During an enterprise resource planning (ERP) software project, the team should document ERP System data conversion requirements as part of the current state review and development of future state process. It is important for data as well as processes to be documented and understood.
The ERP Data Conversion Process
By reviewing both processes and data, the team can identify all databases that will need to be converted. The documentation of these databases becomes a requirement vendors need to address in the vendor evaluation phase.
Immediately upon commencement of an enterprise resource planning software implementation project, the project manager and the team, assisted by the vendor, need to map out a strategy to convert the databases to the new ERP system such as ERPNext. At this time, process owners need to take ownership of the successful version of the data.
The ERP System implementation plan should include tasks and responsibilities. Businesses usually employ their IT resources to prepare the data for conversion, because they know the source of the data and therefore are usually best suited to this task.
The process owner that works with IT will own the data and is responsible for ensuring the data is converted and cleansed for the new ERP system. ERP data conversion issues are often encountered in the testing process.
The project team needs to develop a conversion strategy for the following types of data:
- Static files – master data, like customer information
- Dynamic files – transaction data, like open purchase orders
- History – transaction history
Oftentimes process owners are assisted with the conversion, data cleansing, and data verification.
The Importance of ERP Software Data Conversion
Poor data conversion is the cause of many failed ERP System projects, and is one of the major reasons for an ERP project missing its on-time objective. Planning and execution in this phase are critical.
Supplement your IT staff in the following activities:
- ERP Software project management
- Data conversion planning
- Data mapping from the current system to the new system
- Data migration, both exporting and importing
- Managing data cleansing activities
- Quality assurance
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