The Commitment Intelligence Method™ is a framework. But every capital decision, technology commitment, and strategic investment has its own risk topology, its own stakeholders, its own timeline. Advisory work is where the method meets your reality.
"I don't validate your investment for you. I build the analytical architecture that lets you validate it yourself — and defend that position under pressure."
Not a discovery process. Not an intake questionnaire. A direct conversation about the specific commitment at hand — what's being evaluated, what's at stake, and what the decision looks like if it goes wrong.
From that conversation, I build a bespoke engagement. The Commitment Intelligence Method™ applies three analytical lenses — Signal Integrity, Execution, and Commitment Risk — but which lenses are applied, in what depth, and against which data depends entirely on the nature of the decision, the stage of the evaluation, and the position of the decision-maker.
What you receive at the end of an engagement is not a report. It's a defensible position — a documented analytical foundation that lets you commit with confidence or walk away with clarity. Either outcome is a win.
The format follows the decision, not the other way around. Most engagements begin as a sprint and evolve into retained advisory as the scope becomes clear.
A focused, time-bounded engagement structured around a single decision — typically a technology investment, AI commitment, or market entry. The Commitment Intelligence Method™ applied in full, across all three lenses, producing a complete analytical position.
For leaders managing a portfolio of decisions — technology roadmaps, AI investment strategies, or recurring board governance cycles. Retained access to analytical framing as each decision point approaches.
An intensive working session for leadership teams preparing to make a collective technology or AI investment decision. Builds shared analytical language, surfaces hidden risk assumptions, and produces a documented team position before the board presentation.
A keynote designed for investor conferences, technology summits, and board away-days. The central argument: most technology and AI investment failures are not technology failures — they are commitment failures. The signal was there. The analytical framework to read it was not.
Delivered from a 25-year operating record across Cisco, Check Point, and Akamai — not from research abstracts or advisory theory.
A practitioner-built session on what decision intelligence looks like in environments where the stakes are real and the margin for error is narrow. Covers the key failure patterns behind most AI investment losses and the three-lens analytical architecture — Signal Integrity, Execution, and Commitment Risk — that prevents them.
An engagement only works if the right conditions are in place. Here is what the working relationship requires — and what it produces.
Decision Intelligence advisory is not sector-agnostic. It is built for a specific type of decision: technology or AI commitments where the consequence of a wrong answer is significant and the signal to read it correctly exists but requires a trained analytical lens to see.
You have a term sheet, a pitch deck, and a team you believe in. What you need is the analytical framework to determine whether the technology commitment at the core of the deal is sound — and whether the organisation can execute it.
You are the decision-maker on a technology build or platform investment that will define the next two to five years. The board wants a position. Your team has a recommendation. What's missing is the analytical architecture that makes both defensible.
The management team is proposing a significant AI or technology investment. Your role is oversight — which means you need an independent analytical position. Not to block the decision, but to ensure it's been made correctly.
The early technology and AI decisions are the ones that are hardest to reverse. You are about to commit to a technical direction, a platform, or a market approach that will constrain every subsequent decision. The cost of getting this wrong scales with time.
Advisory work is most valuable before the commitment is made. Once capital is deployed and execution has started, the questions become harder and the options become fewer. The right time is now.