Last Updated on May 26, 2022 by azamnie
Individuals and businesses are creating storing and using tons of data these days. This increased demand and regulations has led to initiatives like master data management, data migration, and steps are being taken to ensure data quality. All these initiative requires data governance to succeed and help enterprises get the best out of their data.
Unfortunately, most businesses are still struggling to ensure data governance due to various reasons such as cultural barriers or lack of involvement from C suite executives. That is why they fail to take advantage of the benefits such as improved operational efficiency, application effectiveness, and minimized risk that comes with data governance.
In this article, you will learn about seven steps your business can take to ensure effective data governance.
Table of Contents
What is Data Governance?
Data Governance Institute defines data governance as, “Data governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models, which describe who can take what actions with what information, and when, under what circumstances, using what methods.”
On the other hand, Wikipedia defines it as, “Data governance encompasses the people, processes, and information technology required to create consistent and proper handling of an organization’s data across the business enterprise. Goals may be defined at all levels of the enterprise and doing so may aid in acceptance of processes by those who will use them.”
1. Focus On Areas of Improvement
Instead of trying to solve all data-related issues all at once, you should start by target informational assets. Begin your data governance journey by implementing it in one department such as marketing or human resources and see how it works. If it delivers the results you are expecting it to, you should then expand it throughout your enterprise. Make sure to align your informational objectives with your business strategy. Think about the ways in which your data assets are supporting your current application architecture and how they are used and managed. This will help you to bring all the stakeholders on the same page and develop a consensus, which is critical for your data governance initiatives to succeed.
2. Availability of Information Assets
Information comes in all shapes and sizes and from various sources. It could be files stored on DDoS protected servers, data coming from ERP and CRM systems or data stored in legacy file structures or cloud. In order to govern all your data assets, you should first make them easily available and accessible. This can be a huge challenge as you first have to move some of that data to data mart for analysis purposes because you can make it available. Then there are instances when the data needs to be accessed in bulk or in real-time. All these challenges force businesses to look for data solutions that ensure the optimum availability of their data.
3. Define Rules and Responsibilities
After making the information available, it is time to decide on who will take which act on that data. Simply put, you should define rules, roles, and responsibilities at this stage. The role and responsibility you assign to a person should determine his or her data access. For instance, a marketing manager should only be able to access marketing and sales department data. Business professionals will have to work closely with the IT department to make it possible.
4. Ensure Integrity of Information
Once you have successfully assigned roles and responsibilities, it is time to ensure information asset integrity. There are four steps involved in ensuring data integrity.
- Data profiling
- Data parsing and standardization
- Data enrichment
- Data monitoring
In data profiling, business-defined KPIs are used as benchmarks for the analysis of data sets. Data is validated and corrected during parsing and standardization. Data enrichment allows you to include additional data. Monitoring the quality of data assets is also important, especially if you are using the data for trend analysis.
5. Establish an Accountability Infrastructure
Even after getting all the pieces in the right places, there is still a piece missing that could complete the data governance puzzle and that is accountability. Irrespective of how good your data management process might be, there are instances where it could not meet the data integrity requirements. That is where people come into play. You should create a structure where people are held accountable for information assets while providing them with the technology needed to ensure data integrity. Once you manage to establish such an infrastructure, there would be far fewer data-related issues as everyone is accountable for their actions.
6. Switch To Master Data Culture
Instead of implementing data governance by changing the organization’s culture, you should change your organization’s culture when your people, processes, and technology working cohesively to achieve a common goal. It is time to ditch the old transaction-based system and switch to a master data-based system. This will save you from vulnerabilities and compatibility issues associated with legacy systems.
The foundation of master data-based systems is laid on facts. These facts define core business entities, products, suppliers, partners, customers, employees, materials, bills, etc. Such information is frequently used and is stored in different applications. Master data-based culture moves master data from individual sources and makes it consistent across all systems. This keeps your data organized and in sync.
7. Develop Feedback Mechanism For Process Improvement
Last but certainly not least is developing a feedback mechanism that could help you bring future process improvements. This feedback mechanism should be integrated at every stage so you can make continuous improvements at each stage. Graphically represent the success and failures of the process to make it easier for stakeholders to see what is working and what is not. With an efficient feedback mechanism in place, you can easily identify and fix issues quickly and make future improvements at a rapid pace, helping your business succeed in the long run.
How does your business ensure data governance? Which steps do you for data governance? Share it with us in the comments section below.