Senior Product Designer | Enterprise SaaS
LG Display vessel tracking
Operators required 6+ steps to detect shipment issues
Founding Product Designer · FNS · Q4 2024 – Q3 2025
FNS is a third party logistics provider supporting LG Display's global shipments. Operators track vessels across ports, terminals, and routes to detect disruptions. However, identifying a single issue required 6+ manual steps across fragmented GIS tools.
PROJECT OVERVIEW
Company
FNS is LG Display's dedicated logistics partner.
Client
LG Display
Shipment flow:
LG Display → Best Buy (US retail distribution)
Impact
Reduced investigation steps from 6 to 2.
Improved issue detection speed by 83%.
From Origin to Destination: Vessel History and Tracking Details
THE OVERVIEW
Marine Traffic showed vessels.
It didn't show what mattered.
FNS manages 300+ vessel shipments for LG Display between Korea and U.S. retail warehouses. LG had no direct visibility into their own shipments. Every update required manual lookups and back-and-forth with the FNS teams.
Users:
FNS ops and logistics, LG Display logistics Korea
BEFORE AND AFTER
Fragmented tools, unified workspace
BEFORE
01 Fragmented investigation workflow
Shipment data was scattered across multiple views and panels
AFTER
01 Unified shipment monitoring workspace
Signals were centralized into one interface
02 Low signal visibility
Critical issues were buried inside geographic context, making them difficult to detect quickly
03 Delayed operational response
Operators had to cross-reference spreadsheets to reconstruct shipment status delaying issue detection
02 Signal-first visibility
Critical issues were surfaced and prioritized
.png){kind=tracking}
03 Faster operational investigation
A unified search interface replaced manual lookups operators could find and act on critical signals in one place.
THE PROBLEM
This forced operators to reconstruct context manually, delaying issue detection.
This resulted in:
— High cognitive load
— Delayed issue detection
— Inconsistent operational responses
BUSINESS ISSUES
Fragmented GIS tools created slow and inconsistent monitoring workflows.
USER ISSUES
Operators could not quickly identify critical shipment signals.
KEY UX INSIGHT
Map-centric design blocked
operational decisions.
Recorded operator screen shares showed operators spent 70% of their time navigating, not deciding. This required redefining shipment monitoring from map navigation to signal driven decision making. Demoting the GIS map required aligning the head of operations and engineering lead. I reframed it from a product identity question to a workflow efficiency decision.
This created a mismatch between:
— System structure: map-centric
— User goal: signal detection and action
01. Destinations were not directly accessible
Critical issues were buried inside geographic context, making them difficult to detect quickly
02.Shipment status required manual lookup
Critical shipment details were buried inside vessel pop-ups — operators had to click each one individually to check status.
03.Critical signals were not directly accessible
Operators had to click through hundreds of vessel dots — no way to filter by urgency.
DESIGN HYPOTHESIS
The problem was not visibility,
but how signals were structured and surfaced.
Instead of requiring operators to navigate maps, the system should surface risk-ranked signals first — so operators can identify and act before the escalation window closes.
Instead of making operators search through dense maps, the system should surface critical vessels and exceptions first, so they can assess and act faster.
DESIGN TRADE OFF
Marine Traffic vs Custom map for LG tracking
We had two options.
Make the existing screens slightly better.
Or rethink how teams investigate incidents altogether.
Option A: Map-centered layout
Option B : Signal-first layout ← Chosen
Weaknesses:
1. LG vessel data overlay on third-party map — no control over rendering
2. Marine Traffic API rate limits restrict real-time updates
3. Custom data contracts required for each LG route layer
Strengths:
1. No map rebuild required
2. Lower engineering effort
3. Faster to ship
Weaknesses:
1. Custom GIS tile server required from scratch
2. Real-time AIS data pipeline integration — high infra cost
3. Cross-browser map rendering consistency issues
Strengths:
1. Full control over vessel data schema and rendering
2. Signal priority logic embedded directly in map layer
3. No third-party API dependency for core tracking
The Head of Operations wanted the map as the primary view. I brought observation data showing operators spent 70% of their time navigating, not deciding. That reframed it from a layout preference to a workflow efficiency decision.
DESIGN DECISION
LG's escalation logic didn't exist.
I built it from scratch.
We made custom prioritizational logic for LG to help them triage the risk
FINAL APPROVAL
A signal-first monitoring workflow
for real-time decision-making
This established a consistent decision model operators could use across shipment workflows. The final design operationalized the signal-first approach into a production-ready monitoring workflow. Instead of navigating across fragmented GIS views, the redesign shifted the system from a map-driven exploration model to a signal-driven decision system, enabling operators to detect and respond to issues without manual context reconstruction.
Critical shipment signals surfaced directly in the list instead of being hidden inside map interactions
EDGE CASES
Operators can continue decision-making even when data is missing or partially available.
These edge cases were defined collaboratively with the engineering lead to ensure the system handled incomplete data gracefully, not just the ideal flow.
Edge Case: 01 No Data Found
When vessel data is unavailable, the system shows the last confirmed status with a timestamp so operators don't misread silence as "no issue."
Edge Case: 02 Revised Shipment Details
When shipment details update mid-transit, changes are flagged inline so operators can act without reopening the full record.
IMPACT & RESULT
Approved for production rollout
across operations teams
Restructuring how signals are surfaced transformed operational workflows and improved decision-making at scale. This reduced reliance on individual operator expertise and made the system more scalable across different teams and use cases.
6 →2
Steps per investigation
83%
faster escalation time
6/6
approved by 6 directors
Based on recorded operator screen shares during prototype validation.