Engineering an evidence-based intelligence layer
Role: Strategic design lead (systems, governance, & data strategy)
Goal: Transitioning the organisation from data invisibility to evidence-based decision-making
It’s difficult to make informed product decisions when the data you need simply does not exist. I saw a clear gap in the organisational process where no behavioural data was being systematically collected, leaving regional teams to rely on anecdotal intuition to justify product direction. By architecting a unified behavioural event framework, I began transitioning the organisation toward a culture where we can actually measure our impact. This systemic intelligence layer is critical as we move towards integrated complex AI capabilities - without robust data capture, we are essentially flying blind into the next generation of experience.
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The impact
- Evidence-based AI foundations For the pilot teams, we can now see exactly where users are struggling with AI workflows, allowing us to pivot design patterns based on behavioural friction.
- Operational velocity The standardised approach has lowered the barrier to entry for the first pods to start measuring meaningful outcomes, creating a blueprint for the rest of the organisation.
- Foundational shift We have established a unified view of behaviour across our initial markets, proving that consistent data capture is possible even in a fast-paced release culture.
Data as an afterthought
In a culture focused heavily on delivery, measurement is easily sidelined. We were facing a consistent friction point where data requirements were pushed down the line to prioritise immediate releases. Often when an insight was needed, the implementation was six months too late because the measurement wasn’t built in at the start. I identified that this gap was becoming a strategic liability; understanding how humans interact with non-linear systems is fundamentally different from tracking traditional clicks, and anecdotal evidence was no longer enough to justify our direction.
Establishing a systems-first culture
I had to push hard against the prevailing release culture to shift organisational thinking toward a systems-first measurement approach. It wasn’t just a technical challenge; it was a cultural shift to prove that measuring the right things early is an operational insurance policy, not a tax on velocity. By architecting the framework that empowered teams to build with precision, I moved us toward a governed, scalable process that treats data as a first-class citizen in all products.
Very nice. I’m expecting more teams to adopt this model next year!
— S. Judson, Design Director
A shared insight infrastructure
I built a shared system that pulls clear insights directly from our products, replacing messy manual tracking with a single, standard process. By turning existing data into consistent dashboards, we finally have a real view of how people navigate our tools, ensuring our decisions are based on actual behavior rather than just guesses.
What did I do on this project?
- Orchestrated data governance Led global workshops to align engineering and product groups on a singular vision for data, identifying the north star metrics that drive both tactical UI refinements and high-level strategic pivots.
- Institutionalised measurement culture Pushed to move the organisation away from ‘we think’ to evidence-based decision-making by embedding behavioural tracking into the core product design process.
- Workflow optimisation Developed a standardised template approach and automated visualisation system, significantly reducing the time required for teams to document journey events.
- Strategic enablement Regular roll-on sessions with the product teams, ensuring the framework is adopted correctly and evolving the system based on real-world challenges.