A data governance framework is an effective tool for ensuring the reliability, integrity, and accessibility of enterprise data. It can help to ensure regulatory compliance and safeguard your organization’s assets from cyber-attacks, unauthorized access, data breaches, and theft.
Developing a practical framework requires the right people, processes, and technology. Here are 5 Key Elements of an Effective Data Governance Framework to guide your strategy:
Define Your Objectives
Before you embark on a data governance framework, setting your objectives is essential. This will help ensure the process is successful and grows as your business evolves.
Defining your objectives will also help you identify and prioritize your stakeholders. These might include data owners, users, and auditors.
You’ll need a team of people to implement your framework, so consider assembling a mix of data security specialists, IT professionals, project managers, and subject matter experts. You can also round out the group with employees with frontline experience who understand your data strategy and how it affects business operations.
When building your team, think big-picture but start small. Getting everyone on board with your vision will help make the process successful.
Once you have a data governance framework in place, it’s essential to refine it as technology and regulatory requirements change continuously. These changes can impact your framework’s scope, policies, and measures.
Define Your Scope
Defining your scope will help you to build a data governance framework that works for your organization. It will portray your strategy, policies, and measures to ensure that all stakeholders are on the same page and that data is trusted, well-documented, and easy to find within your organization.
Leaders in every industry know that to thrive, they need readily available, high-quality, and relevant data. Without these characteristics, digital transformation, analytics, and new sources of revenue cannot drive business success.
When creating a data governance program, leaders in this space often start by understanding the organization’s unique business drivers. These may include regulatory compliance and industry mandates, such as health insurance privacy laws.
Leading organizations also use metrics to measure the impact of their governance efforts. These can include data scientists’ time finding, enabling, or curating data for priority use cases or the dollar losses that poor-quality data results in.
These metrics allow leaders in this space to demonstrate the value creation their data-governance activities have generated. They can help to ensure that governance efforts will continue to receive the attention of top management.
Define Your Policies
Defining your policies is one of the essential elements of a practical data governance framework. It will help you create a roadmap and set your objectives while also enabling you to standardize roles and processes.
The policies you set should align with your business goals, ensuring that you provide the best data possible to your organization and maintain regulatory compliance. These policies should also cover data quality, security, and privacy.
It would help if you also considered whether your data governance model is best suited for the size and structure of your company. For instance, if you are a large enterprise, it might be better to implement an end-to-end approach that includes policies, rules, and guidelines.
Once you have defined your policies, it is time to begin implementing them at your company. This process can be challenging, but following the steps above gives you an excellent foundation to build your data governance framework. You can start with a small sample size to assess the state of your data, then expand from there.
Define Your Measures
A practical data governance framework can improve business data quality, availability, and usability. This can lead to improved customer experience, reduced costs, and more reliable insights across your organization.
A successful data governance framework must also ensure that the data it governs is secure from cyber-attacks and unauthorized access. This can save your business money, increase employee productivity, and help you meet regulatory compliance requirements.
One of the first steps in creating a practical data governance framework is to define your measures. These will help you assess the success of your program and determine how to grow it in the future.
For example, you may want to set goals around protecting top-level data, reducing team friction, or creating a more efficient data entry process. These objectives should be clear and attainable to keep your team motivated throughout the implementation process.
Define Your Metrics
A practical data governance framework is crucial to any organization that collects and stores information from different sources. It helps ensure data is accurate and readily accessible, improving productivity and boosting overall business performance.
A successful data governance strategy also requires a clear set of metrics that can be used to measure its success. These metrics can include the number of workers trained in the new system, improvements in productivity, and stakeholder satisfaction, among others.
The most important aspect of defining metrics for a practical data governance framework is to think with the big picture in mind. Getting caught up in detail and straying from the goal is easy.
A well-defined set of metrics will help you monitor progress and make necessary adjustments if needed. They can also provide a roadmap for how you plan to achieve your goals. In addition, they’re an excellent way to communicate with your team and stakeholders.