Every data transaction these days is a business transaction. That’s why it’s critical to create a solid, adaptable, secure, adaptive, and error-free data governance framework.
Most CIOs are aware that improper data management can result in financial, legal, reputational, and other issues. That’s why any organization committed to data integrity and preservation should prioritize establishing a solid data governance policy, one that ensures compliance and security while also being manageable and accessible.
Unfortunately, since data governance practises and requirements are still evolving, IT leaders can easily fall into traps that can undermine even the best-intentioned planning efforts over time. IT leaders should keep a watch out for the following common mistakes that should be avoided at all costs to safeguard their organization from slipping into a trap that can render their data governance strategy ineffective.
Thinking of data governance as a technology project
Given the inherently fluid nature of data governance, policy creation should not be considered as a project that can be simply planned and released. A data governance policy that does not adapt to changing requirements will eventually collapse. Worse yet, such a policy can be perceived as an inconvenient stumbling block to getting work done, prompting teams to devise their own solutions.
Examining the volume and type of data gathered and stored is a crucial governance responsibility that is frequently overlooked. If used correctly, data can be extremely valuable, but the benefits are ultimately limited to the amount of data that companies can manage, leverage, and safeguard. It’s critical to thoroughly examine the benefits and drawbacks of data rather than simply capturing and retaining it by default.
Failing to communicate the overall business value of data governance
Data governance must be a company-wide effort. An effective data governance policy is value streams and business capabilities. They eventually feed into the larger organizational goals set by senior management.
It’s critical that data governance isn’t seen as a pet project of the IT department. This is critical not only for gaining and maintaining senior leadership buy-in and support, which hopefully extends beyond platitudes. It’s critical for the long-term success and scalability of the data governance program.
When a CIO fails to properly describe and demonstrate how data governance and related activities are helping achieve business outcomes and productivity gains, it is just good in theory but not in practise.
Not involving data owners in the data governance process
Not involving data owners in the process and securing their buy-in is a big data governance mistake. The company that manages and governs data for the enterprise does not necessarily own the data it oversees. Rather than working as data stewards, certain business units or departments are more likely to be the true owners. Finding the data owner can be difficult in many organizations since the owner often does not acknowledge itself as the ultimate owner of the data.
It’s critical to inform the ultimate data owners about the data governance program’s aims and benefits. Then get their buy-in and ask who else in their company can collaborate in the program.
The most difficult component of any data initiative – developing the data taxonomy and platform that will manage the data – needs buy-in. Almost always, this will necessitate adjustments to data structures and the cleansing of data that is out of date or does not conform to corporate taxonomy. The initiative will not be successful without the buy-in from data owners who have influence over the data sources.