Executive Summary

The mining sector faces increasing data challenges as it balances safety, automation, and sustainability goals with the complexity of global operations. Fragmented and ungoverned master data continues to stand as a barrier to achieving operational efficiency, procurement visibility, and digital transformation maturity.

PiLog’s AI-enabled Data Quality and Governance Suite(DQGS) is solving this problem by helping mining companies standardize and govern their service and asset data across multiple regions and systems. This use case demonstrates how a leading mining enterprise is now reaping the benefits of improved maintenance efficiency, reduced procurement spend, and increased equipment uptime — all built on a foundation of ISO-aligned, high-quality master data.

Industry Challenges in Mining

Before PiLog’s intervention, mining enterprises typically struggled with:

Fragmented data across systems and geographies

Poor asset utilization and reporting inaccuracies

Lack of standard taxonomy

Maintenance backlogs and spare part mismatches

Unstructured and inconsistent records

Inventory imbalances and delayed repairs

Compliance and safety data gaps

Risk of failing audits (e.g., ISO 14224)

Siloed governance

Insufficient visibility across multi-site operations

These challenges hindered real-time decision-making, increased operational risk, and limited the ability to modernize systems and processes at scale.

Customer Success Focus: Enterprise-wide Data Governance in Mining & Metals

One of the largest Mining & Metals conglomerates faced critical challenges with inconsistent material and service master data, unstructured BOMs, and fragmented asset records across multiple plants and operations. The lack of standardization led to duplicate entries, inaccurate inventory valuation, and inefficiencies in maintenance, procurement, and reliability management processes.

Project Goals
  • Cleanse and standardize Material Master, Service Master, Asset, and BOM data across all mining and smelting facilities
  • Establish a centralized, ISO-aligned Master Data Governance framework for all domains
  • Eliminate duplicate records and harmonize taxonomy for improved spend visibility and inventory optimization
  • Integrate validated data into SAP ERP for consistent, accurate reporting and analytics
  • Link material, service, and asset data to enable end-to-end traceability and reliability-focused maintenance planning
PiLog’s Deliverables

0K+

Material Records Standardized

0K+

Service Master Records Cleansed

0K+

Fixed Assets Managed

0K+

BOMs Linked

PiLog’s Solution: Implementing Master Data Governance

Using PiLog Data Quality and Governance Suite (DQGS), a comprehensive ISO-aligned Data Governance Framework was executed to transform material, service, and asset data into a governed, high-quality dataset:

  • Extracted, cleansed, and validated Service Master, and Asset data from multiple legacy systems
  • Standardized records using PiLog’s industry-specific taxonomy for mining and metals, ensuring ERP readiness
  • Linked materials, services, and BOMs to assets for complete lifecycle visibility and maintenance reliability
  • Integrated governed data into SAP ERP with full traceability, audit logs, and version control
  • Enabled standardized classification using global coding systems such as UNSPSC, HS, NATO, ISIC, and eCl@ss for enhanced interoperability and reporting

Measurable Results Delivered

Metric / KPI Impact Achieved Strategic Value
Human Capital Cost ↓ 0% Reduced manual effort through standardized processes
O&M and Inventory TCO ↓ 0% Optimized inventory control and maintenance planning
Total Asset Management (TAM) Cost ↓ 0% Improved reliability through predictive asset insights
Classification Accuracy ↑ 0% Accurate reporting and analytics across systems
SAP EAM Implementation Acceleration ↓ 0% deployment time Faster go-live with harmonized master data
Maintenance Planning Accuracy ↑ 0% Improved decision-making using linked BOMs

Standards Alignment and Recognition

Using PiLog Data Quality and Governance Suite (DQGS), a comprehensive ISO-aligned Data Governance Framework was executed to transform material, service, and asset data into a governed, high-quality dataset:

  • ISO 8000: Master Data Quality Standards
  • ISO 22745: Open Technical Dictionaries
  • ISO 29002: Exchange of Characteristics data
  • ISO 14224: Collection and Analysis of Reliability & Maintenance data
  • ISO 81346: Industrial System Structuring and Classification
  • ISO 55000: Asset Management

PiLog’s excellence in data governance was further evidenced by a 4.7/5 Gartner Peer Insights score, with 86% of users recommending the platform.

Conclusion

By partnering with PiLog, the mining and metals enterprise successfully transformed its material, service, and asset data ecosystem, enabling:

  • Enterprise-wide data visibility and governance across mining and smelting operations
  • Predictive maintenance and reliability-centered asset management
  • Seamless integration with SAP ERP for intelligent, analytics-driven decision-making
  • Standardization aligned with global ISO frameworks for compliance and interoperability
  • Reduction in operational costs, downtime, and maintenance inefficiencies

PiLog’s AI-enabled Data Quality and Governance Suite laid the foundation for a unified, intelligent, and future-ready digital mining enterprise — driving efficiency, sustainability, and continuous improvement across all operations.