Scaling Global Procurement: Driving 27% Higher Accuracy via ML & UX Optimization

This platform began as a backend microservice designed to solve a critical operational bottleneck: manual procurement friction. By productizing intelligent logic for commodity and GL classification, we optimized the intake funnel—drastically reducing month-end manual rework and enabling the system to scale across the global enterprise.

Context

The Internal Purchasing UI optimizes the procurement lifecycle by embedding real-time validations directly into the user’s natural workflow. By providing immediate feedback and reducing cognitive load, the platform establishes itself as the frictionless “paved road” for employees.

 

This high-integrity user experience drives organic internal adoption and trust—ensuring the tool remains the default starting point for every global purchase request and eliminating the need for expensive manual retraining or support overhead.

Project Info
Date:

2021-2024

Role:

Sr. Product Manager (Growth)

Technologies & Tools:

Machine Learning, Cloud Infrastructure, QuickSight

Activities and Responsibility:

  • Built a three-year roadmap for internal procurement software
  • Led rollout plan for 750K corporate employees globally
  • Managed cross-functional teams to ship 20+ features
  • Defined product requirements and prioritized user stories
  • Partnered with team of 11 engineers

Key Features:

  • Machine Learning-based Commodity Classification
  • Predictive Validation Heuristics
  • Contextual Feedback Loops
  • Optimized Stream Scheduling
  • Growth & Utilization Dashboard
Achievement:
  • Onboarded 10K+ internal employees within six months
  • Achieved 27% decrease in PO defects within one year post-launch
  • Successfully implemented QuickSight dashboard for utilization insights
  • Established comprehensive metrics tracking system

Launch Process:

User Research
  • Collected qualitative feedback
  • Assessed usability and functionality
  • Gathered overall platform experience data
Testing & Validation
  • Conducted A/B testing
  • Compared performance metrics
  • Monitored user engagement

Analytics & Growth

 

  • Tracked usage metrics
  • Measured engagement levels
  • Monitored performance outcomes
  • Generated utilization insights