Table of Contents
It can be a three-step process if you have governance processes that consistently create perfect master data.
However, the five steps below will work for all scenarios, as it is likely that your existing systems (ERP, CRM, and Planning) may contain some incorrect master data.
Error-proofing at the point of entry
This is an absolute must. The more you can error-proof at the point of data entry, the fewer work/steps are needed in the later part of the process.
Intelligent Master Data Governance within existing NPI and Supply Chain business workflows
Many parts of Master Data depend on previous selections—certain fields or segments only make sense in specific contexts. With ZMDM, you can use simple or advanced JavaScript to dynamically determine those dependencies, reducing the chance of errors and making it easier for stakeholders to get it right the first time.
Validation before creation
This is the last line of defense. Simple to sophisticated validation steps can analyze Master Data for any inconsistencies before creating it in ERP, CRM, Planning, and other related systems.
End-to-end processes for Master Data Management
There is a general misconception that Master Data only encompasses the primary domain object (Material, Customer). However, for Master Data to be usable for business, the complete scope of the Master Data object can include many other elements and several steps to create those elements. Supporting this end-to-end process to create all these elements properly is essential for ensuring Perfect Master Data that is ready for Business.
Continuous Master Data error correction in mission-critical systems without disruption
In an ideal situation, you would not have to have this step at all. However, if you must, you need to do something like this.