Enterprise Order Lifecycle Platform
Shipped a 0→1 MVP replacing 13+ disconnected tools across the supply chain organization. Owned end-to-end design for the platform powering the company's $600B+ AI infrastructure investment.
The company's AI infrastructure investment — $600B+ in data centers, networking, and compute — runs on a supply chain that, until 2022, was managed across 13+ disconnected tools: spreadsheets, email threads, legacy ERPs, and custom one-off dashboards. No single source of truth. No unified workflow. No visibility across the lifecycle of an order.
I was brought in as the lead designer to build the platform from zero — owning the full design scope from discovery through GA launch, across the order lifecycle from procurement to delivery.
Platform overview — single dashboard spanning 5 business verticals and the full order lifecycle.
Order capture — automated ingestion from upstream planning systems with inline validation on import.
PO accuracy — automated fund matching, price master integration, and inline policy compliance.
The problem was not a missing feature. It was a missing system.
The supply chain organization had grown faster than its tooling. Each team had built local solutions to local problems — which meant that a single order might touch 5 different systems before it was fulfilled. No one had a complete picture. Errors were caught late. Escalations were manual. The cost of coordination was enormous.
13+ disconnected tools
Procurement, logistics, vendor management, and delivery tracking each lived in separate systems with no shared data model.
No unified order state
There was no single place to see where an order was in its lifecycle — from PO creation through delivery confirmation.
Manual escalation paths
When orders were delayed or blocked, the resolution path was email. There was no structured workflow for exception handling.
Research output — cross-vertical pain point mapping across 5 personas, 4 verticals, and a 3-week sprint. 60%+ of friction concentrated upstream.
Three phases, built sequentially.
Discovery — mapping the existing system.
Spent the first 6 weeks embedded with the supply chain operations team, shadowing order managers, conducting structured interviews, and mapping the full order lifecycle across all 13 tools. Output: a unified process map that became the shared reference for the entire product team.
Architecture — designing the data model before the UI.
Before opening Figma, I worked with engineering to define the core data model: what is an order, what states can it be in, what events trigger state transitions, and what roles need what visibility. The IA was designed to reflect the actual lifecycle — not the org chart.
Execution — component-driven, handoff-ready.
All UI work shipped with a documented component library: token definitions, variant specs, interactive states, and WCAG 2.1 AA annotations. Handoff included diff-ready specs — not static exports — so design QA was built into the engineering review process.
Three decisions that shaped the platform.
01
Single order record as the atomic unit.
Every view in the platform is organized around the order record — not the team, not the tool, not the vendor. This forced a shared vocabulary across the organization and made cross-team handoffs legible for the first time.
Centralized order ledger — single view across all verticals with a filterable, sortable primary surface and clear status taxonomy.
02
Status taxonomy before UI.
Before designing a single screen, I worked with ops leads to define the canonical set of order states and the rules for transitioning between them. This became the foundation for the notification system, the exception handling workflow, and the reporting layer.
Inline validation — errors surfaced at point of entry, navigable without leaving context, with inline conflict flagging.
03
Progressive disclosure for complexity.
The platform serves users with very different levels of context — from order managers who need deep detail to executives who need summary views. The information architecture uses progressive disclosure to serve both without building two separate products.
Role-based views — Leadership, Finance, and Operations each see the right information density from the same underlying data model.
The most important design decision was upstream of any artifact: what is an order, and what does it mean for it to be complete?
04
Audit trail and accountability layer
Every state change logged with actor attribution, timestamp, and reason. Why, not just what.
05
Extensible component system
Reusable primitives across one system, five business units. Designed for expansion from day one.
06
Order management that improves user productivity
Bulk actions, shareable URLs, saved search, and collaboration. +300 diffs reviewed by design.
The platform shipped to 100% adoption within the supply chain organization — which, given the number of legacy tools it replaced, required a change management strategy as much as a design strategy. The adoption rate is a function of the platform being genuinely better than the alternatives, not just mandated.
This project taught me that the most important design work in enterprise platforms happens before any UI is designed. The data model, the state taxonomy, the role definitions — these are design decisions, even if they don't look like design artifacts.
A platform that reflects how work actually happens will always outperform one that reflects how the org chart is drawn.
The supply chain platform is now the operational backbone for the company's AI infrastructure investment. Every data center build, every networking component, every compute unit that ships — runs through this system. That's a level of impact that's hard to overstate, and it started with a process map and a very long list of questions.