Case Studies
Dial M
for results.

Twenty years of product and technology leadership spanning operating model design, organisational change, outcome-driven AI strategy, AI implementation, and net-new products built from zero to meaningful scale.

Organisations and individuals are kept confidential throughout.

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Selected Engagements

What this looks like in practice.

Every engagement is different, but the through-line is the same: clear thinking, practical execution, and outcomes that stick. The three cases below represent the range of work — a turnaround, a zero-to-one launch, and an AI rollout inside a scaled business.

Product Operations

Building a product operating model inside a large enterprise

A large public limited company had a product management function with no organisational structure, unclear accountability, and no shared way of working. Developed a target operating model for the product function, then established a maturity index based on the Gartner maturity framework to baseline current performance and set quarterly improvement targets. Over 18 months the organisation improved its maturity score from 0.7 to 3.1 against an eventual target of 3.8 — driving measurable gains in cross-team collaboration, customer knowledge, discovery and design process, feature prioritisation, a newly established design system, and consistent external communications.

0.7→3.1
Maturity score over 18 months
18 months
Transformation timeframe
3.8
Target maturity score
Product Strategy

Launching a net-new product into a new market segment

A US B2B SaaS business had built a strong foothold in its initial market but needed to grow beyond it. Led the product function to build a net-new product targeting a new market segment and buyer persona — working cross-functionally with customer success, engineering, UX, and sales from day one. With a small team and limited resources, grounded the entire build in customer insight, running a structured early customer programme with ten design partners to validate the concept before scaling. The result was a pilot product that found real traction fast, generating $10m ARR by year two and proving the business could successfully expand its addressable market.

$10m
ARR achieved in year two
10
Design partners in the pilot
0→1
Net-new product, new market
AI Strategy

Using generative AI to drive onboarding, adoption and retention

A US B2B SaaS data catalogue business had a recognised problem: if the product was not correctly curated at onboarding, customers were slower to see value, less likely to adopt fully, and at greater risk of churn. Led the product function to design and ship a net-new generative AI feature that automatically curated business metadata — removing the manual setup burden and accelerating the path to value. Delivered in 2023, when generative AI at enterprise scale was genuinely uncharted territory, which meant navigating complex decisions around public APIs, private APIs, and self-hosting to find an approach that worked at global scale. The feature reduced time to value from weeks to days, improved usage and adoption, and generated positive signals from prospects — suggesting it was also contributing to new logo conversion.

Weeks→Days
Time to value improvement
2023
Shipped ahead of the market
Adoption, retention and new logos
Things I've Shipped

Selected products and features.

A selection of products, features, and capabilities delivered across roles — from net-new launches to significant platform additions inside scaled businesses.

Demographic Surveillance System

A net-new product built and launched for health research across Sub-Saharan Africa and South East Asia. Designed for a highly regulated environment, delivering population-level surveillance capability where data infrastructure was limited. Led product, engineering, design, and user research end-to-end.

FinOps Billing Platform

Evolved a mature billing solution for ITFM and FinOps, protecting $30m ARR. Led engineering and UX to improve the platform while working with software architecture to re-imagine the product around evolving FinOps requirements — keeping an established product competitive without rebuilding from scratch.

Shared Service Cost Transparency

A net-new product built within an established product family, targeting a new market segment and buyer persona. Taken from zero to $10m ARR in year two through a structured design partner programme and tight cross-functional execution across product, engineering, UX, and sales.

Slack Integration

Built Slack, Microsoft Teams, and Tableau integrations for a B2B data catalogue product. Led product, UX, and engineering to reduce friction between everyday tools and the catalogue — making data accessible where teams already worked rather than requiring behaviour change.

Generative AI Feature

Shipped a net-new generative AI feature in 2023 to automatically curate business metadata at onboarding. Navigated complex decisions around public APIs, private APIs, and self-hosting to deliver at global enterprise scale — reducing time to value from weeks to days and improving adoption and retention.

AI-Native Insights Platform

Re-imagined a basic dashboard product into a highly configurable, AI-native insights platform. Led product, UX, data science, and AI engineering — grounded in customer insight — to give customers a more interactive, more powerful way to surface and act on the data that mattered to them.

A career built on doing, not just advising.

If you'd like to see the full story — the roles, the recommendations, and the detail behind the work on this page — I'd love to connect on LinkedIn.

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