Energy Loss Analysis & Optimization

The Opportunity

Loss analysis is critical to maximizing production on PV (solar) projects, but most of the industry's monitoring platforms don't do it well. The major SCADAs on the market offer some version of it, without the precision teams actually need — so the EPCs and O&Ms who build and maintain these sites end up doing it manually: an analyst runs expected-vs-actual production against the customer's own performance-ratio formula, while the field team tries to trace losses back to historic alerts and tickets.

We saw a chance to build something genuinely better — precise enough to become a real tie-breaker in sales conversations, not just another checkbox feature. It would give prospective customers a concrete reason Solargik trackers outperform, and a reason to pay for the software layer on top. We were well positioned to deliver it: our sensors and trackers in the field, plus direct connections to inverters, gave us granular data to build on, rather than reconstructing it secondhand through a cloud API.

My Role

Product Designer, owning UX strategy and interaction design end to end — from mapping the existing manual workflow through to the shipped v1 and the v2 improvements driven by customer validation.

The Process

The core goal was to create a clear, intuitive view for site operators to analyze energy loss sources and track actual versus expected production.

• Discovery: deeply mapping the existing manual loss-analysis workflow used by O&M teams.
• Design & Visualization: the central design challenge was creating a clean, high-fidelity visual representation of the gap between planned energy production and actual output. We focused on delivering a "glanceable" summary that provided immediate, clear value even before the user interacted further. This meant translating complex, interdependent parameters — environmental, equipment, contractual — into a structured loss breakdown, letting users drill into every subcategory. A key priority was data credibility: giving operators confidence that the numbers accurately reflected the performance shortfall.
• Validation: deploying the initial design and running in-depth interviews off the back of enthusiastic customer feedback. That feedback directly inspired and shaped the drill-down improvements in the v2 release below.

v1 → v2: customer interviews showed operators wanted to keep drilling past the top-line loss categories, so v2 opened every category into its own subcategory breakdown (internal shading, soiling, module degradation, mismatch, and more).

Key UX Decisions

The Outcome

The project turned complex data into clear, actionable insight, empowering operators to troubleshoot faster and with confidence.

• User success: operators adopted the tool rapidly. The design delivered immediate value through a single-glance dashboard summary, paired with the ability to drill down and understand the precise losses in every subcategory — customer feedback confirmed how valuable that dual functionality became in their daily work, significantly reducing time spent on manual analysis.
• Business impact: the new design was highlighted in company keynotes and industry conferences as a leading feature of the monitoring platform, directly contributing to product adoption and sales.