Davis Insight
DavisInsight
Making complex market data easier to read, faster to access, and built to scale
Role: Product Designer (UX/UI)
Platform: Web Application (B2B Analytics)
Tools: Figma, Figjam
Overview
DavisInsight is an internal intelligence platform built for traders and analysts to monitor pricing trends, mill performance, and month-on-month market movements. The challenge wasn't a lack of data, it was helping users interpret that data quickly enough to make confident business decisions.
My goal was to design an experience that reduced cognitive effort, surfaced the most relevant insights first, and created a scalable design foundation as the platform continued to grow.
The Problem I Was Designing For
Commodity traders don't browse dashboards.
They open the platform with a specific question in mind.
Has pricing changed?
Which mills moved this month?
Where should I investigate further?
The existing product exposed every piece of information at once. Filters were scattered across multiple areas, navigation consumed valuable workspace, and dashboards had evolved independently over time, creating inconsistent patterns throughout the product.
Every additional click slowed down decision making.
The challenge wasn't adding more functionality.
It was making complex information easier to consume.
Discovery & Research
Since DavisInsight was a brand new internal product, there wasn't an existing user base to interview or usability-test against.
Instead, discovery focused on understanding the business domain, analytical workflows, and technical constraints before designing the experience.
Stakeholder Discovery
I worked closely with
COO
Data Team
Engineering Team
to understand
how pricing calculations worked
how traders interpreted market changes
how analysts compared historical data
technical limitations around data visualization
long-term product goals
Rather than designing individual screens, we first aligned on how users actually thought about market data.
Domain Research
To better understand enterprise analytics products, I reviewed platforms including
Bloomberg Terminal
TradingView
Tableau
Power BI
Capital IQ
I focused less on visual styling and more on how these products organized dense information, prioritized insights, handled filtering, and supported analytical workflows. Existing enterprise dashboards consistently balanced large volumes of data through modular layouts, progressive disclosure, and clear information hierarchy.
Competitive Analysis
Core Findings
Although each platform solved analytics differently, the same usability problems appeared repeatedly.
Information overload
Complex navigation
Inconsistent filtering
Weak visual hierarchy
High learning curve
The products that felt easiest to use weren't displaying less information.
They simply presented it more intentionally.
Design Principles
Three principles guided every design decision.
Surface insights before data
Users should immediately understand what's happening before exploring detailed reports.
Reduce cognitive load
Grouping related information, simplifying filters, and improving hierarchy should reduce the effort required to complete common tasks.
Design for scalability
Every new dashboard should inherit the same interaction patterns and component system.
User Journey
Understanding the user's analytical workflow helped shape the dashboard structure.
Site Map
The navigation hierarchy was simplified into a predictable structure that grouped related functionality while keeping frequently accessed pages one click away.
Design Exploration
Using the research findings as a foundation, I redesigned the platform around how traders naturally consume information.
Key improvements included
restructuring dashboard hierarchy
consolidating filters
introducing a collapsible navigation
improving chart readability
standardizing tables
reducing visual clutter
Building a Scalable Design System
Rather than solving isolated interface problems, I created a reusable design library in Figma containing
dashboard layouts
filter components
KPI cards
chart containers
tables
navigation
spacing
typography
This allowed future dashboards to be built using consistent patterns rather than redesigning common elements from scratch.
Collaboration
Throughout the project I collaborated closely with
the COO to align design decisions with product strategy
the Data Team to understand pricing logic and analytical requirements
Engineering to balance usability with technical feasibility
This iterative collaboration ensured the product remained aligned with both business goals and implementation constraints.
Outcome
The redesigned experience established a scalable foundation for DavisInsight.
Key outcomes included
Platform delivered 20% ahead of schedule
Unified design system introduced across the product
Consistent dashboard patterns
Improved information hierarchy
Simplified filtering experience
Reduced visual clutter
Faster design-to-development workflow
Most importantly, the platform shifted from presenting data to supporting decision making, helping traders and analysts understand market movements with less cognitive effort.
Reflection
Working on DavisInsight changed how I think about enterprise software.
Good dashboard design isn't about fitting more information onto a screen. It's about deciding what deserves attention first. Throughout the project, every design decision came back to a single question:
Will this help users reach a decision faster?
That principle influenced everything, from the information architecture to the design system, and became the foundation for how I approach complex, data-heavy products today.