Bringing clarity to enterprise healthcare analytics.

Pareto Intelligence builds data products for some of the largest healthcare payers in the U.S., including Cigna, Blue Cross Blue Shield, and Humana. Its tools help these organizations reconcile millions in financial discrepancies, dig into complex claims data, and run more efficiently.

When I joined, the analytics underneath were strong, but the experience on top was a patchwork. Dashboards didn't match each other, workflows were confusing, and dense datasets made it hard for analysts to read a screen and act on it. My job was to bring order and usability to a set of enterprise tools handling huge volumes of sensitive financial and clinical data.

There was no shared design system, so teams built components on their own and the same UI element behaved differently from one product to the next. The mismatches in color, spacing, type, and interaction piled up design and engineering debt, slowed onboarding, made errors more likely in financial workflows, and pushed maintenance costs up over time.

At the same time, the platform had to handle dense healthcare data: claims, diagnoses, risk scoring, audits, payments, RAF charts, and compliance triggers. But the underlying structure was weak, so it was hard to spot anomalies, decide what to fix first, or compare trends. Everything leaned on Tableau dashboards that worked but didn't scale, with no clear hierarchy, clumsy cross-filtering, and little support for how specific people worked.

The company was moving to Looker and needed a UX lead to shape that transition. There was a bigger problem underneath it too: navigation, filtering, and insight patterns changed from tool to tool, so analysts had to keep relearning how to work as they moved between products.

Users weren't asking for more data. They wanted to trust what they were already looking at.

I ran a thorough UX audit: heuristic evaluations, cognitive-load and task-time analysis, error reviews with subject-matter experts, accessibility checks, and a look at how consistent the products were with each other. The same issues kept coming up: insights weren't prioritized, filtering was inconsistent, data tables were overbuilt, it took too many clicks to reach the important details, key metrics were buried, and visual noise hid the trends. Alongside that, I interviewed and shadowed analysts, claims auditors, actuarial teams, operations leaders, executives, and compliance partners.

From there, I restructured the information around a simple flow: insight, then context, then action, then audit. I standardized filtering, simplified navigation, and added reusable data groupings and priority-based layouts for the metrics that mattered most. I designed and built Pareto's first design system, then led the vision for moving dozens of Tableau dashboards into Looker: rebuilding the visuals with consistent logic, clearer drill paths, shared charting rules, better comparison views, and stronger performance under load. I validated it with interactive Figma prototypes tested with analysts across teams.

The real breakthrough was a design system that could scale across enterprise healthcare analytics.

I built a single design system that every product adopted. It standardized the type hierarchy; color coding for statuses, risk states, and data confidence; and reusable dashboard pieces like cards, KPIs, comparison tables, and filters. It also set navigation patterns, spacing, grids, composition rules, and interaction behaviors like hover, expand, drilldown, sort, and compare.

It cleared our worst internal bottlenecks: quicker, clearer specs for engineering, consistent layouts for analysts, and more predictable timelines for leadership on new features. It was easier to maintain too, and it became the foundation for every product update over the next two years.

From cluttered screens to intuitive analytics.

I redesigned several of the key dashboards so scattered data turned into something people could act on. They didn't just look better. They were measurably faster to use, easier to read, and closer to how analysts actually think, which led to sharper decisions.

The redesigned portal and the design system measurably improved the analyst experience: a 25% drop in task-completion time, a 30% drop in error rates, and a 20% increase in new subscriptions. They also gave engineering a consistent foundation for every release that followed.