Listen now to uncover how AI is redefining maintenance operations and data management across the enterprise.
In this insightful episode, Kalpesh Shah is joined by master data expert Jose Bobrek to explore how AI is transforming maintenance data management in asset-intensive industries.
From automating data classification to enabling predictive maintenance and ensuring compliance at scale, this episode highlights how AI-powered solutions are addressing real-world challenges in operations and IT.
AI for Maintenance Data: Automate classification, validation, and enrichment for smarter, structured data.
Legacy to Modern: Seamlessly integrate AI into existing systems without disruption.
Predictive Maintenance: Use enriched data to reduce downtime and optimize asset lifecycle.
Governance at Scale: Enforce compliance and detect anomalies in real-time.
Global Scalability: Standardize data while respecting multilingual, regional nuances.
Driving Adoption: Align technology with culture and data ownership for lasting impact.
Enterprise Impact: Unlock value across procurement, finance, and sustainability.
AI in M&A & ERP: Harmonize data during SAP S/4HANA upgrades and mergers.
Data Governance & MDM Leaders
Maintenance & Reliability Managers
Asset & Equipment Owners
ERP & S/4HANA Program Leaders
Industrial IT & Transformation Executives
AI & Automation Experts in Manufacturing
Extract, Enrich & Sync Technical Data to ERP Systems
AI led enrichment tool for data harmonization
AI-powered parts and inventory management software
Oil and Gas organizations face huge unwanted costs in the form of losses, penalties and compensation due to industrial accidents, taking a sizable chunk of their revenues. One of the important reasons for failures and accidents is the breakdown of key industrial infrastructure arising from ineffective management of the material base and inefficiencies in the MRO supply chain that are highly critical for the production and maintenance cycles.
More and more organizations are now looking to establish Master Data Management (MDM) implementations in order to manage their assets through informed decision-making based on reliable data and ensure optimal industrial safety across the enterprise.
About the company:
This US based company is a global leader in providing essential mechanical components for both land and offshore drilling rigs, complete drilling and well servicing rigs, as well as a comprehensive range of tubular inspection, internal coatings, drill string equipment, lifting and handling gear, and downhole drilling tools. It also offers supply chain services through distribution centers strategically located near major drilling and production sites worldwide. With over 800 manufacturing, sales, and service centers globally and annual revenues exceeding $12 billion, the company delivers customer-focused solutions tailored to meet the energy industry’s quality, productivity, and environmental needs.
The company faced significant challenges with their master data.
• Lack of consistency and standards for the master data
• Incorrect, incomplete, unclassified and outdated attribute fields of master
data High volumes of data in multiple languages
• Multiple ERP and other legacy instances across the company
• Poorly structured material descriptions
• Lack of data governance and collaboration across cross-functional divisions and locations
Solution: Material Master Data Harmonization & Ongoing Maintenance
The company implemented Verdantis Material Harmonize to cleanse and enrich its historical material master data. Using AI-powered tools and the Verdantis Content Repository, the solution classified, standardized, and eliminated duplicate materials.
Once the data was harmonized, Verdantis Material Integrity was deployed for ongoing data governance. It ensured continuous data accuracy through real-time validation, AI-driven classification, and duplication prevention, maintaining high data quality across enterprise systems.
Key Actions Taken:
Results Achieved:
By integrating Material Harmonize & Material Integrity, the company achieved a scalable, AI-powered Master Data Management framework, ensuring long-term data consistency, efficiency, and compliance.
