Do we need to have universal data management standards for data entities, to ensure a good quality?

Note- You may refer Data Management standards for Data Entities in our Data Quality Practice + Tool-Kit package for more details. In-brief, we have provided a tool to create the data management standards (domain value standards, data format standards, data model standards and business rules...) for data entities (like customer entity, invoice entity, product entity...). The question here is that is it must to have these standards for ensuring data quality?

For long-term health of data, universal data management standards are must. Data Quality is closely tied with other data management initiatives like data conversion, data integration, master data management and metadata. We are in the era, where the business is looking for speed. If you don't have common standards, the short-cuts are applied to meet the need of speed. These short-cuts lead to data quality issues. For example, having a common customer data standard will increase you productivity and speed to integrate with other systems and business partners. In-short, you can have short-term data-quality cannot have sustainable data-quality without enterprise standards around your data entities.

We think that the context of this question is that it takes time (sometimes years) to create the universal standards. Does it mean that one cannot have data quality assurance till that time? The answer is divided into two parts:

Yes, it is possible to have data quality assurance without the universal standards. Many organizations having good data quality have not had the data management standards for years. However, these organizations have been in a low change environment. For an organization going through many changes, acquisitions, mergers, major systems initiatives and business process re-engineering, it becomes painful (or nearly impossible) to maintain data quality without these standards
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It is not necessary to consider it a success, only when you have created data management standards for all entities. We should select the top 8-10 to ten entities and make the standards for them first, followed by the others. For example customer, product, location, sales channel could be the top priority entities.

More than the quantity, it’s the quality which matters. You might have established Data Management standards only for few entities. However, once created one needs to work on:

• Ensuring adherence to these standards
• Bringing the existing systems and processes in line with these standards.
• Effectively change managing these standards