An Excel Sheet With a Billion-Dollar Problem

Supply chain risk data is inherently complex. A single enterprise customer might monitor thousands of suppliers across global tiers, each surfacing dozens of risk signals: ransomware events, sanction changes, labor violations, financial instability, sourcing dependencies. The challenge for Interos's new platform was making all of that legible to analyst power users at a glance, condensing complex datasets into meaningful aggregates without losing the fidelity those analysts needed to act.

What had been built before was a legacy platform that surfaced supplier data as rows of attributes with no narrative and no path to action. Analysts called it an Excel sheet with a portal wrapped around it. For a product selling clarity around supply chain risk, the v1 experience did the opposite of what it promised.

I joined through Neudesic in early 2021, embedded as a UX Feature Lead inside Interos's product team. The platform redesign was already underway. Pages were being built in parallel by multiple designers, including third parties. My role was bringing design coherence and quality to core pages, expanding the company's minimal design system as those pages shipped, and acting as a bridge between design and an engineering team that had historically worked in isolation from UX.

The most useful research wasn't about the product, it was about Interos itself. The company had grown fast enough that nobody had a clear picture of their own data acquisition process. Which sources had been purchased? Which were active? Who owned what? The answer depended entirely on who you asked.

I led a one-month engagement interviewing every department head across the data acquisition lifecycle. Mapped each team's role, identified where handoffs broke down, traced the process across every Jira board it touched. Output: an end-to-end journey map of the data lifecycle, with pain points annotated and recommendations structured as good, better, best so stakeholders at different investment levels could act on it.

That research clarified something about the product layer too. The core design challenge wasn't visual polish, it was data density. Supply chain risk is inherently complex. The job isn't to simplify it into something false. It's to give it enough structure that users can act on it. This framing shaped every workstream that followed: lead with risk posture at the aggregate level, surface the most urgent changes, allow drill-down only with intentional interaction. Progressive disclosure as a core principle, not a tactic.

Platform V2 launched in July 2021, the first major redesign of the Interos product experience. Five workstreams delivered. A junior designer mentored through the engagement. A data lifecycle map that gave the company a single source of truth it didn't have before. The UX Review process running as a standard part of the development cycle.

The platform shipped looked nothing like the spreadsheet they started with. It had hierarchy, narrative, and a clear action path from aggregate to detail.

Interos reached unicorn status, $1B+ valuation, during the engagement. The work shipped inside that velocity. The UX Review process carried forward beyond my engagement, becoming part of how the company shipped product to enterprise clients.

Interos taught me what UX looks like inside a company outpacing its own process. The infrastructure to support good design was being built in real time while I was trying to use it. The most valuable skill I sharpened was designing for data density: finding the right level of abstraction for complex enterprise data so it becomes legible without losing fidelity. If I were starting over, I'd push harder earlier to expand the design system in step with the page work, so each new workstream inherited more shared structure than the last.