LIAD Industrial
Analytics Dashboard
Designing an operational analytics dashboard for a logistics company โ giving fleet managers and warehouse supervisors real-time visibility into vehicle tracking, delivery performance, and inventory flow.
Disconnected Logistics Data
The insight: Fleet managers and warehouse supervisors require instantaneous, unified access to data. When fleet tracking and warehouse inventory live in separate silos, reacting to real-time disruptions becomes impossible.
No Fleet Visibility
Managers relied entirely on phone calls to track vehicles, leaving them unaware of delays until they occurred.
Data Silos
Warehouse data existed in Excel, while fleet data was buried in WhatsApp, causing misalignment.
Delayed Alerts
Incidents like breakdowns or stockouts were reported hours late, escalating minor issues into major delays.
Manual Reporting
Compiling weekly performance reports consumed two full days for supervisors, wasting valuable time.
Understanding the Operations Landscape
To build a useful dashboard, I immersed myself in the daily realities of fleet and warehouse operations to identify exact touchpoints where real-time data could streamline work.
Field Observations
Spent time at 2 warehouse sites observing how supervisors tracked incoming and outgoing inventory.
Ride-alongs
Shadowed delivery drivers to understand their constraints, communication methods, and pain points during transit.
Stakeholder Workshops
Conducted sessions with the ops team to align on essential metrics and immediate notification needs.
Competitor Audit
Audited existing dashboards like FourKites and Samsara to evaluate industry standards for logistics platforms.
Who We're Designing For
Illustrative โ Based on research patternsAnil K.
Fleet Operations Manager, 38"I need to see all my vehicles on one screen, not chase 10 different WhatsApp groups."
Goals
Frustrations
Deepa R.
Warehouse Supervisor, 42"By the time I see last week's data, it's already too late to fix anything."
Goals
Frustrations
Sees
- Chaotic WhatsApp chats
- Endless Excel rows
- Drivers waiting at loading docks
Says
- "Where is truck #402 right now?"
- "We need the report by EOD."
- "Call the driver immediately."
Thinks
- Is this data even accurate?
- How can I prevent this delay next time?
- I wish everything was in one place.
Feels
- Stressed during peak hours
- Frustrated by manual tracking
- Overwhelmed by scattered updates
Structuring Operational Data
The architecture focuses on high-level observability that allows users to seamlessly drill down into specific vehicles, warehouses, or incidents.
Mapping the Dashboard
Wireframes were tailored to maximize information density while keeping vital metrics immediately visible.
A live map showing all 50+ vehicles with status indicators and quick-view cards on hover.
A clear grid displaying current stock levels, incoming shipments, and available dock space.
Aggregated metrics showcasing delivery times, fuel efficiency, and overall performance.
Operational UI Kit
The visual language needed to communicate urgency and clarity. Colors were selected specifically for their semantic meaning in an operational context.
High-Fidelity Dashboard Screens
The finalized interfaces deliver data efficiently, reducing cognitive load while ensuring critical alerts cannot be missed.
Dashboard Overview
The central hub providing a macro view of fleet and warehouse status simultaneously.
Fleet Tracking Map
Real-time vehicle locations with semantic color coding for delays and on-time status.
Warehouse Analytics
Detailed breakdown of inventory flow, highlighting bottlenecks across the 3 sites.
Incident Reports
A structured log of real-time alerts and historical incidents for rapid resolution.
Usability Validation
Illustrative findings โ Based on design review sessionsFinding 01
Issue: Fleet managers found the map view too cluttered when all 50 vehicles were shown.
Fix: Implemented clustering and filter toggles to show vehicles by status (e.g., delayed, on-time).
Finding 02
Issue: Important incident alerts blended in with general notifications.
Fix: Redesigned alerts using Alert Orange (#E65100) and added a dedicated top-bar ticker for critical incidents.
Finding 03
Issue: Supervisors struggled to export reports for custom date ranges.
Fix: Streamlined the export flow and added one-click preset ranges (last 7 days, this month).
Key Outcomes
Illustrative metrics โ actual results confidentialWhat I Learned
Information Density is a Balancing Act
Operational dashboards need to show a lot of data at once, but overloading the user leads to paralysis. Strategic use of white space and progressive disclosure is critical.
Real-Time Means Actionable
Displaying live data isn't enough; the interface must provide immediate actions alongside the data, enabling users to respond to issues instantly.
Semantic Color Reduces Cognitive Load
In high-stress logistics environments, users shouldn't have to read text to understand a status. Consistent, semantic color coding allows for split-second comprehension.
Looking Back
Designing the LIAD dashboard highlighted the profound impact of operational design. Moving a team from fragmented spreadsheets to a unified, real-time dashboard isn't just about UI โ it's about fundamentally transforming how they run their business and respond to supply chain realities.