Data migration in ERP projects

Current studies such as the study „ERP in practice 2020/2021“von Trovarit evidence that many companies underestimate the implementation effort of ERP system are often underestimated: This mainly concerns data migration, which ERP users describe as by far the most frequently cited problem in ERP implementation.

The migration of the data is what counts

The migration of data is often the basis for measuring the success or failure of an ERP implementation. One of the main tasks of an ERP system is data management. Correct and effective data migration is therefore essential for the success of a project. If this initial requirement is not met, the system cannot be expected to deliver accurate and adequate data.

Data migration is about ensuring that the transferred data has been cleansed and is also error-free and complete. It is also about checking that the information is not duplicated or redundant. The data must be categorised in such a way that it can be further analysed with the new ERP system and a complete and precise picture of the state of the company is obtained.

Data migration in global structures

Given the wide variety in structure and format of data that can exist for corporate data, ensuring the quality of the data is no trivial matter, especially for global business operations. Data sources are often scattered across different data silos within a company - not only across regions, but sometimes even across continents. It is therefore worthwhile for companies to use specialised tools, especially for global data migration projects. This can be an automated mass check of business partner data for postal accuracy or the automatic cleansing of data duplicates through to the standardised completion of data records

The challenge of data migration

Every company has its own unique starting point and structure, but the following challenges are often encountered during a data migration:

Integrity of the data

Examining the data too superficially leads to misjudgements and hasty decisions. If the analysis is based on too small a selection of data sets, it is likely that the wrong conclusions will be drawn when dealing with large and complex data blocks.

Lack of knowledge in data processing

Insufficient knowledge or information about how the target system works on the part of those responsible generates data records that cannot be processed or can only be processed inadequately.
No sufficient knowledge or information about the functioning of the source systems.

Challenges related to roles and systems

Limited access to the target system due to Authorisations or incorrect configuration delays or hinders processing. The project is slowed down by the incorrect selection of the responsible processors who do not have the competence or authorisation to act.
Incorrect or insufficient user input leads to the failure of the project even before the migration is prepared.

Best practices for data migration

Regardless of which implementation method you use, you should follow some best practices:

Back up data

Back up the data before execution. If something goes wrong during implementation, you cannot afford to lose data. Make sure that Backup-resources are available and have been tested before proceeding.

Clean up your data before migration

Every move to a new home is a welcome opportunity to tidy up. Only what is really needed should be taken with you. The situation is similar with a data migration. It is the ideal time to rid the data of legacy data, errors and duplicates. This is because problems that were already present in the source data can have a greater impact when it is transferred to a new, more complex system.

Stick to your strategy

Too many data managers create a plan and then abandon it when the process is „too“ smooth or things go off the rails. The migration process can be complicated and sometimes even frustrating, so prepare for it and stick to the plan.

Test, test, test.

Test the data migration during the planning and design phase and throughout the implementation and maintenance phase to ensure that you achieve the desired result.

Allow sufficient time for data migration

True to the motto „Good things come to those who wait“, the schedule for data migration should not be too tight. The more extensive your data stock is and the longer you have been using, for example, your previous ERP system, the more likely it is that difficulties will arise during data migration – be it due to a faulty database or due to unexpected technical problems.

Data migration with SAP Business One

SAP Business One Data Transfer Workbench (DTW) is a migration tool that allows you to import data from a CSV file into SAP Business One. The DTW supports the automatic transfer of data into the system, specially designed for the initial transfer. It is useful when you need to import large amounts of data, such as articles and business partners.

To facilitate the import process in SAP Business One, the Data Transfer Workbench Templates for all Objectswhich you can use to enter your own data and then import it into SAP Business One. The standard templates can be found in the folder in which the SAP B1 DTW is installed. The folder hierarchy of the templates corresponds to the structure of the SAP Business One main menu.

The functions of DTW are composed of:

Management & organisation of data transfer projects
Tools for analysing the required SAP structures
Integration of standard data transfer programmes
Registration & integration of your own data transfer/assistance programmes
Different techniques for loading data

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