The reason your AI pilots die is organisational, not technical.

We design the operating model that connects data teams to business decisions — governance, roles, workflows, and accountability. The connective layer between AI capability and business impact.

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Duration
8–12 weeks
Engagement Type
Strategy + Implementation Organisational design & governance
Typical Client
CDO, COO, CHRO, Head of Data Organisations where data/AI teams exist but aren't generating business value
Output
Operating model blueprint Governance framework, RACI, decision rights, workflow designs, and change plan

You have a technology foundation. Now you need the connection.

Most organisations have invested in data platforms, hired data teams, and launched AI pilots. But the insights these teams produce rarely reach the decisions they're meant to inform. There's a structural gap between the people who build models and the people who make business decisions.

This isn't a skills gap or a tooling gap. It's an operating model gap. Without clear decision rights, defined workflows, and shared accountability, even the best data team produces work that goes unused.

Data team and business in parallel universes

Analysts build dashboards nobody uses. Business leaders make decisions on gut. Both are frustrated.

Governance exists on paper only

Policies and frameworks that were designed but never implemented. No one owns data quality or AI ethics in practice.

No clear ownership of AI outcomes

Shared responsibility means no responsibility. AI use cases need clear accountability to deliver impact.

Centre of Excellence that can't scale

A small, overloaded team doing good work that never becomes organisational capability.

The blueprint for a connected organisation.

Six deliverables that turn structural diagnosis into a working operating model.

01

Operating Model Blueprint

Complete organisational design showing how data, AI, and business teams interact — roles, reporting lines, and interfaces.

02

Decision Rights Framework

RACI matrix for every key data and AI decision: who commissions, who builds, who validates, who acts.

03

Governance Architecture

Practical governance covering data quality, AI ethics, model risk, and information security — designed for adoption, not compliance theatre.

04

Workflow Designs

End-to-end process maps for the key insight-to-decision workflows. From business question to AI-informed action.

05

Capability Plan

Skills and roles assessment with a hiring, training, and upskilling roadmap aligned to the new model.

06

Change Management Plan

Adoption strategy with stakeholder mapping, communication plan, and milestone-based rollout.

Eight weeks from diagnosis to design.

Current state, future state, transition path. Built with your people — not handed to them.

Week 1–2
Map

Current State Mapping

Org structure, decision flows, capability inventory, governance gaps. Understand the system as it exists.

Week 3–5
Design

Operating Model Architecture

Roles, governance, workflows, interfaces. Iterative design with key stakeholders.

Week 6–8
Validate

Stress-Test & Change Plan

Test the model against real scenarios. Build the change plan and transition roadmap.

Week 8+
Embed

Rollout & Coaching

Rollout support, coaching, and refinement. Available as ongoing advisory or full implementation.

For leaders who own the how, not just the what

C

CIO / CTO

Owns the technology foundation and needs the operating model to turn infrastructure investment into business impact.

C

Chief Data Officer

Has the team and the tools, but can't demonstrate business impact at scale.

C

COO

Responsible for how the organisation works, including how AI fits into operational decision-making.

H

Head of Data & Analytics

Needs to evolve from a service desk to a strategic capability embedded in the business.

Built a data team but not seeing results? The model is the problem.

30 minutes. No pitch deck. No obligation.