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
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:

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:

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:

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.