Data is now one of the most valuable assets for any organization. The term Data Governance emerged from the need to manage the collection and utilization of data in an efficient manner. Data Governance can be looked upon as building standard practices, processes and frameworks to facilitate the collection, identification, storage and usage of business information that an organization holds. The concept revolves around a simple objective – to make the right data available at the right time, to the right people, and in the right format.
Data governance program is an important step to establish control over information flow by putting up rules, policies, and procedures to safeguard the access and usage of data. Lots of organizations have tried to implement enterprise data governance practices, but only a handful have succeeded in reaping the rewards.
What’s the reason behind all these failures? In this article, we will take a look at the crucial mistakes that you must stay away from while implementing a data governance program for your organization.
1: Lack of a Governing Body to Oversee the Administration
Before going ahead with the implementation, organizations must ensure that a proper data governance framework is in place to control the entire life-cycle. The first step is to create a governing body with the right set of skilled resources to oversee that the data is being administered properly. All the employees working in the data governance project must be answerable to this governing body for any mishap that might happen. To have a proper control over the whole implementation process, it is something that you can’t afford to ignore.
2: You Ignore Data Quality
Data accuracy and consistency are two of the most important factors that can make or break a data governance initiative. You must have adequate measures in place to ensure the integrity of data. Important business decisions are made based on the available data, and if the data is of low quality, it will have a negative impact on the organization’s decision-making process. Having accurate and reliable data to draw insights from helps organizations make the right business decisions.
3: Failure to Embed Framework
Failure to embed the data governance framework is another crucial mistake that you must avoid at all costs. It is easy to document your data governance framework, draft roles and responsibilities, and create attractive process-maps, but implementation is the hardest part. The benefits of data governance will remain a distant dream if you are unable to effectively integrate your data governance framework into your organization. If the framework doesn’t become integral to your business, you are unlikely to achieve long-term goals.
4: Being Unprepared for Change
Data governance is a long-term process, which ultimately involves changing the way people manage data. However, people are usually quite reluctant to accommodate changes. During the course of implementation, there might arise the need to change the framework and processes for increasing efficiency. Resisting the change can be a recipe for a data disaster. Instead you must be prepared to accept the changing dynamics and act accordingly as per the organization’s long-term objectives.
5: You Are Just Looking to Satisfy a Regulator
When you are feeling the pressure to implement data governance just for the sake of satisfying a regulator, then it is very tempting for organizations to look for shortcuts to achieve the compliance requirements. The check-box approach to satisfy compliance norms is normally task-focused and completely ignores the long-term goals.
Right from the outset, you should think about how you can satisfy the regulation and also get some business benefits out of the activities. If you adopt good data governance practices, then you should be able to comply with any check-list or regulatory requirements without deviating from the original goal.
Final Words
Rome wasn’t built in a day. Same is the case with any data governance initiative. A successful data governance initiative will have various data-related issues to take care of — including, but not limited to, data integrity, accuracy, access restrictions and especially consumer privacy. You can’t solve all of an organization’s data problems in the initial phase of data governance. “Too big, too fast” approach is sure to invite troubles.
The key is to start small with your initiative while avoiding the mistakes discussed above. If you can stay clear of the obvious pitfalls, there is no reason why you can’t expand your initiative over time to meet the specific data governance needs of your organization.
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