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Beyond Blue Ai assisted Sourcing Simulator

Sourcing Simulator

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Beyond Blue: AI-assisted Sourcing Simulator

Beyond Blue: AI-assisted Sourcing Simulator

Beyond Blue: AI-assisted Sourcing Simulator

Supply chain teams often need to make high-stakes sourcing decisions when conditions change suddenly. A port closure, supplier disruption, capacity shortage, or geopolitical event can force teams to evaluate dozens of alternatives across cost, lead time, capacity, risk, and geography.

I designed an AI-assisted sourcing simulator that helps teams model disruptions, explore alternative sourcing strategies, and understand the trade-offs before making a decision.

Supply chain teams often need to make high-stakes sourcing decisions when conditions change suddenly. A port closure, supplier disruption, capacity shortage, or geopolitical event can force teams to evaluate dozens of alternatives across cost, lead time, capacity, risk, and geography.

I designed an AI-assisted sourcing simulator that helps teams model disruptions, explore alternative sourcing strategies, and understand the trade-offs before making a decision.

Role

Lead UX designer

Team

Product, Data scientist, Engineering, Design

Role

Lead UX designer

Team

Product, Data scientist, Engineering, Design

The Problem

A disruption rarely affects just one part of the supply chain. A port closure can change supplier availability, transportation routes, lead times, cost, and capacity at the same time.

For a sourcing team, the real questions become


  • What will be affected?

  • What alternatives do we have?

  • Which option gives us the best balance of cost, capacity, lead time, and risk?

  • What happens if we change one constraint?

A disruption rarely affects just one part of the supply chain. A port closure can change supplier availability, transportation routes, lead times, cost, and capacity at the same time.

For a sourcing team, the real questions become


  • What will be affected?

  • What alternatives do we have?

  • Which option gives us the best balance of cost, capacity, lead time, and risk?

  • What happens if we change one constraint?

Key Design Decisions

Make the scenario the starting point

Users think in terms of business events such as a port closure or supplier disruption, not databases.


Show trade-offs

A recommendation is only useful when the user understands what they gain and what they sacrifice.


Keep reasoning visible

AI-generated strategies need enough context for users to validate them.


Progressive complexity

Reveals more detail as the user moves deeper into the decision, rather than overwhelming them at the beginning.

Make the scenario the starting point

Users think in terms of business events such as a port closure or supplier disruption, not databases.


Show trade-offs

A recommendation is only useful when the user understands what they gain and what they sacrifice.


Keep reasoning visible

AI-generated strategies need enough context for users to validate them.


Progressive complexity

Reveals more detail as the user moves deeper into the decision, rather than overwhelming them at the beginning.

Our Users

Procurement Manager

Owns sourcing decisions and needs to quickly compare suppliers, costs, capacity, and risk when disruptions occur.

Owns sourcing decisions and needs to quickly compare suppliers, costs, capacity, and risk when disruptions occur.

Supply Chain Analyst

Analyses network data and scenarios, helping identify impacted routes and evaluate alternative sourcing strategies.

Analyses network data and scenarios, helping identify impacted routes and evaluate alternative sourcing strategies.

Hi- Fi Mockups

View interactive prototype

Solution's Outcome

The project transforms a traditionally manual scenario-planning process into a visual, interactive decision-support experience. Instead of asking teams to work through disconnected data sources and spreadsheets, the simulator gives them a structured path


The bigger design opportunity is not simply using AI to automate sourcing analysis. It is using AI to make complex decisions easier to explore, understand, and validate

Ai Native Design Journey

01

Empathise

User research, interviews & competitor analysis

02

Define

Problem framing, personas & user journeys

03

Ideate

Feature prioritization & information architecture

04

Design

Wireframes, high-fidelity UI & design system

05

Prototype

Making the design interactive

AI was integrated throughout the design process as a thinking and exploration partner, not as a replacement for design decisions. I used it to synthesize research, identify patterns across user and competitor findings, explore problem scenarios, generate and challenge early concepts, and quickly test different information architectures and workflows. During the design phase, AI helped accelerate wireframing, content exploration, UI directions, and rapid iterations, while I stayed responsible for deciding what was relevant, validating assumptions, refining the experience, and shaping the final interaction and visual design. This allowed me to spend more time on the harder parts of the problem: making complex supply-chain decisions understandable, comparable, and actionable.

“This simulator turns supply chain uncertainty into clear, comparable choices, helping teams respond faster and make decisions with confidence.”

— Pete Stubub, Product Manager

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