Aspen Unified Usability Study — De-risking a Platform Redesign With Real User Evidence
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Case Study Snapshot:
Aspen Unified—a platform and workflow hub for oil & gas scheduling, buying/selling, and accounting—was overdue for modernization, but the risk was shipping a "modern-looking" redesign that failed in real users' hands. I led a one-year research program built around iterative, evidence-based decision-making: four rounds of moderated remote usability studies with 20 participants across roles (engineers, planners, accountants, data scientists), measuring task success, time-on-task, and error rate. To support rapid iteration, I built dozens of Figma prototypes simulating realistic behaviors—convergence flows, multi-step wizards, data-dense tables—so testing reflected actual use, not happy-path clicking.
The findings directly changed the product: navigation became significantly clearer, users required ~60% fewer clicks on core tasks, and—most surprisingly—users had little to no need for documentation because the hub structure reduced confusion. The roadmap was reprioritized based on evidence, features were cut where they created friction, and workflows were consolidated into cleaner hubs. Results included faster onboarding, improved task success, fewer defects, and NPS/CSAT uplift. Most importantly, the study prevented a risky launch by validating direction before GA.
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Context:
Aspen Unified is a platform and workflow hub for the oil & gas industry—supporting scheduling, buying/selling, and accounting. It spans complex domains (simulation, planning, optimization) and serves a broad set of users, from engineers to accountants.
Problem:
The UX was legacy and overdue for modernization. A rebrand and executive mandate raised the stakes: this needed to become cleaner, faster, and more intuitive—without breaking mission-critical workflows. The risk was shipping a “modern-looking” redesign that failed in the hands of real users.
Approach:
We ran a one-year research program built around iterative, evidence-based decision-making:
4 rounds of moderated remote usability studies, with longitudinal follow-ups
20 participants recruited through Product Management and partners
A diverse participant mix: senior/junior chemical and process engineers, planners, operations experts, data scientists, and accountants
Measurement focused on what matters in enterprise workflows: task success, time-on-task, error rate, and qualitative feedback
To support rapid iteration, I built dozens of Figma prototypes, ranging from simple flows to highly complex simulations. Using Figma Make and interactive prototyping, we simulated realistic behaviors: convergence flows, multi-step wizards, and data-dense tables/charts—so testing reflected actual use, not “happy-path clicking.”
What we tested:
End-to-end scenarios that mirrored real work
Create a workflow
Import data
Run optimization
Interpret results
Export a report
The studies drove clear, actionable direction:
Navigation was significantly clearer and more learnable
Users required ~60% fewer clicks to complete core tasks
Decision-making became faster and more confident
The experience translated more smoothly across devices
Biggest surprise: users had little to no need for documentation because the hub structure and workflow clarity reduced confusion
Outcomes:
The findings weren’t “nice insights”—they changed the product:
Roadmap reprioritized based on evidence
Features cut where they created friction or didn’t add value
Workflows simplified and consolidated into cleaner hubs
Training time was effectively eliminated for the tested flows
Improved task success, faster onboarding, fewer defects, and an uplift in customer sentiment (NPS/CSAT)
Most importantly: prevented a risky launch by validating direction before GA
My role and team:
I served as synthesis lead and executive sponsor, ensuring findings translated into decisions and shipped outcomes. The team included 2 product designers, 3 UX researchers, 3 PMs, and 10 developers across the year.