Content Value Chain
Services

How Michael works with organisations

Every engagement builds on the previous one. Organizations typically begin by understanding their current Content Value Chain, then redesign the operating model, and finally implement the technical architecture needed to support AI at scale. Executive advisory, speaking, and lightweight setups sit alongside this journey as supporting engagement models.

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1. Understand

Content Value Chain Diagnostic

Understand your content operating system before modernizing it.

The diagnostic begins with a high-level Enterprise Content Value Chain Scan to identify where value flows, where the operating model breaks, and which content domain should be modernized first. It then performs a detailed Content Value Chain Diagnostic of that domain, producing an evidence-based roadmap before further investment in AI, governance, CMS, DAM, workflow, or content experience platforms.

Available engagement models

Self-Install
Run the diagnostic using the Content Value Chain Second Brain in your own AI environment.
Kickstart
Run the diagnostic with guided onboarding and review sessions.
Done-With-You
Combine the analytical power of the Second Brain with facilitated workshops, executive interpretation, prioritization, and roadmap development.

Covers

  • Enterprise Content Value Chain Scan
  • Deep Content Value Chain Diagnostic
  • Failure modes and governance analysis
  • Operating model maturity assessment
  • Executive modernization roadmap
2. Design

Content Operating Model Design

Translate the diagnostic into a target operating model.

Building on the findings of the Content Value Chain Diagnostic, we redesign how content operates across governance, ownership, workflows, lifecycle management, and the relationship between human judgment and AI execution.

Covers

  • Content Factory model design
  • Role and ownership mapping
  • Governance framework and decision domains
  • Human/AI workflow design
  • Service Lifecycle definition
3. Build

AI-Ready Content System Design

Translate the operating model into an AI-ready content architecture.

Design the full technical architecture that makes content governable, reusable, and ready for AI-driven scale — from structural foundations through to AI governance and measurement.

Covers

  • Universal Taxonomy and Atomic Content architecture
  • Pattern Library
  • Digital Backbone and DAM Memory Bank
  • AI Agent Org Chart and Brand LLM governance
  • Decision Domain Map and Variant Ledger
The Second Brain

Every diagnostic is powered by the Content Value Chain Second Brain, a local-first analytical engine that applies the Content Value Chain methodology consistently across your documentation, workshop inputs, governance artefacts, workflow descriptions, and technology landscape.

Executive / Advisory Support

Executive / Advisory Support

Support organizations implementing the recommendations from the Content Value Chain roadmap — strategic guidance for executive teams and transformation leaders across three engagement modes.

Covers

  • Board and C-level advisory on content as infrastructure and AI governance
  • Fractional Content Strategist — embedded strategic leadership for transformation rollouts
  • Shadow Content Strategist — confidential strategic partner for content leaders driving internal change
Speaking and Executive Sessions

Speaking and Executive Sessions

Keynotes, executive briefings, and working sessions on modernizing the content operating system, governance at AI speed, and preparing for generative personalization.

Covers

  • Conference keynotes
  • Executive leadership briefings
  • Half-day working sessions for content and AI teams
  • Custom topics aligned to the framework
Lightweight Content System Setup

Lightweight Content System Setup

For founder-led organizations that need the principles of the Content Value Chain without enterprise-scale governance.

A right-sized version of the operating model and system design work, tailored to smaller teams where a full enterprise diagnostic is not the right scale.

Covers

  • Minimum-viable taxonomy and pattern set
  • Right-sized governance and ownership model
  • Practical AI execution patterns
  • Measurement loop appropriate to team size

Start with a conversation

Discuss a diagnosticSchedule a 30 minute call using CalendlyRequest the ebook