The master data cleansing process is one of the most tedious and strenuous tasks in any ERP implementation. The importance of clean and accurate data cannot be underestimated, it is the food that feeds your business processes and bad data in equates to bad business results. Data extraction, cleansing, mapping, and validation are key to ensuring a successful migration, in this blog we’ll give you al the SAP data migration best practices you should consider as a business to have the highest chance of success when migrating data to SAP Business One.
What does master cleansing mean?
The meaning of data cleansing is to identify, organize and ultimate determine what master data the exists in your current system is necessary in your future system. Consider when you are moving from one house to another, you have to think about what is coming with, what is being donated and what is being thrown out. A very similar thought process should happen during an SAP data migration.
How to approach the Master Data Cleansing Process
It is important to approach the master data cleansing process in a methodical and manageable process. Let’s step through the SAP Data migration best practices below.
Determining what Master Data needs to be in SAP Business One
One of the first and most critical steps in data migration is deciding what data should be migrated. Not all items, customers and vendors data is necessary, and migrating excessive or outdated records can unnecessarily clutter your new ERP system and complicate implementation.
SAP Item Master Data Migration Strategy
- Inventory at Cutover: If an item will still be in inventory at the time of cutover, its item master data must be included to avoid discrepancies between SAP Business One’s opening balance and the legacy system’s ending balance.
- Items on Open Operational Documents: If open sales quotations, sales orders, purchase orders, or production orders are being migrated, every item that appears on those documents must be included in the migration.
- Industry-Specific Considerations:
- High SKU Turnover Industries (e.g., fashion, footwear, furniture): Focus on upcoming new SKUs rather than older items that have not sold in a long time.
- Low SKU Turnover Industries (e.g., industrial equipment, automotive parts, medical supplies): Include items sold in the past 2-5 years, depending on the product lifecycle.
- Seasonal Industries (e.g., agriculture, holiday products): Migrate at least two full seasonal cycles to ensure accurate forecasting and reporting.
SAP Customer & Vendor Master Data Migration Strategy
- Accounts Payable & Receivable: Any business partner that owes you money or you owe money must be included in the migration.
- Open Operational Documents: If open transactions (e.g., sales orders, purchase orders, contracts) are being migrated, the associated business partners must also be included.
- Ongoing Business Relationships: Consider open contracts and future engagements when deciding which remaining business partners should be migrated.
Data Mapping: Matching, Adding, and Reclassifying Data Points
When performing the master data cleansing process there are three key considerations; Firstly, matching legacy system fields with SAP’s equivalent fields, secondly adding new data points that were not previously tracked, and lastly reclassifying data structures to take advantage of SAP Business One’s enhanced functionality.
Matching Existing Master Data
Mapping existing fields from the legacy system to SAP Business One ensures consistency and accuracy.
- Ensure that customer, vendor, and item master data fields align correctly with SAP Business One fields by using cross referencing tables.
- Validate the format matches or needs to be cross references. numeric values, date formats, and classification codes match SAP’s expected formats.
Adding New Data Points
In SAP Business One, new fields may be introduced to support process improvements that were not available in the legacy system. These fields will be identified and you will be responsible for correctly populating the data
Example: Customer Account Statements
Suppose you want to automate the distribution of customer account statements—some customers should receive them via email, while others should access them through a portal. Your legacy system may not have tracked this information, but SAP Business One allows you to define and store this preference at the business partner level. As part of data mapping, you will need to classify each customer accordingly before migrating their data.
Reclassifying Master Data for Enhanced Functionality
Some data may need to be adjusted to take full advantage of SAP Business One’s functionalities. Data that was previously used for reporting may now have functional implications that will require the business to evaluate how they want to capture the data in SAP Business One.
Example: Item Groups
In your legacy system, item groups may have been used only for reporting, whereas in SAP Business One, they have functional purposes, such as defining default GL accounts or enabling automation.
You may need to expand or consolidate item groups during migration to take full advantage of the functionality.
This requires creating new item groups and mapping the item master data to the new groups in SAP Business One to align with the system’s improved classification capabilities.
Validate Data in a Test Database Before Going Live
Once the initial master data cleansing process has been completed the and the production database of SAP Business One is configured, a test database will be created where all master data will be imported for validation. You must ensure that the data came in correctly before uploading to production.
SAP Data Migration Best Practice – Data Validation
Validating imported data to ensure correctness before the final migration to production.
- Testing all business processes to confirm proper system functionality.
- Conducting User Acceptance Testing (UAT) to verify that master data aligns with operational needs before going live.
Important note: the more times data needs to imported, revised and re-imported the more costly your project becomes.
Structured and Repeatable Data Extraction from Legacy Systems
Migrating data to SAP Business One may require pulling information from a single legacy system or multiple systems. Since you might need to be pulling data from these systems several times over the course of the data migration task we recommend a structured and repeatable extraction process to maintaining data integrity and ensuring a seamless transition.
SAP Data Migration Best Practice – Data Extraction
- Develop queries or reports that can be run multiple times to ensure data consistency across extractions.
- Automated data extraction where possible to reduce manual errors.
- Engage current vendors if necessary to develop extraction reports and scripts if in-house expertise is limited.
Managing Delta Master Data Before Go-Live
The heavy lifting of data migration occurs during the realization phase of the implementation project which can span several months. After the initial data extraction, new master data may continue to be added to legacy systems and must be accounted for. Before go-live, it is important to identify and get these records—known as delta master data—into SAP Business One.
SAP Data Migration Best Practice – Delta Master Data
- Identify and track new master data added after the initial data extraction to ensure no critical records are missed.
- Establish a clear process for determining whether new records should be manually entered or imported, depending on the volume. A rule of thumb is 100 Records or less should be keyed in manually.
- Use timestamps in extraction queries to differentiate between previously migrated data and newly created records.
Final Thoughts
A successful SAP data migration requires a clear strategy, ongoing validation, and a commitment to maintaining data integrity throughout the project. These SAP data migration best practices will prepare you for success:
- Clearly define what data needs to be migrated to avoid unnecessary clutter and inconsistencies.
- Develop structured data mapping to align existing fields, introduce new required data, and reclassify where needed.
- Use a test database to validate migrated data and conduct User Acceptance Testing (UAT).
- Establish a repeatable and automated extraction process to maintain accuracy and facilitate multiple iterations.
- Plan for delta master data management to ensure that new records added to legacy systems during the project timeline are accounted for before go-live.
The master data cleansing process is one of the most critical and labor-intensive aspects of an ERP implementation. A well-executed strategy minimizes risks, reduces cost of the project, and positions businesses to fully leverage SAP Business One’s capabilities from day one.
