How we work · the Nova Model

One model. Every engagement.

Governance over the top. Four value pillars in between. A data foundation underneath. Two human threads through it all. The Nova Model was built by running it across 50+ operating businesses — not by theorising it.

Governance Umbrella
Productivity &
Operations
Customer &
Commercial
Decision
Intelligence
Product & Service
Innovation
Data Foundation
Thread · Literacy & Adoption Thread · Change & Workforce

Governance Umbrella

Sits over every engagement: policy, decision rights, use-case intake, EU AI Act readiness and audit trail — owned by the executive and the board, not by IT. Without it, AI is liability. With it, AI is leverage.

Data Foundation

Every pillar above is only as strong as the data underneath it. We assess and build this before — or alongside — any AI use case that depends on it. Skip this layer and nothing above it pays back.

Four value pillars

Where the commercial return actually shows up

Every use case in your organisation should map to one of these four. If it doesn't, it shouldn't be funded.

Productivity & Operations

Cost out. Time, cost and quality gains in the day-to-day running of the business. The easiest entry point — and the easiest to measure.

Customer & Commercial

Revenue up. Segmentation, next-best-action, sales augmentation, marketing personalisation. The highest-value pillar, and the one most often overlooked.

Decision Intelligence

The amplifier. Forecasting, scenario modelling, board-grade insight. Better, faster decisions multiply the return on every other pillar.

Product & Service Innovation

New revenue. AI-enabled products and services that didn't exist before — validated commercially before they're built.

The Revenue Lens

Four questions, applied to every use case

If a use case can't answer all four, it doesn't get funded. This single discipline is what separates AI portfolios that pay back from those that don't.

1. Which lever?

Cost out, revenue up, or new revenue?

2. Whose P&L?

Which commercial owner carries the outcome on their numbers?

3. What's the number?

What return are we underwriting, over what horizon?

4. How will we know?

Measurement frame, reporter, cadence.

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