Technology commercial strategy

I have worked across the whole technology-to-customer journey rather than from inside one discipline looking out. That breadth means I can see how the pieces connect, and where the commercial return is being lost between them.

Usually it is not the technology. It is the proposition, the focus, the pricing or the way the business sells.

AI raises a commercial question before a technical one: what problem does it solve, who pays for that, and how is it packaged and priced so a customer can buy it with confidence?

I have taken an AI capability from internal build to sellable product: leading product and development for a small team on a conversational interface that replaced static reporting, validating it early with customers, several of whom became the first paying deals, and helping win multiple new multi-million-pound opportunities.

Internally, AI and automation are worth doing where they remove real cost, real delay or real error, and worth resisting where they add complexity for its own sake.

The useful work is choosing carefully: which processes, what evidence of benefit, what governance and how data stays secure.

SaaS growth depends on repeatability: acquisition that is not purely heroic, onboarding that delivers value early, retention that holds and expansion that compounds.

I have launched a SaaS proposition into an established enterprise customer base, creating significant new revenue streams by combining product with a focused go-to-market and sales strategy.

Commercialisation is the work between a capability and a customer: proposition, positioning, pricing, packaging, proof and the sales approach that turns interest into paying deals.

This is where my career has repeatedly sat, from launching new digital products to leading the commercial growth strategy of an enterprise software business through to its sale.