Many transformations start with a solution.

I start with the system

My guiding principles

Evidence over assumptions

Conclusions are grounded in what is actually observed, heard, or documented, not in what the organisation believes.

Root causes, not symptoms

Treating symptoms without addressing root causes produces short-term fixes and recurring failures.

The whole system, not isolated parts

An operating model is a system. Changes in one part affect others. Diagnosis addresses the whole, even when the engagement is focused.

Practitioners as experts

The people executing the work understand it better than anyone. Their knowledge is essential to accurate diagnosis and practical design.

AI and operating model foundations

AI doesn’t fix a broken operating model, but it can power a strong one.
Operating model work and an AI investment are not sequential options. They can, and should, be one programme.

When the foundations aren’t in place

AI investment lands on broken infrastructure. Fragmented data, unclear accountability, misaligned incentives, and poor process design don’t disappear when you add AI on top. They accelerate. Decisions get made faster on bad information. Processes that were slow become chaotic and wrong. People don’t know what to expect and respond with fear or skepticism.

When the foundations are sound

Organisations that address operating model foundations with a human-centered, AI-enabled, continuously adaptive approach will get compounding returns from their AI investment. Engaged people, clear accountability, well-designed processes, and aligned incentives create the conditions in which AI delivers genuine value through faster decisions, better information, and execution that scales without breaking.

What an engagement looks like

It is always structured around what an organisation actually needs. My work typically includes three phases, though clients can engage at any stage depending what they need. All engagements start with a conversation to discuss your situation and agree what makes sense.

Phase 1: Diagnosis

A structured investigation into how the operating model is actually performing and where the gaps are.

Findings are evidence-based: the three to five patterns with the greatest impact on execution.

For organisations investing in AI, the diagnostic also surfaces the operating model conditions that will determine whether that investment delivers.

Phase 2: Design

Based on diagnostic findings, I work with the client team to design the execution infrastructure the organisation actually needs. This covers decision rights, governance structures, planning rhythms, coordination mechanisms, and information flows.

The output is built for the organisation’s specific complexity, not a best-practice template.

Phase 3: Transformation

After the design work, clients choose how to proceed.

Options include fractional transformation leadership, transformation advisory supporting an internal lead, or a design handoff with on-call access as needed.

Optionally, organisations can add Operating Model Literacy to their engagement to develop internal operating model capability for long-term monitoring and adaptability.

Outcomes when the operating model is solid

Execution that matches strategic intent

What the organisation says it will do and what it actually does become the same thing. Strategy stops being aspirational and becomes operational.

Growth that doesn’t break the business

Scaling is managed deliberately. The organisation can grow without complexity multiplying faster than the capability to manage it.

Decisions made at the right level

Authority is clear and matched by accountability. The right people are deciding the right things, with the information they need to do so.

AI investment that lands on solid ground

Technology and AI investment delivers because the operating model is designed to absorb and amplify it. The returns are real and sustainable.

Functions that work across boundaries

Cross-functional coordination becomes a capability, not a constant negotiation. Handoffs are designed, not improvised.

Operating model stewardship as a capability

The organisation understands its operating model, can diagnose it when it drifts, and has the internal capability to evolve it deliberately.

Ready to talk about what this could look like for your organisation?

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