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FEI HUANG

Meta · Evolving one design system · 02 of 03

Decision Frameworks
Data Visualization System for Meta Business Products

Team & Collaboration

Fei Huang                                   

Lead Product Designer I Data Visualization System

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Partners

Platform Engineering, UXR, PMs, and teams across Meta Ads and analytics surfaces

My focus

Reframed the design system's role in analytics from chart delivery to decision support — prioritizing reusable patterns that could serve a wide range of literacy levels while unlocking the greatest number of product teams given the organization's direction and constraints at the time.

 

Drove the shift from a DS bottleneck model to a contribution model by consolidating fragmented documentation, pushing back on independently built vertical solutions, and shipping reusable analytics patterns as operational proof points. The patterns launched in production and began scaling across Meta's business products.

Project Overview

Meta Ads and business products rely heavily on data visualization to help advertisers interpret performance and take actions, increasingly alongside automated insights and recommendations within complex campaign workflows.

 

I owned the data visualization domain within the Geo design system, evolving components, patterns, and system guidance across multiple releases.

 

This case highlights one example of that work: enabling decision workflows through more flexible chart components and patterns.

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Over multiple releases, I led the design system effort to evolve decision-making components, enabling product teams to move from simply showing metrics to supporting decision-making actions across surfaces.


This work supported 200+ designers and engineers across Meta Ads products.​

Scope

  • Led strategy and system design for Meta’s data visualization framework

  • Identified system gaps and aligned product and design leadership on the direction

  • Defined the structural relationship between insights, actions, and workflows so teams could build analytics experiences with predictable interaction patterns.

  • Designed flexible components and decision patterns with engineering and PM partners

  • Established contribution models, documentation, and education to enable adoption across teams.

System Problems

Two system gaps were limiting product teams:

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  • Rigid components: existing charts had fixed layouts and limited configuration, making it difficult for teams to adapt visualizations to real analytical workflows.

  • Missing decision patterns: charts surfaced insights but did not support decisions, so teams combined charts with UI controls in inconsistent ways.

 

These workarounds created fragmented layouts and inconsistent interaction patterns across products.

Key System Moves

1. Evolving chart components

I redesigned core chart components to support real analytical workflows.

 

One key change was evolving the horizontal bar chart component with configurable spacing, enabling teams to compose comparison and selection workflows while preserving system alignment.

Screenshot 2026-03-08 at 9.19.56 PM.png

System composition/pattern anatomy

2. Enabling decision patterns

Beyond components, we introduced reusable system patterns that connect insights with actions.

 

These patterns allow product teams to combine visualizations, insights, and next steps in a consistent structure across analytics surfaces.

3. Scaling across products

The work was implemented across Meta Ads products and adopted by multiple teams building measurement and analytics experiences.

System Leadership & Adoption

Beyond the component work, I led the design system initiative to ensure the patterns could scale across teams.

 

This included defining the data visualization contribution model, establishing feedback loops with product teams, and delivering documentation and education to help teams adopt the patterns consistently across Meta Ads surfaces.

Impact

• Enabled reusable analytics patterns across 6+ product surfaces
• Unblocked 200+ designers and engineers building analytics workflows
• Reduced custom visualization implementations through reusable components
• Contributed to a double-digit reduction in usability issues in analytics experiences

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*Full project walkthrough available upon request

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