Leadership Experience
Data governance for mining operations
Improved data quality, reporting consistency, and operational planning across mining sites and business functions.
Representative engagement led by Thessia leadership in a prior consulting role before Thessia was formed.
Industry: Mining
Delivered for: Capstone Copper
Focus: Data governance and operational reporting
Impact: Better reporting consistency and stronger planning support
Project scope
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1
Enterprise governance framework
Scope included implementation of an enterprise data governance framework across multiple sites and business units to improve data quality, accountability, and reporting consistency.
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2
Ownership, stewardship, and standards
Scope included data ownership and stewardship models, standardized definitions, and validation rules across operational and corporate systems.
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3
Predictive planning enablement
Scope included standardizing equipment metadata and failure codes and improving alignment with maintenance and scheduling data to support more reliable planning.
Project context
The initiative focused on bringing fragmented operational data into a single governed environment to improve reporting consistency, support faster issue detection, and create a stronger foundation for operational analytics.
Problem
Operational and reporting data lacked consistent definitions, ownership, and validation, which reduced trust in reporting and made planning decisions harder across sites and functions.
Solution
The engagement introduced a governance-led operating model with clearer ownership, stewardship, standardized definitions, validation rules, and better alignment between operational data and maintenance planning processes.
Outcome
The resulting approach improved reporting consistency, strengthened decision support, and created a stronger foundation for planning, analytics, and future AI use cases.
Selected outcomes
- Improved reporting consistency through standardized definitions, ownership, and validation rules
- Strengthened trust in operational and planning data across sites and functions
- Supported better maintenance and scheduling decisions through more reliable governed data
- Created a stronger foundation for future analytics and AI use cases
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