Data isn’t valuable if it isn’t precise and reliable. In order to yield the long-term benefits of a successful data governance program, follow the best practices outlined below.
What is Data Governance?
Data governance is a set of policies, processes, and procedures embedded into the daily functions of an organization, which in turn improves the quality and accuracy of its data.
The purpose of data governance is to identify what data and information is important, establish the processes to manage it, and measure the effectiveness of the effort in achieving business objectives.
The Challenges of Data Governance Adoption
Getting your organization to buy into a new data governance program conceptually is the easy part. Taking action and sticking to it, on the other hand, can be much more challenging.
Indeed, many organizations believe that simply implementing technology—like a Master Data Management system—will improve the health of their data.
Tools will help streamline your organizational processes and complement information governance and information management, but building and maintaining a culture that treats data as an asset to your organization is the key to ongoing success.
Data Governance Best Practices
Some key factors to build good habits and generate momentum once your data governance program is underway are:
- Impart a sense of urgency for the data governance program
- Communicate effectively and often
- Operationalize change within the organization
- Make the plan as RACI as possible
- Automate for efficiency
- Measure, communicate, repeat
1. Impart a sense of urgency for the program
For every organization with a plan to manage its data assets, there needs to be a sense of urgency to keep the plan in place. This sense of urgency is created by socializing the reasons why a data governance program is important for your organization’s success.
The reasons are unique from organization to organization, but they might be driven by:
- Compliance
- Customer satisfaction
- Sales
- Revenue
- Mergers & Acquisitions
In order for these reasons to be effective, they must resonate with senior leadership and be tied to the company’s strategic goals.
2. Communicate effectively and often
The cornerstone of a successful data governance program is a well-organized (cross-departmental) communication plan. A solid plan helps remove the silos and maintain cross-departmental support for the initiative.
Seek your champions throughout the organization and meet with key stakeholders regularly to document their pain points. It is important to get people engaged early to keep the excitement going.
3. Operationalize change within the organization
Your delivery will need to be agile in nature because the plan you put in place will naturally evolve. The goal is to learn what works within your organization early on to ensure you deliver value quickly and the process is sustainable moving forward.
Complete tasks iteratively and agree upon a small set of high-value data attributes to aid in validating your data governance process. In addition, manage your data elements to ensure their best quality.
4. Make the plan as RACI as possible.
Actively listen to your supporters and put together a plan that encompasses a RACI (Responsible, Accountable, Consulted & Informed) model so that everyone on the team knows their role across the process.
A RACI plan will keep your team focused and guide your initiatives moving forward.
You’ll raise your odds of success by forming a strong governance organizational structure with roles and responsibilities in place, along with approvals that complement your existing change management process.
These roles may include:
- Data users: The team members who use and input data as part of their day-to-day job function
- Data owners: The team members who are responsible for, and are thus a point of contact for, a certain type of data.
- Data stewards: The team members who serve as the champions of your data governance strategy. They help to enforce policies and procedures and train new employees or team members in data governance.
- Data governance council or committee: This team may go by another name, but their responsibility remains the same. They help to oversee the data governance strategy, approve new policies, and guide the program.
5. Automate for efficiency
Digital process automation enables businesses to automate low-value and time-insensitive business processes.
Automation solutions replicate business activities and processes typically performed by individuals or teams, allowing those teams to shift their time to more valuable work.
The results of automation are improved efficiency, reduced costs, faster systems and processes, and reduced errors.
There are several areas to incorporate automation in your data governance program, including:
- Workflows
- Permissions requests
- Data requests
- Approval processes
6. Measure, communicate, repeat
Keep in mind that “you can’t manage what you don’t measure.” You’ll need to face the facts and communicate your findings.
It’s wise to identify and document KPIs (Key Performance Indicators) so that you can measure the progress of your initiative over time. These KPIs may include the amount of sensitive data you are creating and the amount of stale data you are saving.
Tracking these metrics will give you better insight into your data governance program and point you to what’s working and what isn’t. Linking the KPIs to revenue or sales loss, for example, can be a strong indicator to help drive change.
As you learn more about your data, it’s important to communicate what’s meaningful to your stakeholders and continue to move forward.
Key Components of a Successful Data Governance Program
In addition to following each of the above best practices, you’ll also want to be mindful of these key factors when implementing your data governance program:
- Transparency: To ensure full buy-in, both participants and auditors need clear communication around motivations, processes, practices, and control.
- Flexibility and growth: The data landscape is constantly changing, as is your organization. Continue to evaluate your data governance journey and make strategic changes as necessary to ensure continued success.
- Accountability: The key players in your data governance program, including data owners and data stewards, must have full accountability for their areas of responsibility in order for the program to be a success.
- Organizational change management: Without adoption or benefit realization, your data governance efforts are useless. Approach data governance in a strategic way that ensures employees and change leaders alike have the necessary understanding and ability to implement and sustain the change.
Putting Data Governance Into Action
Data governance demands a discipline that takes time and patience to fine-tune. This requires changing years of undisciplined behaviors regarding data within your organization, and the change will not happen overnight.
Remember that data governance is a marathon, not a sprint. Implementing an effective data governance program is a journey that requires commitment and hard work.
If you want to take your organization to the next level, you need to develop the discipline toward information management that your organization requires for long-term sustainable success.
For those with little experience in implementing or maintaining a data governance plan, experienced data & analytics consultants can be of great value.
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