Data migration in ERP projects.
29 June

Data migration in ERP projects

Current studies such as the "ERP in practice 2020/2021" by Trovarit show that many companies do not consider the implementation effort of a ERP system often rate too low: This predominantly concerns data migration, which is described by ERP users as by far the most cited problem point in ERP implementation.


The migration of the data is what counts

Often the migration of data is 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 making sure 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 classified in such a way that it can be further evaluated with the new ERP system and a complete and accurate picture of the state of the company is obtained.

Data migration in global structures

Given the large number of different in terms of structure and format of data that can exist for corporate data, ensuring the quality of the data is not a trivial matter, especially in global business operations. Often, data sources are scattered across different data silos in a company - not only across regions, but sometimes even across continents. That is why it is worthwhile for companies to use special tools, especially for global data migration projects. This can be an automated mass check of business partner data for postal correctness or the automatic cleansing of data duplicates up 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:

Data integrity

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

Lack of knowledge in data processing

Insufficient knowledge or information about how the target system works among those responsible creates data sets that cannot be processed or can be processed insufficiently.
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 wrong selection of the responsible agents, who do not have the competence or authorisation to act, slow down the project.
Incorrect or insufficient user input already leads to the failure of the project during the preparation of the migration.

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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 that they have been tested before proceeding.

Clean up your data before migration

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

Stick to your strategy

Too many data managers make a plan and then abandon it when the process goes "too" smoothly or things get out of hand. 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 timetable for data migration should not be too tight. The more extensive your data stock is and the longer you have been using your previous ERP system, for example, the more likely it is that difficulties will arise during the data migration - be it due to an incorrect database or 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. DTW supports the automatic transfer of data into the system, specifically designed for the initial transfer. It is useful when you need to import large amounts of data, such as items and business partners.

To facilitate the import process into SAP Business One, the Data Transfer Workbench Templates for all ObjectsThese can be used to enter your own data and then import it into SAP Business One. The standard templates can be found in the folder where 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/auxiliary programmes
  • Different techniques for loading data

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