Issue

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.

Recommendation

Background & Context

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:

• Define and standardize foundational data elements such as manufacturer name, part number, model number, short/long descriptions, and MRP type.
• Establish a uniform naming convention through a data dictionary to ensure consistent descriptions and classifications.
• Identify and eliminate duplicate spare parts records using advanced data matching and cleansing techniques.
• Ensure compliance with industry standards by linking parts to specifications, regulatory requirements, and maintenance best practices.
• Leverage an automated, scalable data cleansing solution to process large volumes of spare parts data efficiently before migration to S/4HANA.

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.

Assumptions

• Syniti is the official data migration partner for the S/4HANA implementation.

• The cleansing process must be completed before the S/4HANA migration cutover.

• The selected tool must support large-scale data cleansing while ensuring data integrity and governance.

• Business users will be engaged to validate and approve the cleaned data.
• Standardized naming conventions and classifications will be adopted.

Constraints

Impacts

• Improved accuracy and consistency in spare parts data.
• Enhanced efficiency in procurement, maintenance planning, and inventory management.
• Reduced data redundancy and improved system performance in S/4HANA.
• Minimized risk of data migration errors and inconsistencies.

Business Rules

Options considered

Option A: Syniti - Enterprise Data Matching

Syniti offers an enterprise-grade data matching and cleansing solution that integrates seamlessly with its data migration platform. It enables:

• Automated deduplication and harmonization of spare parts records.
• Advanced matching algorithms to detect duplicate and near-duplicate records.
• Seamless integration with SAP S/4HANA migration tools.
• Scalability and governance features to ensure ongoing data quality management.
• Centralized data repository for cleansing before migration.

Pros:

• Fully aligns with the migration strategy and reduces integration complexity.
• Strong governance framework ensures sustainable data quality management.
• Proven SAP compatibility and real-time cleansing during migration.

Cons:

• Higher licensing and implementation costs compared to standalone tools.
• Requires user training for effective utilization.

Option B: 

Option C: 

Option D: 

Evaluation

	Option A	Option B	Option C	Option D
Criterion 1	Pro Con	Pro Pro	Pro Con	Pro Con
Criterion 2	Pro Con	Con	Pro Pro	Con Con
Criterion 3	Pro	Con	Con	Pro

See also

Change log

Workflow history