The whole case, in under a minute.

Problem

The gap was the next action.

Prevention has no natural trigger, so the real question was where to step in. A 141-source literature review mapped the known risk drivers of coronary artery disease, and no single fact was missing.

What I found

All 18 knew their risks. None had a next action.

I ran 18 semi-structured interviews about daily routines, then coded the transcripts until the same behavior themes kept repeating.

  • The themes: time, motivation, personalization, and awareness of the disease.
  • The new brief: one next action inside a routine people already have.

What it cost

The finding holds for working adults; people already in cardiac care, and clinicians, are who it still has to be tested with.

See the affinity map
The affinity map from the interviews: coded sticky notes in four clusters, time management, motivation, need for personalization, and lack of awareness about CAD
An interview session at Philips: two people talking across a table, a whiteboard of sticky notes behind them
The sample: working adults aged 30 to 60, in manager, designer, and developer roles.

What I decided

I chose a system.

SCAMPER, a checklist of ways to change an idea, opened directions from a single tracker to a full ecosystem. I shortlisted the ones the Philips design system could carry and scored them in a Pugh matrix, each against a baseline, on four design principles, feasibility, and viability.

What it cost

A matrix makes the comparison formal, but we wrote the criteria: it reduces bias, it doesn’t remove judgment.

Proof

The connected system won because it linked learning, routines, tracking, guidance, devices, and WhatsApp in one service.

See the principles and the matrix
  • Minimum intrusion for maximum motivation
  • Involve major influencers for frictionless adoption of healthy habits
  • Continuous guidance for heart‑healthy living
  • Personalization for integration and sustainable habit formation
The Pugh matrix: twelve concepts scored against the four design principles, feasibility and viability, from minus one to one each. Concepts 10 and 12 both total 3; concept 12 is highlighted as the choice
Concepts 10 and 12 tied at 3. We chose 12, the connected system.
Two Ecosystem screens: an overall health score of 83, then health insights for heart, stress, environment, diet, and fitness
Two Ecosystem screens: connected devices such as a smart watch, Alexa, and an air purifier, then connected services such as Samsung Health, Google Fit, and Strava
Directions opened (SCAMPER)
24
Feasible shortlist
12
Chosen in the Pugh matrix
1

What shipped

Learn explains the risk. Routine sets today’s action.

I tested the core loop, connect, learn, act, in moderated prototype sessions: could people understand their risk and find their next action without help? The team concept went on to win an iF Design Award in 2024.

  • Connect: the wearable syncs steps, stress, and heart rate; WhatsApp pulls you back.
  • Learn: a Mayo Clinic video and articles; Health Wiz answers in plain language.
  • Act: Routine turns the risk and the learning into a weekly plan for that person.
My accessibility gap

The intended users included adults over 30 with heart risk, but the accessibility claim came from using the Philips design system rather than testing the experience with people at the edges.

If the target users were not represented in task-based testing, the work could claim conformance properties but not accessibility.

Two Learn screens: a Mayo Clinic video explaining coronary artery disease, and a list of articles on risk factors
Two Routine screens: a tailored daily plan across a week, and the same day split into upcoming and completed activities
A score, not proof: 82.1 on the System Usability Scale from 8 people, give or take 10 to 14 points, on Bangor’s bands. Usable, but proving it works clinically needs a longitudinal study.

Looking back

Next, I set the target before testing.

Next time I’d agree the target and the minimum sample before testing, and watch task success beside the survey. I’d also close the consent gap: people linked their devices, the web app, the AI companion, and WhatsApp themselves. I’d connect them by default and ask for consent per data source.

Two things were outside the brief. Nobody had scoped interviews, so I wrote the objectives, recruited people, and ran them myself. Developers and usability specialists taught me the product, so the interface became one part of a service with hardware and clinical claims.