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Syensqo currently operates two separate SAP ECC systems, each housing material master data for spare parts. Over time these systems have accumulated inconsistencies, duplicate records and non-standardized data. These inconsistencies create challenges in spare parts identification, procurement and maintenance planning.
As Syensqo prepares to transition to a single S/4HANA system, it is critical to cleanse and harmonize spare parts data to prevent these inefficiencies from being carried forward. Without a structured cleansing approach issues such as duplicate materials, incomplete records and inconsistent descriptions will persist, resulting in difficulties in inventory management, inaccurate procurement planning and potential operational disruptions post-migration.
Key areas covered in this document include:
A decision is required on how to systematically cleanse and harmonize the spare parts data, ensuring accuracy, consistency and usability in the new S/4HANA environment while minimizing operational disruptions during the migration.
Given the complexity and importance of ensuring accurate and consistent spare parts data as Syensqo transitions to a single SAP S/4HANA platform a two-stage approach is recommended for material data cleansing and optimization. This approach will leverage both Syniti - Enterprise Data Matching and Sphera - MRO Data Quality Optimization Services to ensure data quality, streamline integration and optimize critical spare parts for better operational efficiency.
The first stage focuses on addressing the fundamental issues of duplicate records and data inconsistencies. The goal is to use Syniti - Enterprise Data Matching to perform large-scale deduplication and data cleansing across all material records. Syniti’s AI-driven data matching tools will help identify and eliminate duplicate entries, standardize basic data elements and ensure the overall consistency of spare parts data. Additionally, the tool can be repurposed for cleansing other master data objects (e.g. Vendors) beyond just materials.
Once the initial cleansing is complete, Stage 2 focuses on optimizing critical and high-value spare parts data. For these materials, it is important to go beyond basic cleansing to ensure that the data is standardized, enriched and optimized to support operational and compliance needs. This stage will leverage Sphera’s MRO Data Quality Optimization Services, which specialize in improving data quality for Maintenance, Repair, and Operations (MRO) items.
Spare parts data is critical for effective asset management, procurement and maintenance planning. The transition to S/4HANA presents an opportunity to cleanse, standardize and harmonize spare parts data to enhance operational efficiency. The chosen tool must facilitate data validation, deduplication and enrichment while integrating seamlessly with the data migration strategy led by Syniti.
To address these challenges, the project aims to:
By conducting a thorough data cleansing exercise prior to migration, Syensqo can eliminate these inefficiencies and create a more streamlined, accurate, and efficient spare parts management system within S/4HANA. This will ultimately enable smoother procurement processes, better maintenance planning and more accurate inventory tracking contributing to greater overall operational efficiency.
Syniti is the official data migration partner for the S/4HANA implementation.
The selected tool must support large-scale data cleansing while ensuring data integrity and governance.
Option A: Syniti - Enterprise Data Matching
Syniti’s Enterprise Data Matching tool provides advanced data matching, cleansing and migration capabilities. As Syniti is already the migration partner for the project, leveraging their data quality tools ensures alignment and efficiency.
Features & Benefits:
AI-driven data matching for duplicates and inconsistencies.
Seamless integration with SAP
Supports large-scale data cleansing for global operations.
Alignment with the project’s migration strategy, reducing implementation complexity.
Limitations:
May involve additional licensing costs depending on scope.
Sparetech specializes in MRO (Maintenance, Repair and Operations) data quality improvement, focusing on spare parts classification, taxonomy and cleansing.
Features & Benefits:
Industry-specific MRO data cleansing and classification.
AI-based recommendations for standardization.
Automated enrichment of missing attributes using external databases.
Supports multiple languages for global deployments.
Limitations:
Sphera provides a service-based approach to MRO data optimization, focusing on compliance, standardization and cataloging.
Features & Benefits:
Expert-led data cleansing and classification services.
Regulatory compliance support for industry standards.
Ensures alignment with corporate MRO strategies.
Limitations:
Higher cost due to service-based pricing model.
May require additional validation when integrating into SAP S/4HANA.
| Criterion | Syniti - Enterprise Data Matching | Sparetech - MRO Master Data Cleansing | Sphera - MRO Data Quality Optimization |
|---|---|---|---|
| Data Cleansing Approach | Deduplication, data consistency, and cleansing of material master data | Industry-specific MRO data cleansing, classification, and enrichment | Standardization, enrichment and optimization of critical, high-value and high-usage materials |
| Scalability | PRO: Highly scalable for large volumes of material data. Suitable for large-scale deduplication of vast material data | CON: Limited scalability for large-scale projects. Focuses on MRO-specific materials, particularly for industry standardization and classification | CON: Less scalable for large datasets compared to automated solutions like Syniti |
| Data Integrity | CON: Ensures only basic data integrity by removing duplicates and ensuring consistency | PRO: Improves data integrity by cleansing and classifying MRO materials using industry standards | PRO: Ensures enriched, high-quality data with complete attributes and regulatory compliance |
| Integration with SAP | PRO: Seamless integration with SAP S/4HANA, ready for migration | CON: Limited SAP integration, additional effort required for migration | PRO: Can integrate post-enrichment, but requires validation for seamless integration |
| Data Enrichment | CON: Limited enrichment, mainly focused on deduplication and consistency | PRO: Provides some enrichment via external databases but limited compared to Sphera’s service | PRO: Comprehensive enrichment using external databases, AI-driven suggestions, and regulatory updates |
| Customization | PRO: | CON: Requires some customization for aligning with S/4HANA and migration | CON: Requires high-level customization for critical materials and regulatory compliance |
| Cost for Large Scale Projects | |||
The two-stage approach leveraging Syniti - Enterprise Data Matching (Stage 1) for deduplication and Sphera - MRO Data Quality Optimization Services (Stage 2) for enrichment and standardization provides a comprehensive solution for Syensqo’s material spare parts data cleansing and optimization.
Rationale:
Key Benefits:
Rationale for Stage 2:
Key Benefits of Stage 2:
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