With the tremendous growth in data comes a parallel increase in the importance of proper data governance. New data protection regulations, such as GDPR, make data governance a mandatory part of compliance.
Barriers to Effective Data Governance
Yet companies often struggle to implement data governance. This is largely because while creating and using data are core business functions, data governance isn’t. In fact, data governance projects typically cut across traditional departmental boundaries. As a result, the only way to really make sure data governance gets done properly is to treat it as a strategic project with the visible backing of senior managers.
Another reason data governance projects should be treated as strategic projects is today’s push for business transformation. The digital transformation effort increases the important of data quality and often requires restructuring and sharing data. But the deadline pressures of transformation work can drive an approach of “implement first, look back later”. This leads to poor results, as transformation projects that don’t ensure they work with meaningful data—only truly achievable by data governance projects that ensure data is maintained with consistency and integrity—are guaranteed to fail in the long term.
Business transformation projects are just one example of projects where data governance is as important success factor. Even everyday projects in the organization breakdown when data quality is neglected and bottlenecks and silos impede access. Treating data as a strategic asset and managing it through data governance can eliminate those barriers.
Implementing Strategic Data Governance
Along with support from top management, treating data governance as a strategic project requires prioritizing the many aspects of data governance. Without a clear focus, even teams that have management support can work furiously but accomplish little. Potential areas to focus on are:
- Data meaning. With this priority, the team focuses on ensuring that data is defined consistently across the business.
- Data quality. This priority emphasizes maintaining consistency and integrity to ensure data is correct.
- Data control. A data control project needs to tackle data from two directions: breaking down silos to expand access while limiting access to users who have a legitimate business need for seeing that data.
Data Governance Is An Ongoing Effort
The commitment to data governance as a strategic project needs to be consistent and ongoing, because data governance is an ongoing effort. Once the data governance team addresses their first priority, they need to be able to move on to address the other aspects of data governance as well. In addition, as new kinds of data are collected and new uses identified, the completed data governance work will need to be reviewed and updated.
Management should help the team complete their work by continuing to express support through memos, meetings, and other communications. Management should also support the team by providing appropriate funding and technology to support their work. Tools such as Enterprise Vault and Data Insight help organizations put their data governance strategies into practice. Contact dcVAST to learn more about the benefits of implementing an effective data governance strategy.
