Modernizing Supply Chain & Vendor Management for a Manufacturing Giant

Are you looking to enhance supply chain efficiency with AI vendor management. Factspan’s MDM solution streamlines operations, reduces costs, gives real-time insights and ensures compliance for enterprises.
Executive Summary

A multinational manufacturing corporation sought to harmonize data across its four core divisions and 50+ brands to improve supply chain efficiency. The goal was to enhance vendor management, reduce costs, and ensure regulatory compliance. Additionally, the company aimed to integrate AI-driven data quality enhancements to improve forecasting and anomaly detection.

To achieve this, Factspan deployed a decentralized yet unified MDM solution powered by Reltio MDM, enabling real-time data exchange, AI-driven vendor data enrichment, and improved decision- making. The solution streamlined supplier relationships, optimized shipping logistics, and ensured compliance with complex global regulations.

About the Client

The client is a privately held, multi-national manufacturing leader with a global vendor network spanning 22 countries. Supply chain inefficiencies and regulatory complexities drove the need for a modern data management approach.

Business Challenge

With 50+ brands across four divisions, the company faced high supply chain costs and fragmented vendor data across 40+ legacy ERP, CRM, and SCM systems. Operating in 22 countries with 3,500+ vendors, it struggled with data inconsistencies, compliance risks, and security gaps. Poor integration of SAP, Oracle, TMS, and WMS led to shipping inefficiencies, while shifting regulatory and carrier requirements forced costly manual reconciliations, increasing operational expenses.

Our Solution

Factspan developed a decentralized yet unified MDM framework leveraging Reltio MDM to improve supply chain visibility, vendor data quality, and regulatory compliance. The solution focused on:

  • AI-Driven Vendor Data Cleansing & Standardization
    Advanced AI-based entity resolution and anomaly detection were used to cleanse, match, and enrich vendor data across 3,500+ suppliers and 22 countries. This improved logistics forecasting, risk assessment, and cost optimization by ensuring accurate and up-to-date supplier profiles.
  • Federated Data Governance & Compliance Management
    A hybrid data governance model allowed divisions to maintain local compliance rules while adhering to global regulatory standards (GDPR, CCPA, ISO 27001). Role-based access controls and audit logging mechanisms ensured data security and compliance oversight across systems.
  • Microservices-Driven Integration & Real-Time Insights
    The solution established an API-driven architecture to enable seamless interoperability across SAP, Oracle, TMS, WMS, and supplier portals. This enhanced supply chain resilience, allowing the company to adapt to regulatory changes and carrier requirements in real time while reducing operational disruptions and manual reconciliation costs
Business Impact:
  • 25% reduction in supply chain disruptions through real-time vendor insights
  • 15% cost savings by optimizing shipping and vendor management
  • Improved compliance with global regulatory standards
  • Increased operational efficiency through AI- driven analytics
Featured content

The Future of Data Pipelines for Modern ...

Streamlining Product Data for an Automot...

Optimizing Customer Data Management for ...

Exploring Data Mesh – PoV...

Data governance consulting

Data Governance – Starter Kit...

Enhancing CX and Reducing OpEx for Truck...

banner image-logistics

AI-Driven Transformation in Trucking and...

Elevating Data Integration with ELTV Data Pipeline

Elevating Data Integration with ELTV Dat...

Evolving Data Stewardship Roles for Data...

Illuminating the Roads to Business Growt...

Download Case Study

    Work Email*

    Company Name*

    Scroll to Top