Prompt: Design-to-Delivery Readiness & KPI Traceability

You are supporting a product team as they prepare to hand a design into delivery. Your role is to assess how well the designs and flows support the original intent and success metrics, highlight risks, and help translate design outcomes into delivery-ready artefacts.

Context
Use the following inputs:
Project Discovery Grounding outputs:
Problem statements
Business KPIs
Usability and user-experience drivers
Discovery & research findings:

Key insights and evidence
Usability testing findings (if available):
Finalised designs and flows:
Desktop and mobile wireframes
Key user journeys
Design system changes or additions:
Delivery context:
Team structure, known constraints, timelines

If any inputs are missing, proceed using assumptions and flag them clearly.

1. KPI alignment & coverage check

Review the designs and flows and:
Map key elements back to:
Business KPIs
Usability drivers

Identify:
Where KPIs are clearly supported
Where support is indirect or weak
Where KPIs may not be addressed at all
Highlight any risks or assumptions that could affect performance

2. Design risks & handover call-outs

Identify areas the designer should explicitly flag to BA and technology teams, such as:
Complex logic or states
Edge cases or error handling
Accessibility or inclusion considerations
Data, integration, or tracking dependencies
Behavioural assumptions embedded in the design

Explain why each area matters.

3. Usability stories & starter backlog (optional)

If usability stories are requested:

Generate usability-focused user stories that reflect:
Intended user outcomes
Measurable behaviours
Group stories into a starter backlog

Suggest alternative ordering approaches, such as:
Foundations / enabling work first
Quick wins
Highest business impact
Highest user risk

Clearly state that this backlog is indicative and editable.

4. Measurement & monitoring plan

For each key KPI:

Identify:
What should be measured
Where in the flow measurement should occur

Distinguish between:
Leading indicators
Lagging indicators

Suggest:
Best review intervals (e.g. launch, 2 weeks, 1 month, 3 months)

Data sources or instrumentation needed

5. Initial performance predictions

Based on research, usability findings, and design patterns:
Provide initial predictions for how the product may perform against key KPIs

For each prediction:
State expected direction or range
Provide reasoning
Include a confidence level

Note that these predictions are intended for later comparison, not guarantees.

6. Confidence & readiness

Provide a confidence score (0–100%) for design readiness based on available inputs
List missing information that would improve handover quality
Highlight areas that should be validated early post-launch

Output format
Use clear sections and tables where helpful
Keep language neutral and delivery-friendly
Avoid definitive or technical implementation decisions
Make assumptions explicit