April 23, 2025Machine Learning

Data & Business Analytics Project Showcase

📊 Last month, I had the opportunity to present our SLB project at the Data and Business Analytics (DBA) Project Showcase alongside an incredible team and in front of industry leaders and partner company managers.

Project Overview

Our project focused on unsupervised classification of 1.2 million+ multilingual material descriptions across SLB's global operations using cutting-edge machine learning techniques:

🤖 Technical Approach

BERT Embeddings: Leveraged state-of-the-art transformer models for semantic understanding of multilingual text
K-Means Clustering: Applied unsupervised learning to identify natural groupings in material descriptions
Multilingual Processing: Handled diverse languages across SLB's global operations
Scalable Architecture: Designed to process millions of material descriptions efficiently

🎯 Business Impact

Procurement-Relevant Categories: Identified meaningful material classifications to support procurement decisions
Regional Usage Patterns: Discovered geographical trends in material usage across different operations
Cost Optimization: Enabled strategic procurement decisions through better categorization
Inventory Efficiency: Improved inventory management through enhanced material classification
Supplier Consolidation: Supported supplier strategy optimization through usage pattern analysis

Industry Recognition

It was an enriching experience to share our work with professionals from top partner firms and gain valuable feedback on applying AI in real-world business operations. The presentation provided insights into:

Practical AI Implementation: How advanced NLP techniques can solve real business challenges
Scalability Considerations: Managing large-scale data processing in enterprise environments
Cross-functional Collaboration: Working with domain experts to translate technical solutions into business value
Global Operations: Understanding the complexities of multinational corporate data

Event Gallery

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Key Learnings

Technical Insights

Feature Engineering: The importance of domain-specific preprocessing for multilingual text
Clustering Validation: Techniques for validating unsupervised learning results in business contexts
Performance Optimization: Strategies for handling large-scale text processing efficiently

Business Integration

Stakeholder Communication: Translating complex ML concepts into actionable business insights
Change Management: Understanding how AI solutions integrate with existing procurement workflows
ROI Measurement: Quantifying the business impact of machine learning initiatives

Acknowledgments

Grateful to SLB and SUTD for this incredible opportunity! Special thanks to:

Our amazing team for their dedication and collaborative spirit
Industry professionals who provided valuable feedback and insights
Academic supervisors who guided our technical approach
Event organizers for creating this platform for knowledge sharing

Looking Forward

This experience reinforced the immense potential of applying advanced NLP and machine learning techniques to solve real-world business challenges. The intersection of academic research and industry application continues to drive innovation in data science and analytics.

Excited to continue exploring the frontiers of AI in business applications! 🚀