Approach
How I work
Services usually break where one team hands over to another, or where a rule nobody remembers writing gets in the way. So I spend a lot of time with the people behind the service, not only the people using it. When we help those behind the scenes, they feel more empowered to help those using a service.
What I believe
01
Start with whoever finds it hardest
Someone who's ill, caring for a parent, or reading in their second language. If it works for them it tends to work for everyone else.
02
Don't assume tech or AI is the only answer
Sometimes it is. But I've seen more delays caused by approvals and handovers than by anything AI would fix. I look at the space holistically and only recommend tech and AI if it improves the service and creates space for the humans to focus on the interaction.
03
Bring the whole orchestra in.
Good service design works like conducting an orchestra. I rarely play every part myself. I bring together the people who own each piece of a service, from policy and risk to operations, technology and the front line, and run the conversations until they're playing the same score. Mapping the policies, targets and handovers behind a journey is how everyone gets to see that score at once.
04
Build the capacity to carry on
I want the organisation and project teams I work with to keep doing this after I've moved on to the next problem. I include elements of coaching and leave the team with repeateable toolkits and playbooks while keeping a channel of communication and feedback always open.
How a project usually runs
01
Agree on the goal
With senior people and with frontline staff, including how we'll know it worked.
02
Map the service
Draw the whole thing: the person, the staff, the systems, the data and the rules.
03
Try it for real
Prototype and test changes inside the actual service with the people who use and run it.
04
Hand it over
Measure, give each part an owner, and teach the team the method.
Before AI goes into a service
I want answers to a few questions first.
Is there a simpler fix?
Who checks what the AI produces, and who is responsible for the decision?
When it gets something wrong, how would the person affected find out and get it corrected?
And where does it sit under GDPR and the EU AI Act?
The answers aren't always clean. Asking early still prevents expensive rework later.
What I can help with
Leading
Setting up or growing a service design team
Prioritizing the right journeys
Facilitating decision making
Showcasing a vision of what good looks like
Designing
Research with customers and involved teams
Service blueprints and journey maps
Prototypes tested inside the real service
AI ENABLEMENT
Working out whether AI is worth it here
Designing who checks it and how people appeal
Testing AI ideas with the staff who'd use them
Working on a regulated service?
I’m always glad to compare notes with people in finance, healthcare or the public sector, especially if you’re working out where AI belongs.