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Sourcing Insights

An explainable fulfillment tracking system for enterprise retail supply chain.
 
UX/UI Case Study
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reduced
in avoidable long-distance sourcing

reduced
in manual order investigation time

faster
decision turnaround for sourcing exceptions

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Project Overview

As omnichannel volume increased, sourcing decisions became harder to explain, audit, and optimize. Operations teams struggled to understand why orders were fulfilled from distant locations despite closer inventory availability — leading to rising transportation costs and slower issue resolution.

I led the end-to-end UX strategy and design of Sourcing Insights, an investigation-first analytics platform that transformed opaque sourcing logic into actionable intelligence.

Impacts:

Business Problems

As online order volume increased, sourcing logic became more complex:

  • Orders were sometimes fulfilled from distant stores despite closer inventory availability

  • Transportation cost variance was rising

  • Operations teams lacked visibility into why decisions were made

  • Investigations required manual data pulls from multiple systems


Stakeholders frequently asked:
“Why did this order ship from Store A instead of Store B which is far away from the customer address?”
There was no single interface to answer that.

The result:

  • Increased fulfillment cost

  • Delayed delivery

  • High operational overhead

  • Frustration among supply chain leaders

Operations needed explainable sourcing decisions to reduce investigation load and cost variance.

Possible Solution

Build a dashboard where business teams can easily search by order ID or store to understand sourcing decisions, fulfillment costs, delivery times, and performance metrics.

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Figma, Illustrator, Photoshop, Surveys, Interviews, A/B Testing

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15 Months

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A team of 3 designers involved in the entire design process, including user research, wireframing, and usability testing.

My Role

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Design Thinking process

Reframed the problem. Evaluated Options. Validate through user testing

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Research

User Interview

Competitive analysis

Define

User personas

Empathy map

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Ideate
Prototype

Brain storming

Low fidelity design

Sketch

High fidelity design

Site Map

UI kit

Wireframe

Final prototyping

Usability testing

Feedbacks

Case study

  • Diagnose sourcing decisions quickly

  • Compare alternative sourcing scenarios

  • Understand cost and delivery tradeoffs.

  • Identify systemic inefficiencies.

  • Users didn’t need more KPIs. They needed decision traceability.

Core Needs:

Understand Users

Store Managers

E-commerce Operations Leaders

Transportation Manager

Network Optimization Analyst

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User Research

Pain Points

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Information Architecture

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Users could move from macro network trends to order-level diagnostics in under 3 steps, reducing cognitive switching:
Order-Level Diagnostics

  • Search by order ID

  • Full sourcing breakdown

  • Cost and SLA impact visualization

Store & Region Insights

  • Performance comparison

  • Fulfillment efficiency score

  • Exception frequency

Network Intelligence Dashboard

  • Aggregated cost trends

  • Delivery time distribution

  • Sourcing optimization opportunities


We intentionally designed progressive disclosure which reduced cognitive overload for non-technical stakeholders:
1. Summary first
2. Drill-down second
3. Technical depth last

Key Design Decisions & Tradeoffs :

  • The biggest tension was between engineering transparency and operational usability.

  • Stakeholders initially requested more KPI dashboards, but user behavior told a different story.

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User Flow

Order Resourcing Flows 1
Reason Insight Flows 1

Usability Testing

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Low-Fidelity Wireframes

NDA restrictions on visual exposure (hence low-fidelity representation in portfolio)

Business Impact

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