- name
- good-services-service-design
- description
- Audit or improve an end-to-end service with Lou Downe's Good Services principles, journey maps, operational blueprints, and evidence-linked improvement work. Use for service outcomes across digital, human, and offline channels, not pure visual styling or a narrow code defect without a service-design question.
- compatibility
- Core review works from supplied evidence without special tools. Current regulatory, accessibility, or operational claims require appropriate sources and access; artifact creation depends on available tools.
- metadata
- {"version":"2.0.0","author":"generated-skill","category":"service-design","tags":"service-design, journey-mapping, service-blueprint, good-services"}
# End-to-end service design
Define the service by the outcome a person needs, not the provider's org chart or
one screen. Use Good Services as a practitioner framework for finding problems and
improvements, not as a legal standard, automatic certification, or measured proof
that an untested design works.
## Choose the useful scope
Read the supplied brief, research, analytics, frontline accounts, policies, and
operational constraints. Identify the user outcome, start trigger, done condition,
user groups, channels, and pain point. Use existing answers rather than always
repeating an intake questionnaire. State missing assumptions and proceed with the
portion the evidence supports; ask only where an unresolved fact blocks a sound
recommendation.
A quick review needs the most consequential findings and next evidence, not every
artefact. A cross-team redesign may need a definition, journey, blueprint, backlog,
service standard, and validation plan. A workshop request needs a facilitation
plan and unfilled templates, not invented workshop consensus. Adapt the outputs
to the request; do not treat a full seven-part packet as mandatory.
## Follow the user's whole journey
Use the [service definition](references/templates/service-definition-canvas.md),
[service map](references/templates/service-map.md), and
[blueprint](references/templates/service-blueprint.md) when they clarify the task.
Map discovery, eligibility, preparation, decisions, transactions, waiting, support,
completion, changes, cancellation, and aftercare where applicable. Include failed
and alternative routes, not only the happy path.
Show user-visible actions and information separately from staff, systems, policies,
and handoffs. Record evidence at each step, whose experience it represents, and
where coverage is missing. Do not invent user emotions, volumes, abandonment
causes, staff capacity, or cross-team ownership. A stakeholder assumption is not
observed user research; a drop-off metric does not by itself establish why people
left or whether they achieved the outcome elsewhere.
## Review the principles with evidence
Read [the principles](references/15-principles.md) as prompts for findability,
purpose, expectations, completion, familiarity, prior knowledge, organisational
handoffs, effort, consistency, dead ends, inclusion, incentives, change, decisions,
and human assistance. Keep the intended user outcome and actual affected groups
visible rather than averaging away exclusion.
Use [the local scorecard](references/templates/principles-scorecard.md) only when
scoring improves the decision. It distinguishes evidenced failure/partial/sound
performance from **unverified** and **out of scope**. Do not award a number merely
because a template has an empty cell. A narrowly scoped 2 is not proof the whole
service works for everyone, and scores are not an interval scale to sum into a
universal quality percentage.
This package's 0–2 rubric is an internal shorthand. Lou Downe's published Good
Services Scale uses 0–4; don't present the local worksheet as that official scale
or convert between them without the actual definitions. For formal use of the
published scale, consult the author's current material.
## Improve the service, not the score
Prioritise demonstrated user harm, outcome failure, frequency, exclusion, operational
risk, and effort. Separate confirmed causes from hypotheses. Put each proposed fix
against evidence, an owner when known, dependencies, acceptance criteria, and the
observation that would establish improvement. Use the
[backlog](references/templates/improvement-backlog.md) and
[service standard](references/templates/service-standard.md) as needed.
Minimise unnecessary burden, not clicks at any cost. A pause, confirmation, appeal,
or human conversation can protect understanding and agency. Do not hide cancellation,
push people into self-service, or optimise call deflection while making support
harder to obtain. Explain what happens after a refusal or error, including feasible
alternatives and escalation; do not invent eligibility or appeal rights.
Accessibility and inclusion require actual testing with relevant needs and channels.
A visual audit cannot prove equal access. Check current applicable requirements,
privacy, and safeguards; don't relabel a practitioner principle as legal advice.
Evaluate the burden shifted onto staff, carers, partner organisations, or users
who lack documents, connectivity, language fluency, time, or confidence.
## Validate and report
Define a small test or pilot for the riskiest assumptions, with observable user
outcomes, operational measures, and guardrails. Distinguish prototype intentions
from observed results. Describe sampling, channel coverage, time window, and
unresolved limits. Don't claim a workshop, survey, usability test, or production
pilot happened when it was only proposed.
Return the decision-useful map/findings/patch or plan, with evidence and specific
next verification. For a workshop, use the existing
[agenda](references/workshop-agenda.md), adapting roles, duration, and participation
needs to the actual request. No stakeholder agreement or assigned ownership is
implied until it is established.
Sources reviewed 2026-09-13: [author's principles](https://good.services/) and
[author's scale explanation](https://loudowne.com/). Detailed local templates are
this package's adaptations, not a new official standard. Metadata follows the
[Agent Skills specification](https://agentskills.io/specification).
Voir sur GitHub