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:

• Benefits and drawbacks of each product
• Overview & Background
• Product Options
• Evaluation
• Recommendation
• Business & Project Impacts

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

Summarise the recommendation being made for the reader, leaving the pro/con evaluation and exact decision-making process to the subsequent sections.

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

• Differences in the data structures of the two ECC systems will require careful consideration when merging or harmonizing data.
• The cleansing process must not interfere with ongoing operations or delay other critical project activities.

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

• Material descriptions must follow a standardized dictionary format to ensure consistency.
• Identified duplicates must be either merged or removed, with no duplicate records migrated to S/4HANA.
• Only validated, cleansed spare parts data will be migrated into the new S/4HANA system to ensure data integrity.

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: Sparetech - MRO Master Data Cleansing

Sparetech is a specialized MRO data cleansing tool that focuses on spare parts standardization and enrichment. It offers:

• Industry-specific taxonomies and classifications to enhance spare parts identification.
• AI-driven data enrichment to fill missing attributes.
• Integration with supplier databases for enhanced data accuracy.

Pros:

• Tailored for spare parts and MRO data, ensuring high-quality classification.
• Strong AI capabilities for automated data enrichment.

Cons:

• Limited integration with Syniti, requiring additional effort to align with the migration approach.

Option C: 

Option D: 

Describe the option in sufficient detail for a reader familiar with the subject matter to understand it properly

Evaluation

Outline why you selected a position. The best format could be a pro/con table (sample below), but is up to you as the author. You must consider complexity, feasibility, cost/effort to implement, but also ongoing operational impact and cost. You must consider the program principles and explain any deviations in detail. This is probably as important as the decision itself.

	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

Insert links and references to other documents which are relevant when trying to understand this decision and its implications. Other decisions are often impacted, so it's good to list them here with links. Attachments are also possible but dangerous as they are static documents and not updated by their authors.

Change log

Workflow history