Frequently Asked Questions

Yes. The final cleansed data is delivered in ERP-ready formats, allowing direct upload using standard data load tools.

Yes. Cleansing is usually performed off-system or in parallel, ensuring no disruption to day-to-day business operations.

Yes. Cleansing can be phased by material type, plant, or criticality, allowing faster results where needed most.

Yes. Cleansing is most effective when combined with enrichment, classification, and governance for long-term data quality.

Yes. Correct and searchable material data enables faster spare identification, reducing downtime and emergency buying.

Yes. Engineering, maintenance, and operations teams can validate cleansed data to ensure technical correctness and usability.

Yes. Cleansing is a critical step in SAP ECC to S/4HANA migrations, ensuring simplified data models and improved system performance.

By implementing Material Master Governance and controlled code creation processes to prevent errors at the source.

Accuracy is ensured through multi-level validation, technical reviews, rule checks, peer reviews, and customer approvals before finalization.

Inconsistent descriptions are standardized using defined naming conventions, noun–modifier methodology, and controlled description structures, ensuring uniformity across the ERP.

Duplicates are identified using rule-based logic, description similarity checks, attribute matching, classification analysis, and usage comparison across plants and locations.

Poor-quality data is handled using automation, rule engines, enrichment, and expert validation, supported by clear assumptions and approvals.

Data is cleansed using central standards with plant-level visibility, ensuring consistency while respecting location-specific requirements.

Accurate data ensures correct MRP calculations, reliable forecasts, and meaningful analytics, improving operational decisions.

Cleansed data ensures traceability, consistency, and documentation, reducing audit findings and compliance risks.

Cleansing eliminates duplicates, excess stock, and incorrect purchasing, leading to lower inventory holding costs and optimized procurement.

Master data cleansing focuses on correcting errors, removing duplicates, and standardizing existing data, while enrichment adds missing technical details, attributes, specifications, and classifications. Cleansing improves accuracy; enrichment improves completeness.

Timelines depend on data volume and complexity:
Small datasets: a few weeks
Large or multi-plant datasets: several months

Master data cleansing is typically a project-based activity, but without governance controls it must be repeated. For long-term sustainability, cleansing should be followed by Material Master Governance and controlled code creation.

Yes. Clean and structured master data is the foundation for digital transformation, analytics, automation, and AI-driven initiatives.

Yes. Master data cleansing is fully compatible with leading ERP platforms including SAP and other ERP systems, following system-specific data models.

Yes. Cleansing before ERP implementation or migration ensures that only accurate and standardized data is moved, reducing system issues, rework, and post-go-live disruptions.

Customers receive cleansed ERP-ready data, documentation, and recommendations, along with options for governance implementation.

Obsolete and non-moving materials are identified, flagged, rationalized, or recommended for blocking or archiving, based on business and maintenance requirements.

Clean data improves stock accuracy, material visibility, and real-time inventory reporting, enabling better planning and control.

The methodology includes data assessment → duplicate identification → standardization → validation → ERP-ready delivery, executed in structured phases.

Common KPIs include duplicate reduction %, data completeness %, inventory accuracy improvement, and procurement efficiency gains.

Customer involvement is typically limited to requirement clarification, technical validation, and approvals, minimizing internal workload.

Master data cleansing can be applied to material master, vendor master, customer master, service master, BOMs, and asset-related data. The most common focus is material and MRO master data, where duplication and inconsistency directly impact inventory and procurement.

Organizations should start cleansing when they experience duplicate materials, excess inventory, incorrect planning, poor ERP search results, or audit issues. It is also highly recommended before ERP upgrades, migrations, or expansions.