Brighton Science
Role
UI/UX Designer
Type of Project
Real Client Project
Project Duration
One Week
The Problem: Too Much Data, Too Little Clarity
Brighton Science needed a way to streamline data visualization and reduce manual entry on their BConnect web app. The goal was to design a consolidated GR&R dashboard to help manufacturing and QA managers quickly assess measurement reliability without losing data.
The Process
01. Discovery
02. Define
03. Ideate
04. Prototype
05. Handoff
Discovery
Define
Ideate
Prototype
Handoff
01. Understanding the Problem Before Solving It 🔍
Listening to the Experts 🎙
To align the design with user needs, we began with stakeholder interviews to understand the pain points directly from the development team and key users.
These insights highlighted the need for a streamlined dashboard that simplifies data interpretation and reduces manual tasks.
Walking in the User’s Shoes (Without the Blisters) 🗺
We mapped out how QA managers interacted with the BConnect dashboard to dig deeper. This revealed a few glaring issues:
Navigation was a Maze: Important metrics were buried under too many clicks.
Cognitive Overload: Users were overwhelmed by cluttered data and complicated charts.
Exporting Data Was a Pain: Manually copying data to Excel disrupted workflows.
This map highlighted which parts of the dashboard needed a redesign first making the data easier to find and understand without overwhelming users.
Discovery
Define
Ideate
Prototype
Handoff
02. Prioritizing What Matters Most 🛠
The findings from our interviews and journey maps made it clear that the redesigned dashboard needed to focus on:
Focusing on these priorities helped keep the design process practical and user-centered.
Discovery
Define
Ideate
Prototype
Handoff
03. Dashboard That Works Smarter, Not Harder 🖼
Armed with a clear direction, we moved into ideation to sketch out potential solutions without making things more complicated than they needed to be.
Focusing on What Matters Most 🎯
We created feature cards that highlighted only the essentials:
Clear Result Views: Pass/fail tests are at the top, and no scrolling is required.
Readable Data Tables: Detailed info at the bottom but easy on the eyes.
No Extra Fluff: Excluded anything that didn’t help users make decisions faster.
This approach was about keeping the design clean and straightforward because a cluttered dashboard helps no one.
Example of one of my concepts
Aligning Design with Development 🚦
We held meetings with the development team to assess the effort needed for each feature using story points and T-shirt sizing. This helped us prioritize features that were both impactful and feasible to develop quickly.
Prioritizing Features That Matter ⚖️
After presenting the feature cards, we conducted a dot vote to narrow down the 13 proposed features to the 10 most valuable ones. This helped the team focus on high-impact features that addressed key pain points without overcomplicating the design.
Validating What Users Want ⚖️
To ensure these features aligned with user needs, we bundled them into a Kano Survey (Diserability test) and sent it to six key stakeholders. The feedback clarified which features were must-haves, performance boosters, and nice-to-haves, directly shaping the final design decisions.
We modeled the chosen Concept using a Kano Analysis Model
Double Checking just to be Safe
Another designer and I approached the Kano Analysis from a methodically mathematical perspective, turning the desirability survey results into a spreadsheet with multiple data tables. And the mathematical method we took aligned with the Kano Analysis Model, which was shocking.
Discovery
Define
Ideate
Prototype
Handoff
04. Bringing It All Together 💡
We built a simple, clickable prototype in Figma to show stakeholders how the new dashboard would work
Discovery
Define
Ideate
Prototype
Handoff
05. No Lost-in-Translation Moments 📊
To make sure nothing got lost between design and development, we put together an annotated findings report
What Worked, What Didn’t, and What’s Next 🤔
This project proved that listening to users and developers early on makes the design process a lot less painful. Prioritizing features based on actual feedback (and not just gut feelings) helped us build a dashboard that’s both useful and realistic to develop.
Focusing on clear data visuals and automation showed that good UX isn’t about adding more it’s about making what’s there easier to understand and use. For future iterations, gathering direct feedback from QA managers will be key to fine-tuning the design even further. 🚀