What 10 Years of Industrial Data Has Taught Us About Prosol vs Traditional MDM
In the battle of Prosol vs Traditional MDM, the past decade of industrial data tells a clear story: companies that adopt AI-driven, industry-specific master data management outperform those that rely on legacy approaches in accuracy, speed, and cost savings.
If you’ve ever had a project delayed because your MDM team took weeks to clean a batch of material codes, you know the cost of poor data management. In asset-intensive industries, every incorrect material entry can mean delayed maintenance, stalled procurement, or even operational shutdowns.
Traditional MDM can’t keep up with the speed, complexity, and scale of modern industrial data.
That’s where Prosol, CODASOL’s AI-driven MDM platform, comes in. Its purpose-built to meet the challenges of industrial-scale data with speed, accuracy, and governance.
Why Traditional MDM Falls Short in Asset-Intensive Industries
Traditional MDM systems were built for static, structured datasets. But industrial operations generate high-volume, fast-changing, multi-format data every day:
- Equipment upgrades and replacements create new SKUs
- Vendor catalogs arrive in different formats and languages
- Engineering attributes change with design or market updates
- ERP integration demands speed and consistency
When faced with this complexity, traditional MDM struggles with:
- Manual Cleansing & Enrichment – Heavy reliance on human effort slows turnaround.
- Scalability Limits – Performance drops sharply at high volumes.
- Low Adaptability – Hard to integrate IoT, AI, and predictive maintenance data.
- Siloed Workflows – Disconnected from procurement and operations.
The impact is costly: procurement delays, unnecessary inventory purchases, compliance risks, and slower project execution.
How Prosol Redefines MDM
Prosol was designed for industries where delays cost millions. It blends AI algorithms, domain-specific templates, and ERP-ready workflows to deliver governance-grade data at industrial scale.
| Feature | Prosol | Traditional MDM |
|---|---|---|
| Data Cleansing | AI-assisted, with industry-specific rules | Manual or limited rule-based |
| Enrichment | Pre-built catalogs & attribute libraries | Manual research |
| Integration | Native ERP connectors (SAP, Oracle, Maximo) | Custom coding required |
| Processing Speed | 10x faster bulk uploads | Sequential batch processing |
| Scalability | Millions of records without slowdown | Performance degrades with volume |
| Governance | Real-time dashboards & alerts | Periodic manual audits |
What a Decade of Data Shows
Managing industrial master data for 10 years across oil & gas, utilities, EPCs, mining, manufacturing, and ports has shown us exactly where traditional MDM fails, and where Prosol delivers.
Over the last decade, Prosol has processed over 250 million industrial records worldwide. Here’s what that experience proves:
1. Accuracy That Eliminates Guesswork
- Prosol: Consistently achieves 98%+ attribute accuracy post-cleansing using AI-trained templates, multilingual catalogs, and ISO-compliant standards.
- Traditional MDM: Often stalls at 80–85% accuracy due to manual classification limits.
2. Speed That Keeps Projects Moving
- Prosol: Processes 500,000+ records in under 48 hours, including deduplication, attribute mapping, and ERP-ready formatting.
- Traditional MDM: Weeks or months for similar volumes.
3. Scalability Without Bottlenecks
- Prosol: Seamlessly onboarded 3 million vendor items during a mining sector merger without slowing processing.
- Traditional MDM: Requires workload splitting or extra staffing at scale.
4. Governance That’s Real-Time
- Prosol: Live dashboards monitor compliance, duplicates, and data health continuously.
- Traditional MDM: Relies on quarterly or annual audits.
5. ROI That’s Tangible
- Typical Prosol results:
- 20–35% procurement cost savings from duplicate elimination
- 15–25% inventory carrying cost reduction
- 2–4x faster ERP migrations
Ready to see these results in your own SAP environment?
Prosol is now available directly on the SAP Store, making it easier than ever to integrate with your existing ERP. Start your data transformation today with the only AI-powered MDM solution built for asset-intensive industries.
When to Switch from Traditional MDM to Prosol
Consider Prosol if your organization:
- Manages 50,000+ SKUs or asset records
- Operates in multiple geographies and ERP systems
- Suffers procurement delays from poor master data
- Must comply with ISO 8000, UNSPSC, or eCl@ss
- Wants to integrate IoT and predictive analytics into operations
Prosol Isn’t Just Faster; It’s Smarter
For small datasets, traditional MDM can work. But for complex, multi-location, asset-heavy operations, Prosol delivers:
- Speed – Hours, not weeks
- Accuracy – Enriched, compliant, governance-ready data
- Scalability – No performance trade-offs
- ROI – Measurable cost and time savings
If your data backlog is slowing down operations, discover how AI-driven MDM can transform your workflows.
How Prosol Future-Proofs Your Data Strategy
With Industry 4.0, data is your competitive edge. Prosol ensures your master data is ready for:
- Predictive maintenance
- Supplier risk management
- Digital twin creation
- Real-time asset monitoring
- Global compliance standards
By automating governance, Prosol keeps your enterprise agile, audit-ready, and innovation-driven.
FAQ: Prosol vs Traditional MDM
1. Is Prosol only for large enterprises?
No. While optimized for asset-intensive industries, its modular design fits mid-sized companies planning to scale.
2. How fast can Prosol be deployed?
Most deployments take 4–6 weeks, including ERP integration and template setup.
3. Does Prosol handle multilingual data?
Yes. It supports multi-language attribute enrichment for global teams.
4. Does Prosol only work with SAP?
No, it integrates with SAP, Oracle, Maximo, and other leading ERPs.
5. What ROI can I expect?
Most clients recover their investment within 6–12 months through cost savings and operational efficiencies.
Stop losing money to bad data and take control of your master data.
