Data Governance Methodologies

After implementing their ERP projects, many companies struggle to maintain their master data with sufficient accuracy and completeness to make the ERP system work properly. As companies add new materials, customers and vendors, critical master data elements may not be updated or they may be updated incorrectly. This incorrect or missing master data results in business transaction interruptions – the inability to create production entries, the inability to ship products, and the inability to invoice customers. Such interruptions are expensive, time-consuming and negatively impact your ability to achieve the full return on your ERP investment. In some cases master data processing errors can place a company at risk for failure to meet regulatory compliance standards.

It is critical to evaluate a correct process for the ongoing creation and maintenance of master data through Data Governance Methodologies:

Passive Data Governance – a self-guided, technology-supported method to help business users identify errors in data quality, with a facility to promote user corrections and reporting on data quality. Working in a reactive mode, the method allows uninterrupted data entry, with error reporting back to the data owner for correction.

Directed Data Governance - applying controlled sequences to data creation and maintenance through web-based applications that control and direct data management tasks.

Active Data Governance – a technology-supported method that allows data interactions to occur, while providing a firewall for master data by collecting the data for validation prior to posting to systems. By inserting a validation step, the business can collaboratively assess and implement corporate data standards on new or changed data without impeding data entry.

Learn why Passive and Active Data Governance are not mutually exclusive.

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