Supply Chain Intelligence

Deposco's platform sits at the center of its customers' operations — orders, inventory, shipping, and labor all flow through it. That depth produces an enormous amount of data, but data alone doesn't move a business forward. Customers needed a way to see what was happening across their supply chain and, more importantly, to know what to do about it.

Supply Chain Intelligence was the answer: a command center that turns operational signals into action. I joined as the lead product designer responsible for the screens behind the offering — defining how complex supply-chain data becomes something an executive or operator can act on in seconds.

As lead product designer, I owned the end-to-end design of the Shipping, Inventory, and Labor Intelligence experiences — from first research through developer handoff. I also designed Deposco's Executive Intelligence mobile app, the executive-facing companion to this offering, which I cover in depth in its own case study.

Across all of it, my goal was consistency: a single visual and interaction language, so that learning one Intelligence module means knowing how to use them all.

I started wide. Working with product and engineering, I ran whiteboarding sessions to map the problem space, built journey maps to understand how each role actually moves through their day, and grounded the direction in UX research with the people who'd use it. Understanding the operational context — and where decisions were getting stuck — shaped everything that followed.

From there I moved fast and iteratively — sketching concepts, building wireframes, mapping user flows, and pressure-testing every round against real user needs. By the time a screen reached high fidelity it had already earned its layout, and I carried that fidelity into a close partnership with engineering through handoff.

The most important decision wasn't any single screen — it was the framework underneath them. I designed the Intelligence UI as a scalable system: a consistent structure for navigation, data visualization, and the all-important “what to do next,” that any new module can adopt out of the box.

That consistency is exactly what the three modules below show: Shipping, Inventory, and Labor are different data, but the same language. It's also what lets the offering grow — the framework already supports new subpages built for specific customer needs, and it's the foundation for six more categories of intelligence on the way.

Each module applies the same framework to a different slice of the operation. Shipping Intelligence turns carrier and network performance into cost-saving moves. Inventory Intelligence reframes inventory from counting to capitalizing — surfacing where working capital is trapped. Labor Intelligence makes workforce performance and cost-to-serve visible in real time.

“Opportunities” is a newer feature within the offering that surfaces the highest-value actions a customer should take next. For this one I leaned heavily on AI as a design partner — using Claude Code and Figma Make to iterate on concepts and stand up ultra-high-fidelity, interactive prototypes far faster than traditional methods allow.

Those prototypes did real work: they aligned the internal team around a shared vision, and let me put a near-real experience in front of users for research — so the feedback I gathered was about the actual interaction, not an imagination of it.

I partnered closely with engineering through handoff and build, staying in the loop to protect the experience as it became real. But launch was the starting line, not the finish. I continue to add pages for specific user needs and refine the experience as I watch real customers use it — research-driven iteration on a product that's genuinely alive.

Supply Chain Intelligence became a flagship part of Deposco's offering — a differentiator that drives expansion sales with existing customers and helps win new ones. Just as importantly, the framework behind it means that value compounds: every new module and subpage ships faster because the foundation is already there.

It's the work I'm most proud of — not because it's finished, but because it isn't. It's a living product I get to keep sharpening with every round of research.