How can you use industry standards for better data governance?

1 What are industry standards for data governance?

Industry standards are sets of best practices, guidelines, frameworks, or models that are widely accepted and followed by a specific industry or domain. Examples of such standards for data governance include the Data Management Body of Knowledge (DAMA-DMBOK) published by the Data Management Association, which covers 11 knowledge areas of data management, the International Organization for Standardization's (ISO 8000) standard for data quality, and the Data Capability Assessment Model (DCAM) created by the EDM Council, a framework that assesses the maturity and effectiveness of data management capabilities across eight dimensions. These industry standards are developed by experts, organizations, or associations that have authority and credibility in their fields.

2 Why use industry standards for data governance?

Using industry standards for data governance can bring several benefits to your organization, such as improving data quality and consistency, enhancing data security and compliance, facilitating data integration and interoperability, and increasing data value and trust. Clear and common definitions, rules, and metrics for data quality can help you avoid errors, inconsistencies, and duplication. Furthermore, industry standards establish the minimum requirements and best practices for data protection, privacy, and ethics to help you comply with regulations. Additionally, industry standards enable the exchange and sharing of data across different systems, platforms, and formats to improve accessibility and usability. Finally, demonstrating your commitment and professionalism in data management can increase the confidence of your users, customers, and stakeholders.

3 How to use industry standards for data governance?

Using industry standards for data governance is not a one-size-fits-all solution. You need to consider your organization's specific needs, goals, and context, and adapt the standards accordingly. To do this, you should assess your current data governance maturity and gaps with a self-assessment tool or third-party auditor. Then, select the relevant industry standards for your domain and scope, define your data governance strategy and roadmap, and implement and monitor your initiatives. When selecting the standards, research and compare the different options available for your industry or domain. For example, financial organizations may want to use the DCAM framework to measure their data management maturity, while manufacturing organizations may want to use the ISO 8000 standard to ensure their product data quality. After defining a roadmap that outlines the actions, resources, timelines, and milestones for implementing the standards, execute it and monitor your progress and performance. Use the industry standards as benchmarks and indicators to measure data quality, security, compliance, integration, and value. Finally, communicate and report your results to users, customers, and stakeholders.

4 What are the challenges of using industry standards for data governance?

Using industry standards for data governance can also pose some challenges, such as finding the right balance between standardization and customization, managing the complexity and cost of implementation, and keeping up with evolving industry standards and trends. You may need to customize or supplement the standards with your own policies, rules, or processes, but too much customization may compromise consistency and compatibility. Additionally, you may need to upgrade data systems, tools, or skills, or redesign data workflows, roles, or responsibilities. Furthermore, you must stay informed about the latest developments and revisions of the industry standards and adjust your data governance practices accordingly.

5 How to overcome the challenges of using industry standards for data governance?

To successfully use industry standards for data governance, you need to involve data users, customers, and stakeholders. Explain the benefits and rationale of the standards, and provide training and guidance on how to use them. Additionally, adopt an agile and iterative approach to data governance by starting with small pilots and testing the standards in your context. Leverage external resources and expertise for advice, assistance, or collaboration from industry associations, consultants, or peers who have experience with the standards. This will help you learn from their best practices and apply them to your own data governance situation.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?