A visually structured consulting simulation focused on transforming enterprise operations through AI integration. This public project showcases how strategy consultants approach operating model redesign—with emphasis on stakeholder alignment, process analysis, automation opportunities, and value realization.
It was designed to reflect a real-world consulting engagement from kickoff to strategic recommendation, including mock data analysis, stakeholder planning, KPIs, and implementation playbooks.
📖 Case Study Narrative - 2-minute transformation story with key insights and interview talking points
This GitHub simulates a real consulting engagement that redesigns an enterprise operating model using AI. Think Bain meets automation — with measurable ROI and structured delivery.
- Strategic Alignment: Map stakeholder priorities and align AI efforts with business goals
- Process Optimization: Identify pain points and streamline workflows using AI capabilities
- Governance & Risk: Simulate frameworks for AI oversight, data ethics, and compliance
- Value Realization: Define KPIs and financial impact to measure AI-enabled transformation success
| Folder | Description |
|---|---|
| 00_Overview/ | Executive summary, project charter, and transformation methodology |
| 01_Stakeholder_Alignment/ | Stakeholder mapping, communication strategy, and RACI matrix |
| 02_Current_State/ | As-is process mapping, performance baseline, and pain point analysis |
| 03_Opportunity_Analysis/ | AI value targeting, automation use case framing, and prioritization |
| 04_Data_Analysis/ | Mock data exploration, attrition analysis, and visual storytelling |
| 05_Design_Solutions/ | Solution sketches, journey maps, automation flows, and redesign frameworks |
| 06_Implementation/ | Phased roadmap, execution tracker, and implementation visuals |
| 07_Strategic_Recommendations/ | AI maturity model, CoE strategy, and executive briefing deck |
| 08_Impact_Measurement/ | KPI baseline, dashboard mockups, and before/after value metrics |
| 09_AI_Tools/ | Governance frameworks, prompt templates, and ethical guidelines |
| 10_Business_Case/ | Financial model, ROI assumptions, and scenario sensitivity |
| 11_Project_Decision_Log/ | Trade-offs, rationale, and strategic decision audit trail |
This project includes over a dozen strategic visuals and executive-ready deliverables:
- 📖 Case Study Narrative - Complete transformation story and interview guide
- 📄 Executive Brief - 2-minute read for C-suite stakeholders
- 📊 Strategic Recommendations Deck - Executive presentation
- 🧠 Decision Log Analysis - Strategic trade-offs and lessons learned
- Stakeholder Power-Interest Grid and Communication Map
- AI Opportunity Prioritization Matrix with Impact vs. Effort Analysis
- Current-State Workflow Swimlanes and Process Maps
- Strategic AI Roadmap with 4-Phase Implementation Timeline
- Before/After KPI Comparison Dashboards
- HR Attrition Prediction Analysis - Jupyter notebook with correlation heatmaps and predictive modeling
- ROI Business Case - 3-scenario financial modeling with sensitivity analysis
- AI Maturity Assessment - 5-level organizational readiness framework
- RACI Matrix and Implementation Timeline
- AI Governance Framework - Comprehensive ethics and risk management toolkit
- Change Management Strategy - Structured adoption and training approach
Each artifact supports structured storytelling and is embedded directly in the corresponding folder.
- $2.5M+ annual savings through process optimization and intelligent automation
- 30% reduction in process cycle times across priority workflows
- 85% accuracy in AI-powered employee attrition prediction
- 18-month payback period on transformation investment
- 95% stakeholder satisfaction with structured methodology and transparency
- AI Maturity Advancement from Level 2 (Emerging) to Level 4 (Integrated)
- Center of Excellence established with governance frameworks and reusable assets
- Decision Velocity improved by 50% through streamlined stakeholder architecture
- Organizational Capability built for sustainable AI adoption beyond pilot projects
This project is designed for:
- Consulting Professionals – Portfolio piece demonstrating end-to-end engagement leadership
- Strategy & Transformation Roles – Case study reference showcasing structured methodology
- Digital/AI Transformation – Complete framework for stakeholder alignment and value realization
- Interview Preparation – Ready-made stories demonstrating analytical and strategic capabilities
- Capability Assessment – Evaluate strategic thinking, analytical rigor, and execution planning
- Methodology Review – Understand candidate's approach to complex organizational change
- Communication Skills – Assess ability to create executive-ready deliverables and compelling narratives
- Self-Contained Evaluation – Complete project simulation requiring no additional context
- Students & Career Switchers – Understand how AI fits into broader business transformation
- Consulting Training – Learn structured approach to stakeholder engagement and change management
- Best Practice Reference – Extract reusable templates and frameworks for real projects
- Industry Benchmarking – Compare approaches against proven transformation methodologies
❌ Not: Generic PowerPoint decks or surface-level case studies
✅ Instead: Complete consulting engagement simulation with working analysis and real data
❌ Not: Technology-focused AI implementation
✅ Instead: Business transformation with AI as strategic value accelerator
❌ Not: Academic exercise or theoretical framework
✅ Instead: Practical, executable methodology with measurable business outcomes
✅ Stakeholder Management - Complex organizational dynamics with structured influence mapping
✅ Analytical Rigor - Data-driven recommendations with comprehensive modeling and validation
✅ Strategic Thinking - Balance of short-term wins and long-term capability building
✅ Change Leadership - Systematic approach to adoption, training, and cultural transformation
✅ Business Partnership - Quantified ROI and measurable business impact throughout
This transformation demonstrates several key insights about successful AI-enabled change:
- Stakeholder Focus over Consensus Building - Centralized engagement around 3 executives vs. broad committee approach
- Evidence-Based Prioritization - Data-driven use case selection vs. stakeholder preference or technology capabilities
- Phased Implementation - MVP approach with continuous validation vs. comprehensive big-bang transformation
- Capability Building - Internal skill development and reusable frameworks vs. consultant-dependent solutions
- Clear Stakeholder Architecture - Know who decides, influences, and implements
- Data-Driven Decision Making - Eliminate politics and bias through quantified analysis
- Quick Wins Balanced with Long-Term Vision - Build momentum while creating sustainable capability
- Systematic Change Management - Structure adoption through training, governance, and feedback loops
For detailed retrospective analysis: Lessons Learned Summary
If you'd like to collaborate, learn more, or provide feedback:
📧 Ivana Gibson
🌐 LinkedIn Profile
📁 View the Full Project
This project is licensed under the MIT License — see the LICENSE file for details.
🧠 Strategic transformation simulated. Consulting excellence demonstrated.
Built for portfolio, interview storytelling, and professional development