With every ERP implementation, it is a topic of conversation: how do we deal with the data from the old system? And especially with all the data contamination that has occurred over time and the problems this has caused. Data is often entered inconsistently, is incomplete or appears multiple times in the system, contains errors and is out of date. This absolutely must not happen in the new ERP system. A good goal and the upcoming ERP implementation is also the perfect time to start doing this structurally better now. But what can you do to prevent data contamination over time? With good agreements and a structured approach, you can get - and keep - a grip on the data in your ERP system.
Performing data conversion well prepared
New ERP systems can often be set up to minimize incorrect data entry (and thus data contamination). But the rule still applies: 'garbage in, garbage out'! When transitioning to a new software package, start the data conversion in good time. Cleansing data is a time-consuming task, do not underestimate this. A timely start gives you the opportunity to map out where cleanup actions need to be performed to ensure that you start in the new system with a cleaned database.
Monitor master data quality
Master data is the basic data in your system that does not change much, if at all, and plays a role in various processes. Think of data about customers, suppliers and articles. Good management of master data increases the quality of the data and reduces the risk of errors within the various processes. Modern ERP packages support the single entry and central management of data. But in many companies, data is still stored in multiple systems and there are no clear procedures for managing data in one location and distribution from here to the other systems. Get the right procedures, processes and tools in place to improve the quality of master data and keep it at a high level in the future. The ERP package is the perfect choice when it comes to managing master data centrally.
Tight authorizations and clear agreements
It is also important to properly arrange authorizations in the system and make clear agreements internally. Put the responsibility for managing certain data where it belongs. In this way you limit incorrect data entry. For example, let one department mutate customer name and address data, but place responsibility for customer-level data that controls financial flows with another department. For uniform data entry, it is wise to use a set of good work instructions.
Getting things right and making clear agreements will get you a long way. But mistakes will still be made. Therefore, check regularly, using reports, for data contamination in the system. That enables you to make timely adjustments.
Peter Gerhardt is Senior Lead Consultant Logistics at Dysel and helps customers achieve maximum results with its business software.
