Supply Chain Copilot:
AI-Powered Operations
A conceptual product design case study on transforming complicated supply chain software into an easy-to-use, smart assistant.
Project Type
Conceptual Enterprise Product Design
Timeline
2 Weeks
Domain
Supply Chain Planning & Enterprise SaaS.
My Role
Conceptualization
Initial Solution
From Manual Analysis to Real-Time Automated Insights Agent
Iteration 2:
After Incorporating Feedbacks
Problems
From a lengthy configuration process to quick and flexible prompting
Problems
Problems
Scattered Information
Data lives across dozens of different dashboards, spreadsheets, and databases.
Catching Problems Too Late
Planners often discover shortages or delays only after money has already been lost.
Supply Chain Planning & Enterprise SaaS.
Moving stock around or paying for emergency shipping is risky if you cannot predict how it will affect company profit margins.
Chatbots Don't Cut It
A standard text-only chatbot cannot display the complex tables, charts, and metrics enterprise planners need.
Goal: Create an AI workspace that helps planners spot critical supply risks early, test out solutions safely in a sandbox, and resolve issues in just a few clicks.
Iteration 2:
After Incorporating Feedbacks
I would be happy to dive deeper into my full design process, trade-offs, and thinking during the interview rounds.
