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Catalyst Canvas: Getting Started
Start using Catalyst Canvas with a controlled example.
Catalyst Canvas · Getting Started
Problem framing, stakeholders, personas, journeys, evidence, assumptions, research, concepts, prototypes, tests, learning, review, and handoffs.
Purpose
This guide provides a safe first run of Catalyst Canvas. It explains the product role, the main feature surface, the synthetic demonstration dataset, how to recognize a valid result, and when human or expert review is required.
Capability overview
- Project Workspace
- Challenge Frame
- Stakeholder Map
- Personas
- Journey Map
- Point of View
- How Might We
- Evidence Ledger
- Assumption Ledger
- Research Plan
- Idea Generation
- Concept Selection
- Prototype Plan
- Test Plan
- Learning Log
- Review Workflow
- Comparison
- Export and Handoffs
Prerequisites
- A modern supported browser or runtime
- The current installed product and service version
- A new demonstration workspace
- No confidential, personal, credential, or production information
- A named reviewer for consequential output
Sample data
This article uses a fictional Resilient Community Retrofit Program. The files contain one demonstration row for every documented feature, so each capability can be tested without private or production data.
Download CSV feature examples · Download JSON workspace example
Preview
| # | Feature | Sample action | Expected result | Classification |
|---|---|---|---|---|
| 1 | Project Workspace | create CANVAS-RETROFIT-001 with owner and status | a persistent project | synthetic-demo |
| 2 | Challenge Frame | describe energy, comfort, users, desired change, and boundaries | a concise challenge statement | synthetic-demo |
| 3 | Stakeholder Map | map visitors, staff, facilities, funders, and contractors | a stakeholder network | synthetic-demo |
| 4 | Personas | create an evidence-bounded facilities-manager persona | a persona separating evidence from inference | synthetic-demo |
| 5 | Journey Map | map room booking, comfort complaints, and facilities response | a stage-based journey | synthetic-demo |
The downloadable files include all 18 feature rows.
Procedure
- Open the product from its canonical Sustainable Catalyst page or administrative route.
- Confirm the product and backend version before creating data.
- Create a synthetic workspace named CATALYST-CANVAS-RETROFIT-001.
- Download the CSV and JSON examples supplied below.
- Use the feature matrix to complete the first six feature checkpoints.
- Save, close, and reopen the workspace to verify persistence.
- Inspect warnings, sources, units, permissions, and lifecycle state.
- Export or hand off only after completing the verification checklist.
1. Project Workspace
Action: create CANVAS-RETROFIT-001 with owner and status.
Expected result: a persistent project.
2. Challenge Frame
Action: describe energy, comfort, users, desired change, and boundaries.
Expected result: a concise challenge statement.
3. Stakeholder Map
Action: map visitors, staff, facilities, funders, and contractors.
Expected result: a stakeholder network.
4. Personas
Action: create an evidence-bounded facilities-manager persona.
Expected result: a persona separating evidence from inference.
5. Journey Map
Action: map room booking, comfort complaints, and facilities response.
Expected result: a stage-based journey.
6. Point of View
Action: synthesize user, need, and insight.
Expected result: a reviewable POV statement.
Expected output
- a persistent project
- a concise challenge statement
- a stakeholder network
- a persona separating evidence from inference
- a stage-based journey
- a reviewable POV statement
- A saved record that reopens without data loss
- An export or handoff that identifies product, version, artifact, source, and review state
Verification
- Every sample value remains attached to its identifier and classification.
- Warnings remain visible and are not silently treated as approval.
- The saved workspace reopens in a clean session.
- The product and version shown in output match the installed release.
- Another reviewer can understand how the output was produced.
Responsible use
Avoid fabricated personas, extractive research, sensitive-data collection without safeguards, and claims unsupported by evidence.
