Strategic Analysis & Approach
Strategic analysis and strategy development that produced the Phased Internal Build approach
1Strategic Analysis
Key Finding
Three independent analyses converged on a core insight: the organization's decentralized, relationship-centric culture and competitive position require AI capabilities that cannot be purchased — they must be built from proprietary institutional knowledge.
We conducted three independent analyses to map the landscape and build a complete picture of the context, stakeholders, and organizational dynamics. First, we consulted stakeholders to understand their needs. Then, we analyzed the competitive landscape (Five Forces) to identify market imperatives. Finally, we assessed the organization (7S + SWOT) to expose cultural, capability, and structural realities.
Board, C-Suite, Culture & People, Customer requirements
Budget, culture, adoption, language, and structural constraints
Proprietary capabilities, efficiency, defensibility, staffing
Stakeholder CTQ Analysis
Before evaluating strategic approaches, we analyzed stakeholder needs to derive Critical to Quality requirements that any solution must satisfy. Interviews and focus groups with Board members, C-Suite executives, staff representatives, and customer-facing teams revealed eight distinct requirements spanning financial expectations, risk tolerance, adoption preferences, and service quality standards.
Quarterly visible progress demonstrating momentum
Rapid return on investment, not deferred payback
Ability to stop at any point without sunk cost
Limited exposure at any decision point
Quick wins that solve real problems from day one
Self-initiated adoption, not top-down requirements
Improved service quality and compliance
No imposed changes to existing relationships
Four CTQ categories emerged: Cultural, Financial, Competitive, and Operational constraints that traditional AI approaches could not satisfy simultaneously.
View Full Analysis →2Strategy Development
Key Finding
Traditional enterprise AI approaches — vendor platforms and big-bang custom builds — systematically violate the CTQs discovered in strategic analysis, requiring evaluation of a fundamentally different approach.
With 19 CTQs established, we developed three strategic alternatives and evaluated each using Pugh Matrix analysis. The alternatives ranged from vendor platform purchase to custom full-scope deployment to a fundamentally different phased approach designed specifically for organizational constraints.
Purchase commercial AI platform and configure for organizational needs
Build custom AI system from scratch with full-scope deployment
Build proprietary AI internally with progressive deployment
Evaluating Solution Options
With 19 CTQs established across stakeholder, organizational, and competitive dimensions, we developed three distinct strategic alternatives representing fundamentally different approaches to enterprise AI. Each option varies in investment scale, implementation timeline, risk profile, and alignment with organizational constraints.
Vendor Platform
Purchase commercial AI platform (e.g., Microsoft Copilot, Salesforce Einstein) and configure for organizational needs.
Custom Big Bang
Build custom AI system from scratch with full-scope deployment across the organization simultaneously.
Phased Internal Build
Build proprietary AI internally with existing staff, deploy progressively with self-initiated adoption.
Next: Transformation Framework
With strategy selected, the Transformation Framework translates these strategic decisions into concrete implementation through Three Horizons phasing, a detailed roadmap with embedded change management, and Balanced Scorecard measurement.
View Transformation FrameworkThis is a portfolio demonstration project showcasing the complete design and implementation of an enterprise AI system. The technical implementation is actual and deployment-ready. Business context (the $1.3B international organization) provides realistic constraints and requirements. Direct investment figures are based on actual infrastructure costs and industry-standard training program estimates.
© 2025 Daniel Dimick. Licensed under CC BY-NC 4.0 for educational use.