Data is the new oil to drive the digital transformation of your organization. And for your organizations to effectively use the data insights to drive value to topline and bottom-line impact, reduce risk and drive operational efficiencies, it relies on ensuring that the data is managed well using a robust data governance program.

For a large number of organizations, data fails to deliver promised value because they fail to realize the importance of effective data governance and do not put appropriate policies and processes in place.

Here are the top five reasons why data governance fails in an organization.

1. Treating the program as an IT project and not aligning with business leaders

   When data governance is seen as an IT initiative and not as a business initiative, then they fail. Data governance policies, processes that manage and monitor data catalog, data dictionary, business glossary, data quality, security, master data, reference data, etc. allow business users to use the data more effectively and efficiently.

   Therefore, a successful data governance program engages and involves the business users from the get-go and not as an after-thought. It should never really be an IT initiative.

2. Not driving it as an enterprise initiative with the formal governance body

   One of the objectives of the data governance program should be to break the data silos and consider data as an enterprise asset. Most data governance programs fail because they do not take an enterprise-wide approach and are silo'd to small groups.

   It is essential to engage all major business functions well in advance and ensure that they have visible and constant participation in the steering of the data governance program.

3. Not defining and agreeing on common business value-driven vision, strategy and roadmap

   As you start using data, it is easy to get bogged down by all the data related challenges that start popping up. These hurdles can be connected to data definition, quality, master data, or something else. Most data governance programs that do not take the business value end up solving challenges that not very many business users care or benefit from. These users soon start questioning the value that has been delivered by the governance program in comparison to the effort that has gone into the program.

   Therefore, you should consider putting together a vision, strategy, and roadmap based on the business requirements and something that they are aligned with. Also, consider putting together a prioritization approach to systematically solving these challenges based on the business value.

4. Not having an open/transparent platform to communicate the data governance processes and policies

   For a governance program to be effective and succeed, you need to have an open platform where the governance process, policies, and artifacts can be stored and then made available to all the stakeholders.

   These documents should be kept up-to-date. Easy access to all the program related documentation is vital to instill confidence in the stakeholders that this program and makes it an integral part of their day-to-day work.

5. Failure to come to a consensus
   Sometimes, data governance fails because the leadership finds it hards to agree. When putting together the data governance steering council, you need to put together a framework that allows that deadlocks can be resolved and taken care of promptly without frustrating rest of the team members.

Robust and formal data governance practice helps you get the most out of the rich data that credit unions and banks have about your members. Therefore, appropriate care must be taken in setting the program.