Figure 7 – Representative MDM Workflow: Topographic File Governance from Field Survey to Official File Release. Swimlane diagram showing actor responsibilities, validation gates, multidisciplinary approval steps, and BI dashboard update triggers in Deswik MDM at Aripuanã. 5. RESULTS AND DISCUSSION The implementation of Deswik MDM at Aripuanã yielded measurable improvements in data governance, process efficiency, and operational visibility. Quantitative metrics, collected over a six-month post-implementation period (2025-Q2 to 2025-Q3) and compared against a baseline (2024-Q4 to 2025-Q1), demonstrate the platform's impact on key performance areas. Data Governance and Safety Assurance. We enforced a single source of truth, eliminating the proliferation of parallel file versions circulating through informal channels. This addressed a critical vulnerability: analyses conducted on outdated designs could propagate hazardous assumptions into field execution. Post-implementation, mandatory downloads from Deswik MDM and multidisciplinary validation steps for field releases mitigated this risk. Standardization improved team alignment, reducing inconsistencies in naming conventions and data structures across disciplines. Workflow Performance and Cycle Time Reductions. Three representative workflows illustrate significant improvements: (i) linear advance measurement in horizontal development headings decreased from 4–6 hours (N=35) to 10–15 minutes (N=42), a ~90% reduction; (ii) stoping/production reconciliation shifted from 2–3 days (N=28) to 4–6 hours (N=31), roughly 80% improvement; and (iii) drilled reserves control evolved from low-auditability spreadsheet tracking to a governed process with spatial visualization, reducing reconciliation errors by ~60% (N=25 assessments). These reductions resulted from automated data ingestion, validation rules, and elimination of manual reconciliations, freeing technical teams for higher-value tasks. MDM as Foundational Enabler for Short Interval Control. We position the governance architecture established through MDM as the foundational data layer required for implementing Short Interval Control (SIC)—a structured operational management system executed at sub-shift intervals. SIC effectiveness is directly contingent on data quality, accessibility, and timeliness; without a governed, centralized platform, SIC cycles are undermined by fragmentation. The GMG (2019) SIC maturity framework defines six levels. Our MDM platform at Aripuanã—enforcing single source of truth, automating validation, and enabling BI-driven monitoring—positions the operation at SIC Level 3–4, a necessary precondition for advancing to Level 5 (integrated closedloop control). The three workflows demonstrating the most significant gains (linear advance,
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