Case study
Eaton EPMS. Smart Alarm Discovery Research
Understanding what "smart" alarms mean to EPMS users, before building them
Senior UX Researcher
1-on-1 interviews
Design Thinking Workshop
The challenge
Alarm notification is one of the most essential features of Electrical Power Monitoring Systems (EPMS), directly shaping how data centers, manufacturing facilities, and building operators detect and respond to critical events. With recent technology developments, including the introduction of AI across many tasks and workflows, user expectations for smart, responsive systems have risen sharply. This research set out to close the gap between those rising expectations and Eaton's current alarm experience, understanding how users across our core segments actually work with alarms today, and identifying concrete opportunities to steer product strategy ahead of the curve.
Outcome & impact
3 main use cases that guided new feature prioritization and shaped customer support strategy.
Proposed a framework of [redacted] versus [redacted] to guide platform decisions and pricing policy.
Identified more than 20 opportunities for new features across 5 categories.
Planned and facilitated a design-thinking workshop for ideation and prioritization of these features.
Research Process
01 — Panel management
Managed relations with third-party vendor.
02 — data collection
13 one-on-one interviews, conducted via video call.
03 — synthesis
Using swim lane process mapping and thematic coding
04 — Alignment
Make the next decision easier for everyone.
Process Highlights
Artifact
Swim Lane Diagrams
To make the top 3 use cases actionable, I mapped each one into a swim lane diagram showing how different roles interact with the EPMS during an alarm event. Swiml anes made the cross-functional handoffs visible in a way a use-case list couldn't, giving product and technical teams a shared reference to prioritize strategy around.
Artifact
Proposed framework
Using segment-specific determinants uncovered in the research, I proposed a framework for understanding how market [redacted variable] shapes feature and platform expectations across segments. This gave the product team a structured way to target features and inform platform and pricing decisions by segment, rather than treating all customers the same way.
recommendations
Possible Features
I translated user pain points into the broader underlying needs driving them, then mapped each need to possible features that could address it. This gave the product team a clear line from research finding to actionable feature direction, rather than a list of complaints without a path forward.
Reflections and learnings
Held together very different research traditions, speculative futures methods, ethnographic personas, and quantitative regression modeling, within a single coherent research narrative, rather than treating them as separate exercises.
Informed each year's research with insights and methods from the previous cohort, creating a continuous cycle of process refinement and team expertise development.
Created product proposals through a prospective, forward-looking lens, and participated directly in the intellectual property application process.
Mentored students across disciplines and degree levels within a design studio environment, structuring subgroups to ensure interdisciplinary representation on every team.