
Process Optimization Tool (~85% Faster) for a Scientific Team
Timeline
7 weeks
Platform
Web (Internal Tool)
Designing a complex calculation tool into a clear, confidence-driven experience for high-stakes scientific workflows.
Confidentiality Note
This case study is a reimagined version of real-world work. All names, visuals, and data have been anonymised to respect confidentiality.
Users
Scientific Domain Experts
Analysts working with complex inputs and outputs
These users were highly knowledgeable, but often under time pressure and cognitive load.
Why This Mattered
In workflows where accuracy is critical, usability issues don’t just slow people down—they introduce doubt, friction, and risk. A better experience wasn’t about making the tool “simpler”— it was about making users feel confident, guided, and in control.
Research & Key Insights
Rather than focusing on surface-level UI issues, I looked closely at how users thought while using the tool.
Key Insights
01
Scientific teams didn't approach calculations as one-off tasks. They naturally compare multiple scenarios side by side to validate decisions.
02
When inputs disappear while switching cases, users didn't just lose time—they lose confidence in the system’s reliability.
03
Repeatedly re-entering similar values shifts focus away from analysis and toward remembering what was changed.
04
Users prefer structured exports and visual formats to quickly validate results and communicate findings with stakeholders.
My Role
UX Designer
7 Weeks
Web App
Framing the problem with stakeholders
Identifying user pain points across the workflow
Defining clearer user flows
Designing wireframes and interaction patterns
Iterating based on feedback and usability insights
The Problem
Despite the expertise of its users, the tool struggled to support them effectively.
Key Pain Points:
The system worked—but it didn’t feel reliable.
The UX “Aha” Moment
The problem wasn’t the complexity of the calculations—it was the lack of guidance, feedback, and confidence throughout the experience. Once that became clear, every design decision followed naturally.
Solution Strategy
I focused on designing an experience that supported users as they worked, not after.
Design Principles
User Flow
I focused on designing an experience that supported users as they worked, not after.

Impact & Outcome
Due to confidentiality, impact was measured qualitatively and through feedback—but the improvements were clear.
Observed Outcomes
Reduced task time from 20 minutes to 2 to 3 minutes, cutting analysis effort by 87.5% and eliminating mid workflow abandonment during complex simulations.
Enabled scientists to run up to 4 simulations in the time previously required for one, increasing experimentation capacity by 10x and strengthening repeat usage across teams.
Compressed a full day of analysis for 4 FTEs into approximately 20 minutes, significantly reducing cognitive load and minimizing manual input errors from Excel based workflows.
Accelerated cross functional decision making by delivering instant simulation outputs, allowing R&D teams to evaluate 60 analyses in 20 minutes instead of one day.
Overall, the solution reduced friction across critical workflows, improved engagement, and supported sustained usage by making complex tasks feel more predictable and manageable.
Reflection & Learnings
What this project reinforced for me
This project strengthened my approach to designing for complexity—where clarity, predictability, and confidence matter more than novelty.





