Overview
I worked within the Product Design and Strategy team on a SaaS digital freight decision platform designed to support complex, multi-modal logistics operations. The platform integrated multiple systems to deliver personalized logistics and delivery experiences for suppliers while maintaining system performance and usability.
Responsibility
I collaborated closely with:
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Product managers
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Strategy stakeholders
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Engineers and domain experts
Tasks completed:
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Product discovery and problem definition
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User research synthesis
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Concept validation and solution exploration
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UX design for decision workflows
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Aligning design decisions with business and operational strategy
Process
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Semi-structured interviews
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Concept validation
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Workflow mapping
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Role based journey mapping
Problem
Freight decision-making relied on multiple disconnected systems, resulting in fragmented data and complex workflows.
The core challenge was enabling personalized logistics decisions at scale without increasing operational or cognitive burden.
Freight forwarding decisions are inherently complex:
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Multiple transport modes (air, sea, road, rail)
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Constantly changing constraints (cost, time, capacity, risk)
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Heavy reliance on manual coordination and expert judgment
Existing tools either:
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Over-automated decisions, reducing trust and flexibility, or
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Relied too heavily on manual processes, slowing operations and increasing errors
The goal was to ensure efficiency, and clarity
while enabling personalized logistics experiences
without overwhelming users or system performance
DISCOVERY
Mapping the decision landscape
Interviewed freight operators to analyze routing decisions, documenting shipment requests and API calls. Found that fragmented information impeded confident decision-making.​
Output
> workflows maps
> painpoints
> system interactions
DEFINITION
Identifying the system framework
Collaborated with PMs and engineers to define automated flaging. Improved rule-based logic was key to better decisions. Clarified request attributes and meanings for effective flagged request presentation.
Output
> logic framework
> define user roles
> decision taxanomy
VALIDATION
Tested and validated concepts
Validated low-fidelity concepts with freight operators to assess clarity and actionability of flags. Focused on operators' understanding in accepting or contesting recommendations, while enhancing presentation and data visibility to them.
Output
> usability findings
> trust criteria
> decision iterations
DESIGN
Role-based decision flows
Enhanced the freight decision flow system with API data aggregation and route suggestions. Created role-specific interfaces and delivered decision flows and reusable patterns for implementation.​
Output
> decision flows
> wireframes
> component specs
Solution and Impact
SaaS-based digital freight decision platform enhancement that
centralizes fragmented logistics data into a unified decision layer
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Unified fragmented logistics data into a single decision layer
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Redesigned workflows with role-based interfaces to reduce cognitive load
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Standardised templates and reusable specs for faster deployment
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Scalable personalization without overwhelming users or systems
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Increased user engagement by 30% on the B2B platform through redesign workflows
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Improved task efficiency by 25% via role-based interfaces tailored to distinct user needs
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Enabled 50% faster deployment cycles through standardised design templates and reusable specs
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Reduced cognitive load by abstracting multi-modal complexity into a unified decision layer
Key Takeaways
This project reinforced that personalization at scale is less about adding features and more about abstracting complexity through modular design. Centralization only improves decision-making when experiences are tailored to distinct user roles, and automation earns trust through transparency and human control. Ultimately, designing effective logistics platforms requires deep cross-functional collaboration to navigate the complexity of enterprise systems.