grade cloud infrastructure with 99.9% uptime
  • DATA: Proprietary consumer data assets across 5B consumer touchpoints
  • INVESTMENT: $1.2B annual R&D budget for technology innovation

Weaknesses

  • LEGACY: Technical debt from 20+ year-old systems hampering innovation
  • FRAGMENTATION: Disconnected technology stacks across 65+ global brands
  • AGILITY: Slow release cycles averaging 90+ days for major deployments
  • ANALYTICS: Underutilized data assets with only 22% driving decisions
  • TALENT: Engineering skill gaps in key emerging technology areas

Opportunities

  • IOT: Connected home products projected to grow 23% annually through 2030
  • PERSONALIZATION: AI-driven personal care market growing at 18% CAGR
  • PLATFORMS: Direct-to-consumer digital platform expansion potential
  • ECOSYSTEMS: Strategic technology partnerships with retail platforms
  • SUSTAINABILITY: Green tech innovations driving 15% premium price points

Threats

  • COMPETITION: DTC startups with 40% lower technology overhead costs
  • DISRUPTION: Retail partners developing competing technology platforms
  • SECURITY: Increasing cybersecurity threats to consumer data platforms
  • REGULATION: Emerging global privacy laws impacting data capabilities
  • TECHNOLOGY: Rapid pace of innovation requiring faster adoption cycles

Key Priorities

  • MODERNIZATION: Accelerate legacy system replacement across divisions
  • UNIFICATION: Create unified consumer data platform across all brands
  • ACCELERATION: Implement agile engineering practices to reduce cycle time
  • INNOVATION: Expand IoT and AI capabilities in core product categories
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Align the plan

Procter & Gamble Engineering OKR Plan

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To transform consumer experiences through innovative technology by building superior product and digital platforms that power P&G's growth to $100B by 2035

MODERNIZE CORE

Transform legacy systems into scalable digital platforms

  • MIGRATION: Complete cloud migration for remaining 30% of applications with zero downtime
  • TECHNICAL_DEBT: Reduce legacy system maintenance costs from 42% to 30% of engineering budget
  • ARCHITECTURE: Implement microservices architecture for 5 critical consumer-facing platforms
  • AUTOMATION: Achieve 50% reduction in manual deployment steps through CI/CD pipeline enhancements
UNIFY DATA

Create seamless consumer data experiences across brands

  • PLATFORM: Launch unified consumer data platform connecting 65+ brands by end of Q3
  • INTEGRATION: Connect 100% of digital consumer touchpoints to centralized data lake
  • INSIGHTS: Increase data-driven decision making from 22% to 45% across all business units
  • GOVERNANCE: Implement global data governance framework compliant with all regional regulations
ACCELERATE INNOVATION

Reduce time to market for technology-enabled products

  • AGILE: Reduce average deployment cycle time from 90+ days to 30 days across all teams
  • ENABLEMENT: Implement self-service developer platform used by 85% of engineering organization
  • EXPERIMENTATION: Increase A/B testing capability to support 500+ concurrent experiments
  • TALENT: Complete agile transformation training for 100% of engineering organization
AI-POWER GROWTH

Drive consumer value through AI-enabled experiences

  • PERSONALIZATION: Deploy AI recommendation engines across top 10 brand websites and apps
  • EXCELLENCE: Establish AI Center of Excellence with representation from all business units
  • CAPABILITY: Train 2,000 engineers on applied AI through internal certification program
  • ETHICS: Implement comprehensive AI ethics framework with 100% compliance verification
METRICS
  • DIGITAL ENGAGEMENT: 500M monthly active users across all digital platforms
  • ENGINEERING VELOCITY: 30-day average release cycle time (down from 90+)
  • PLATFORM STABILITY: 99.99% uptime for consumer-facing digital services
VALUES
  • Innovation Through Technology
  • Consumer-Centric Engineering
  • Operational Excellence
  • Sustainability by Design
  • Data-Driven Decision Making
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Align the learnings

Procter & Gamble Engineering Retrospective

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To transform consumer experiences through innovative technology by building superior product and digital platforms that power P&G's growth to $100B by 2035

What Went Well

  • CLOUD: Successful migration of 70% of applications to cloud infrastructure
  • DIGITAL: E-commerce platform handled 40% YoY growth without performance issues
  • AUTOMATION: Engineering automation reduced deployment time by 35% last quarter
  • INNOVATION: New digital consumer platform launched on time and within budget
  • SECURITY: Zero major security incidents despite 200% increase in threat volume

Not So Well

  • INTEGRATION: API platform upgrade caused 4 days of service disruptions
  • TALENT: Engineering attrition reached 18%, above industry average of 13%
  • VELOCITY: Software release cycles still 2.5x longer than industry benchmarks
  • TECHNICAL_DEBT: Legacy system maintenance consuming 42% of engineering budget
  • ANALYTICS: Data platform instability affected business intelligence reporting

Learnings

  • TESTING: Need for more comprehensive integration testing across platforms
  • ARCHITECTURE: Microservices approach proves effective for scaling platforms
  • WORKLOAD: Engineering teams significantly overallocated across initiatives
  • PRIORITIZATION: Technology roadmaps need stronger business alignment process
  • CULTURE: Remote-first engineering culture requires stronger communication

Action Items

  • IMPLEMENT: Unified release management system across all technology teams
  • ESTABLISH: Engineering career development program to address attrition
  • ACCELERATE: Technical debt reduction program with dedicated funding
  • OPTIMIZE: Engineering resource allocation process to prevent overcommitment
  • ENHANCE: Cross-functional collaboration between product and engineering
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Drive AI transformation

Procter & Gamble Engineering AI Strategy SWOT Analysis

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To transform consumer experiences through innovative technology by building superior product and digital platforms that power P&G's growth to $100B by 2035

Strengths

  • FOUNDATION: Strong AI/ML infrastructure supporting 200+ internal models
  • EXPERTISE: 300+ AI/ML engineers across global technology centers
  • PATENTS: 75+ AI-related patents filed in consumer product applications
  • DATA: Massive proprietary datasets ideal for training custom AI models
  • ADOPTION: AI algorithms deployed in 40% of digital consumer touchpoints

Weaknesses

  • FRAGMENTATION: Disconnected AI initiatives across product categories
  • GOVERNANCE: Inconsistent AI ethics and governance frameworks
  • SCALABILITY: Limited production-scale AI deployments (<15% of potential)
  • TALENT: Competition for top AI talent with 28% engineering vacancy rate
  • INTEGRATION: Poor AI integration with legacy product development cycles

Opportunities

  • PERSONALIZATION: AI-driven personalized product recommendations
  • FORECASTING: Supply chain optimization through predictive analytics
  • CUSTOMER: AI chatbots and virtual assistants for consumer engagement
  • INNOVATION: Generative AI for accelerated product development cycles
  • AUTOMATION: Manufacturing efficiency through intelligent automation

Threats

  • COMPETITION: Tech giants investing 3x more in consumer AI applications
  • TALENT: Engineering talent shortage in specialized AI domains
  • REGULATION: Emerging AI regulation impacting product development
  • PRIVACY: Consumer concerns about AI-driven data collection
  • QUALITY: AI model drift affecting product recommendation accuracy

Key Priorities

  • UNIFICATION: Create centralized AI Center of Excellence for all brands
  • ACCELERATION: Deploy AI-driven product personalization at scale
  • TALENT: Establish AI upskilling program for 2,000+ engineers
  • GOVERNANCE: Implement enterprise-wide AI ethics framework