Advisory and expertise

Four advisory domains where I help organizations turn architecture into a practical control system for change, with decisions made explicit, governance made executable, and business outcomes made measurable.

Enterprise Architecture

I use enterprise architecture as a strategic control system: a way to align business capabilities, data ecosystems, technology landscapes, investment choices, and delivery decisions across complex organizations.

  • Define architecture strategies that connect capability scope, governance, standards, and transformation priorities.
  • Establish EA operating models, including charters, roles, methodology, governance forums, tooling, and ways of working.
  • Rationalize and modernize large application portfolios, including globally distributed landscapes with hundreds of applications.
  • Develop AI-augmented EA practices around agents, capabilities, data products, governance, risk, and compliance.
  • Create and animate architect communities of practice so architecture knowledge becomes shared, reusable, and operational.

Data Strategy and Products

I connect data strategy to implementation by turning governance, priority use cases, platform choices, and data product design into an executable roadmap.

  • Build end-to-end data and AI strategies covering governance, value-based prioritization, technology selection, and scalable deployment.
  • Design data products as governed units of meaning, ownership, quality, access, and reuse.
  • Apply data mesh principles pragmatically, with clear domain ownership, product contracts, and governance mechanisms.
  • Architect data platforms across lakehouse, warehouse, analytics, integration, metadata, and data governance capabilities.
  • Translate vendor and platform choices into operating models, implementation plans, and adoption trajectories.

AI and Agentic AI

I help organizations adopt AI and agentic systems responsibly, with architecture boundaries that make autonomy useful without losing control over data, decisions, tools, and evidence.

  • Define agentic AI reference architectures, including agent roles, orchestration, tool access, memory, data access, and human review boundaries.
  • Build AI assistants for architecture, data quality management, API maturity assessment, and enterprise knowledge activation.
  • Design AI governance frameworks that link business value, regulatory compliance, risk classification, controls, and evidence.
  • Model AI capabilities, AI agents, data dependencies, lifecycle states, and accountability structures in enterprise architecture practice.
  • Turn AI governance from principles into policies, contracts, runtime permissions, and validation evidence.

ERP and Transformation Architecture

I work on ERP and transformation architecture as a control problem: modernizing core systems while preserving integration discipline, business continuity, and a clean operating model.

  • Lead ERP modernization and transformation architecture across regulated and operationally complex environments.
  • Assess enterprise integration landscapes and define target integration strategies, governance models, and transition plans.
  • Clarify the boundary between core platforms, extensions, workflows, data products, and surrounding digital capabilities.
  • Connect transformation roadmaps to design decisions, architecture principles, standards, and delivery governance.
  • Support tooling selection, operating model evolution, and execution planning for large-scale transformation programs.