Client Overview
A global manufacturing company specializing in industrial components, with operations spread across multiple plants worldwide, faced growing challenges in managing and leveraging data. The client produces thousands of SKUs across different product lines, works with a vast supplier base, and relies on complex global supply chain networks.
As the company scaled, its leaders recognized the need for a unified and intelligent data platform to gain operational visibility, ensure data governance, and accelerate decision-making across departments.
Problem Statement
The company lacked a single, trusted view of core business data (product, supplier, asset, production). This made it difficult for operations, maintenance, and supply chain teams to act quickly on issues, led to repeated manual reconciliations, increased compliance risk, and blocked efforts to deploy predictive analytics at scale.
Key Challenges
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Siloed and Fragmented Data
Product, supplier, and operational data were scattered across ERP, SCM, and legacy systems.
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Lack of Trustworthy Insights
Operations, maintenance, and supply chain teams often worked with outdated or inconsistent data.
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Compliance & Audit Risks
Meeting regulatory and industry standards was difficult due to the absence of clear data lineage.
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Delayed Decision-Making
Business intelligence reports took days or even weeks, slowing responsiveness to production or supply chain disruptions.
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Scalability Issues
Rapidly expanding SKUs and supplier networks made it difficult to sustain consistent data quality and governance.
Solution Implemented
The client implemented Semarchy Data Intelligence to create a governed, discoverable, and collaborative data foundation.
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Unified Data Catalog & Metadata Management: Centralized metadata for product, supplier, and operational data to provide a single source of truth.
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Self-Service Analytics with Governance: Enabled business users to build dashboards and run analyses while preserving data quality controls.
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Data Lineage & Impact Analysis: Delivered end-to-end traceability from dashboards back to sources for auditability.
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Collaborative Stewardship: Role-based access, tagging, and business term management to align IT, operations, and data stewards.
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AI-Ready Data Infrastructure: Clean, governed datasets prepared for predictive maintenance and production forecasting.
Business Impact
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68% Improvement in Operational Visibility
A unified data catalog provides a single source of truth for product, supplier, and production data, improving transparency.
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44% Reduction in Downtime
Predictive maintenance powered by clean, trusted data minimized unexpected equipment failures.
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75% Less Manual Reconciliation
Automated governance and lineage eliminated repetitive reconciliation between ERP and reporting systems.
Highlights
- 68% Improvement in Operational Visibility
- 44% Reduction in Downtime
- 75% Less Manual Reconciliation
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