Several companies have started recognizing data as a valuable asset which can help them improve their performance. This has made big data and analytics the key elements of any Enterprise Information Management program or EIM Program. Data governance presents its unique set of challenges, yet these obstacles can be surmounted through the adoption of six best practices that enterprises follow when implementing an EIM program.
Big Data has opened up vast possibilities for accessing economical and accurate data solutions but a system for monitoring the information management initiative is necessary. With data sets becoming increasingly large and diverse, data governance becomes essential for overseeing the initiative.
Many organizations still feel that having a state of the art system is enough and they do not require a data governance program. This can lead to data quality issues and defeat the purpose of the whole initiative. Data governance has its own challenges which can be overcome if the following best practices are adhered to by enterprises. Let’s take a look at them.
Ensuring Quality: A Deep Dive into Data Governance Techniques
1. Involve Executive Leadership In The Program
The governance initiative can be a huge change for any organization. Not everyone will be well-prepared or enthusiastic about the project. This can be a cause for resistance to the initiative.
This program will need substantial funds for creating the framework at the enterprise and acquiring technological solutions. The best way to solve these issues is to involve the executive leadership in the project.
The key decision makers from important business sections and the core functional areas must be identified. The benefits of the governance program must be explained to them in order to bring them on board.
Once the executive leadership is convinced of the value of the new project, it will become easier to implement the program. With the decision-makers behind the initiative, its chances of succeeding automatically improve.
The best way to solve these issues is to involve the executive leadership in the project. The key decision makers from important business sections and the core functional areas must be identified. The benefits of the governance program must be explained to them in order to bring them on board.
Once the executive leadership is convinced of the value of the new project, it will become easier to implement the program. With the decision-makers behind the initiative, its chances of succeeding automatically improve.
2. Assign Data Stewardship Roles in The Initial Phase
Even a well-thought-out data management strategy will fail in absence of a comprehensive monitoring program. Governance involves defining the policies and procedures which must be followed by the whole organization while handling information assets.
Data stewards are the individuals who ensure that the rules are followed every time a data element is used in any manner by users. Identification of the appropriate people for stewardship roles must be done in the initial phase of the project.
The stewards must be picked from all business sections of the company and must have professionals with considerable experience in working with chosen data elements.
Some corporations create new posts for the purpose while some assign the role as an additional responsibility to existing staff members. Every organization must adopt the way which suits them the most.
3. Define The Business Benefits Of The Program
The best data governance consulting experts are of the opinion that the utility of the program will not be understood by all staff members until it is linked to specific business benefits.
Every organization has its own reason for implementing an EIM program. While these business goals are known to the executive leadership but the workforce at the lower levels who actually work with data assets are unaware of them.
These people must be communicated the exact benefits of following the established rules and regulations. They must be told how errors can creep up in an element affect a process that they are conducting.
Communicating the clear advantages of the project like increased sales or better customer service will help in generating support for the initiative across the organization.
4. Start The Project On A Small Scale
One of the biggest errors that companies commit is rolling out the whole program across all departments. This can lead to issues which ultimately bog down the project. While it is sensible to keep the big picture in mind, the initiative must be implemented on a small scale in a step-wise manner.
This will help identify any problems which can then be resolved before the onset of the next phase. The new project is not just a technical change involving new tools but it is also a cultural change.
Working in phases will also help spot any resistance to the program. The implementation needs a nuanced approach which involves compromising on some issues to achieve the strategic goals.
5. Identify Metrics To Measure The Success Of The Program
It goes without saying that governance is extremely beneficial for enterprises but it is essential to quantify these advantages.
Just like EIM consulting experts help organizations set targets, the governance team must also identify the metrics which can be used to measure the success of the project.
Studying the business processes and the data elements related to them will be helpful in this purpose. Once the risks of these assets becoming inaccurate or unavailable can be defined in specific terms, it will be easier for the workforce to understand their importance. It will also be helpful in getting the executive leadership to support and fund the project.
6. Incentivize The Participation Of The Team
One greater challenges of running an efficient data governance initiative is to ensure adequate participation of all the team members constantly. As mentioned earlier, the stewardship roles can be assigned as additional duties to individuals. The added responsibility along with their operational roles can make stewards unenthusiastic about the program.
This will impact the data quality and in order to avoid this, the participation of the team members must be incentivized. Rewarding them for good performance will keep the stewards interested. Corporations can use monetary benefits or other forms of recognition as incentives to sustain the enthusiasm of the workforce.
Conclusion
An effective EIM program cannot be implemented without a comprehensive data governance strategy. Enterprises must engage experts to devise a scheme for monitoring the whole initiative for management and analysis of data assets.
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