Ensuring an intuitive flow in the initial PVA was critical. The application needed to serve both Alfa Laval’s repair technicians, who have deep domain expertise, customer support agents, and account managers who are in discussions with the technical teams operating the heat exchangers.

To kick things off, I facilitated a discovery workshop with Alfa Laval’s key stakeholders. The goal was to align on the app’s objectives, validate assumptions, and uncover hidden challenges.
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I began with empathy mapping to encouraging participants to step into the shoes of both customers and technicians. We mapped out how they currently maintain equipment, their frustrations with existing processes, and their expectations from a new service tool.

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The unified user flow that connected every step has the following:

1. Entering the Alfa Laval PWA,
2. Scanning or uploading thermal images,
3. Generating an automated health report
4. Contacting customer support when needed.
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To make results instantly understandable, we introduced a traffic light system in backend:
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🟩 No fault have been found
🟨 Potential faults detected
🟥 Critical faults detected

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For the first round of user testing, we invited five customer support employees to test the new flow, as we were unable to access the repair technicians who would ultimately use the product. Their feedback was highly valuable:

‣ Maintenance notifications were well received.
‣ Navigation and overall logic were smooth.

Technicians, however, needed clearer guidance when using the thermal camera on how to handle connection issues and whether to capture photos within the app or upload them afterward.

Based on these insights, we refined the flow to improve usability and outcomes:

‣ Users can manually enter a serial number if it’s not found in the database.
‣ The products page now displays all owned units, completed checkups, and upcoming maintenance reminders.
‣ A fallback support flow ensures help is always accessible.
‣ Unit verification was simplified, guiding users through key questions and photo uploads to generate more accurate reports.

Beyond the solutions presented here, the project included important dimensions such as cross-functional collaboration, stakeholder alignment, and overcoming team-level challenges. I’m happy to share more about these behind-the-scenes learnings :)