Process
Data, AI and empathy, in that order of evidence, that order of heart.
Every engagement runs through the same 12 steps, refined over 13 years, from national platforms to Ontario classrooms. Click through them below; arrow keys work too.
The 12 steps
Identify challenges
Before pixels, questions: what's hurting, why, and how? I focus on the pain points of users and stakeholders alike, because in public services, both sides of the counter matter.
UX research
Needs analysis and requirement gathering; a hard look at previously collected data and analytics; then detailed requirement documents everyone can rally around.
Collaborate & brainstorm
Structured brainstorming sessions with project leaders, developers and stakeholders, the cross-functional collaboration that Agile teams run on.
Hands-on field research
Observation and contextual inquiry in users' natural environments, firsthand usage data, not assumptions from a meeting room.
Surveys
Targeted questionnaires that turn user satisfaction and requirements into quantifiable feedback, numbers that can back a recommendation.
User journey mapping
Charting the user's full path through the service, first contact to final goal, AS-IS and TO-BE, so improvements target the moments that matter.
Concepts & storyboards
Design concepts grounded in real needs: storyboards, wireframes and low-fidelity prototypes that make ideas cheap to test and easy to challenge.
Feedback & design system
Lo-fi feedback loops with stakeholders and users, alongside a design system, tokens, components, patterns, so consistency scales beyond one project.
Interfaces & interactive prototypes
High-fidelity, responsive interfaces for web, desktop and mobile, with custom artwork, photography and iconography that carry the brand, not fight it.
Prototype usability testing
Interactive prototypes tested with stakeholders and users, observation plus eye-tracking technology when depth is needed, feeding straight back into design.
Accessibility enablement
Adherence to accessibility standards (WCAG 2.1) so the product is usable by people across the full range of abilities, inclusion, verified rather than assumed.
UX benchmarking & heuristics
Measuring usability against industry standards and peers to expose gaps and opportunities, the discipline of never declaring victory without a yardstick. The same rigour drives my design QA reviews: shipped product checked against approved designs and brand guidelines.
Deliverables
20 artifacts your teams can pick up and run with
Deliverables aren't paperwork. They're how the work survives me leaving the room.
Every engagement leaves behind standard, reusable artifacts, organized across four disciplines. (The sticky notes are a habit from my Miro boards, restyled to the Snow UI palette.)
- UX Design, flows, IA, lo-fi & hi-fi screens, specs, handoff 7
- Service Design, journey maps, ideation, user stories 5
- UX Research, research plan, stakeholder analysis, personas 4
- UX Project Management, vision, goals, kick-off, plan 4
Data
I read user behaviour the way analysts read markets
Design opinions are cheap; behavioural evidence isn't. A deep data practice is what turns "I think users struggle here" into "here's the heatmap, the drop-off metric, and the fix."
Behavioural analytics
Tobii eye tracking, heatmaps, gaze plots and attention metrics, quantifying cognitive load and spotting friction users can't articulate.
Product & service metrics
Google Analytics, A/B test results, app-store review mining and post-launch monitoring, the feedback loop that keeps live services improving.
Data visualization
Dashboards and visual analytics built with D3 and AmCharts, making complex data legible to users and decision-makers alike. Certified in Google Data Analytics.
AI, ethically applied
AI accelerates the work. Empathy still steers it.
I use AI daily, to synthesize research faster, explore more design directions, and prototype at speed, while the judgment about what serves people stays human. It's the same principle I teach seniors in Milton about using AI safely.
Faster synthesis
AI-assisted analysis of interviews, reviews and survey data, more evidence processed, more time left for the thinking only humans can do.
Rapid prototyping
AI-powered prototyping (including Firebase AI Studio builds) to put testable experiences in front of stakeholders in days, not weeks.
Ethics first
AI applied transparently and reviewed critically, never a substitute for user research, accessibility standards, or accountability to the public.