¿Cómo se controlan los datos de su sistema ERP?

When I set out to govern my ERP system's data, I start by clearly defining my data standards. This essentially creates the rulebook for how data should be managed across the board. I specify how dates should be formatted, what naming conventions to follow, and what security measures are needed for sensitive data. I document these standards meticulously and share them with all key data stakeholders in my organization. This way, everyone knows the playbook and can execute their tasks with a high degree of accuracy and consistency. It's not just about maintaining quality; it's also about building a foundation of trust in the data we use every day.

Establish data management policies, Controls and procedures to ensure data security, accuracy and its compliance. This can include defining data ownership, Role based access to the system etc.

While defining the data requirement for ERP system, we must consider the following: 1. Identifying the data requirement like Supplier Data, Customer data etc. 2. We need to identify which data to be taken for ERP system e.g. Only Active Supplier Data, 1 Year Invoice transactions etc. 3. Data Templates - To ensure that the Source and Destination systems can share the data as per need 4) Any requirement of naming convention e.g. Supplier code to be standardized in ERP system etc. 5) Data Security requirement - How the data would be transferred from Source to Destination System 6) Data Archival and Purging Requirement in ERP system

That's absolutely correct - clearly defining roles is crucial for good ERP data governance. But it's also important to remember that these roles may need to evolve. For example, during a merger, the Data Governance Committee should quickly assess how these roles might change and which new departments should be involved. I've found that having a well-organized data governance office really helps. They make sure everyone is following the rules and provide a go-to place for solving any data issues. So, while structure is key, flexibility to adapt to changes can really make the difference in your data governance efforts.

Many organisations do not have a proper data lifecycle strategy, I see it in "customer data" for example. Customer records can become obsolete over time due to changes in customer information or behaviour, such as moving to a new address, changing phone number or email, or switching to a competitor. This can have a negative impact on the business. For example, customers may receive duplicate or irrelevant messages, offers or surveys from the company, or be excluded from loyalty programmes or promotions due to out-of-date information. Data lifecycle management can help organisations improve customer service, marketing, sales and analytics by providing a complete and reliable picture of data assets.

Project RACI should be created for Data Migration part to ensure that each and every person is aware about what activities to be performed. Moreover, create data migration detailed plan which should be linked with the overall program management plan.