Evo
Evo was a product-validation programme, not a conventional product delivery project. I was seconded into the programme as UX Lead while managing a design team, giving me the chance to return to hands-on research and design. The work tested whether a connected geoscience platform could create meaningful value for end users, partners, and the wider Seequent ecosystem.
The work connected platform strategy to the people, workflows, and technical ecosystem it needed to serve.
The proposition was a fundamental shift toward interoperability across Seequent and third-party products.
Validate the platform proposition
Section titled “Validate the platform proposition”Evo aimed to connect geoscience data, compute, and insight across Seequent and third-party products. That meant challenging a powerful assumption: that better interoperability would translate into a better experience and better business outcomes. I shaped the UX research plan and worked with a multidisciplinary team across Christchurch, Auckland, Vancouver, and Toronto to test that assumption with the people the strategy depended on.
The research was deliberately broad enough to validate the platform, but structured enough to produce decisions:
- In-depth interviews with Evo partners and end users to understand current workflows, unmet needs, barriers to interoperability, and what would make an open platform credible.
- Research synthesis and affinity mapping to identify patterns across roles, industries, jobs, pains, and expectations.
- Audience segmentation, personas, and value proposition canvases to test whether the platform created distinct value for customers and partners rather than one generic promise.
- Service blueprinting and ecosystem mapping to understand how data, products, teams, and handoffs could connect across the partner journey.
- Early wireframes and prototype reviews to make the strategy tangible enough to critique, refine, and plan against.
Open-ended interviews surfaced needs and expectations that a feature list could miss.
Understand who the platform had to work for
Section titled “Understand who the platform had to work for”Industry labels alone were too blunt to guide product decisions. The interviews showed that a platform proposition had to account for different jobs, levels of technical confidence, commercial relationships, and expectations around control of data. I helped reframe the audience model around those differences so the team could test value by behaviour and context, not by market label alone.
Customer value propositions connected audience needs to the platform opportunity.
Partner value propositions clarified reciprocal value, beyond a simple list of integrations.
Personas turned the audience model into something product teams could reason about and use.
Turn evidence into a product direction
Section titled “Turn evidence into a product direction”I translated the research into personas, service mapping, and early wireframes. These were validation tools, not final delivery artifacts. They helped the team test whether the ecosystem idea could become a coherent experience, where integrations belonged, what partners needed from the platform, and what a useful beta needed to prove.
The developer portal made the platform proposition concrete: APIs, data, tools, and workflows in one place.
The JupyterLab playground showed how developers could test and work with Evo APIs in practice.
The service blueprint made the platform opportunity visible across the partner journey, not just inside an interface.
What this validated
Section titled “What this validated”- Which customer and partner needs the platform could credibly address.
- Where interoperability, open data, and connected workflows created meaningful value.
- A research-backed direction for product definition and beta planning.
This was foundation and validation work. Later products could reuse the audience and platform context where it applied, then do focused discovery for the workflows and users they introduced. The value was not a finished product; it was better evidence for deciding what the ecosystem should become and where to invest next.