From Figma to Power BI: Building a Design System Workflow for Data Visualisation.
Designing for data visualisation is a discipline in itself. Unlike marketing sites or mobile apps, analytics platforms demand precision, consistency, and a deep sensitivity to how users read, interpret, and act on information. Figma provides a workflow that bridges design and implementation, ensuring Power BI dashboards don’t just look polished but actively drive decision-making.
In this post, I’ll walk through an end-to-end Figma workflow tailored for data and analytics teams, drawing on lessons learned from implementing design systems inside enterprise banking and government contexts.
1. Discovery in FigJam: Defining Information Needs
Every strong workflow begins upstream. Instead of rushing to UI, start by mapping user needs:
Stakeholder workshops in FigJam → capture KPIs, metrics, and the "jobs to be done."
Information hierarchy mapping → prioritise the visuals that matter most (e.g., executive scorecards vs. analyst drill-downs).
Data storytelling flow → sketch out user journeys (e.g., “What happens after the CFO sees a red KPI?”).
👉 Example: In one engagement, a banking team mapped 40+ metrics in FigJam, then consolidated them into a north-star KPI hierarchy that informed every visual in the dashboard.
2. Component-Driven Libraries in Figma
Power BI dashboards thrive on consistency. Figma becomes the single source of truth by hosting:
Design tokens → colour palettes (aligned with brand accessibility), typography, grid spacing.
Reusable components → card templates, slicers, filter panels, navigation bars.
Visualisation frames → pre-built bar, line, and donut chart containers that match Power BI defaults but extend them with accessibility and brand polish.
👉 Tip: Use Token Studio in Figma to sync colours and typography directly with Power BI JSON theme files, so design and implementation stay in lock-step.
3. Prototyping the Dashboard Experience
Static mockups don’t capture the fluidity of analytics. Figma prototypes help simulate:
Drill-through flows → clicking a KPI card to reveal detail pages.
Interactions → toggling slicers, changing themes, expanding a table.
Responsive behaviours → desktop vs. mobile views of the same dashboard.
👉 Example: An enterprise HR analytics dashboard was prototyped in Figma to test whether managers could complete tasks (e.g., finding attrition risks) in under 3 clicks. The prototype validated the flow before a single dataset was wired up.
4. Developer Handoff: From Figma to Power BI
Smooth handoff is crucial. With Figma’s Dev Mode:
Developers can inspect spacing, styles, and variables.
Export assets like icons and logos optimised for Power BI.
Annotate component usage (e.g., “This slicer maps to field ‘Region’ in Power BI”).
👉 Advanced move: Use GitHub to store dual artefacts: Figma tokens and Power BI theme JSON files. This creates a design-ops bridge where designers and engineers speak the same language.
5. Version Control & Iteration
Data visualisation evolves constantly. KPIs shift, regulations change, and executives demand new cuts of data. Figma workflows support:
Branching for experiments → e.g., test different layouts for a financial overview page.
Merge protocols → validated changes are merged back into the master design library.
Design documentation → every update is captured with rationale, making audits easier in regulated industries.
👉 Example: A government agency required annual accessibility audits. Because the Figma workflow tracked design rationale, compliance teams could easily verify that dashboard updates maintained WCAG 2.1 AA standards.
6. Cross-Functional Collaboration at Scale
The true value of this workflow emerges when design, data, and product teams collaborate seamlessly:
Product Managers → validate that dashboards align with business strategy.
Designers → enforce consistency and UX clarity.
Engineers / BI Developers → implement Power BI reports efficiently.
Executives & Stakeholders → leave comments and approvals directly in prototypes.
A strong Figma workflow is more than a design exercise—it’s a business enabler. In Power BI environments, the difference between a cluttered dashboard and a well-designed one can mean millions of dollars in misinterpreted decisions. By applying an end-to-end workflow, analytics teams transform data into clarity, trust, and action.