Data Governance Is More Important Than Ever: Best Practices And Examples
Our personal and professional lives are becoming more dependent on data every day. Businesses and individuals create data daily at an unprecedented rate. Throughout 2020, every single person on the planet created at least 1.7 MB of new data every day. By 2025, this figure is set to increase to 463 exabytes each day. For reference, one exabyte equals one billion gigabytes.
It’s an almost unimaginable amount of data and dealing with this data responsibly is what data governance is all about. The more data we produce, the more important it becomes.
What Is Data Governance?
The Institute of Data Governance (IDG) offers a very brief definition of the term: “Data Governance is the exercise of decision-making and authority for data-related matters.” The definition may be deceptively short, but the field itself covers a wide range of roles and processes.
In practice, data governance refers to the protocols and procedures that determine who within an organization has access to and control over the entity’s data assets. Data governance includes the people, processes, roles, policies, metrics, and standards that determine how an organization uses the data it collects effectively, efficiently, and safely.
It defines individual responsibilities when it comes to data handling and clarifies who can take action, using what data, in what situations, and with which methods. Data governance ensures that there is clear ownership of and accountability for data assets within a company.
At its most efficient, data governance provides organizations with a clear strategy for data handling.
Why Is It Important To Organizations?
Every single business in 2021 utilizes data as part of its daily operations. Does this mean that every organization requires a data governance strategy? There is no one-size-fits-all answer.
However, any organization that is active in the big data field or simply handles large amounts of data needs to have a solid data governance strategy in place. The consequences of operating without this strategy in place are simply too serious.
Data governance prevents and helps rectify a wide range of organizational difficulties. Common tasks of data governance teams include:
- Delivering streamlined definitions for data to ensure a shared understanding of industry terms
- Improving data quality through consistent efforts to improve data sets held by the business
- Limiting a company’s exposure to inconsistent data held separately by different departments or branches of the business
- Preventing data errors and deliberate misuse
- Increasing analytics accuracy, ensuring your leadership team has reliable information for decision-making
- Ensuring compliance with data protection legislation such as the European Union’s GDPR regulations or California’s CCPA
Neglecting any of these considerations can be detrimental to a company’s performance whilst also exposing it to legal problems.
Data Governance Vs. Data Management
Data governance and data management are frequently confused because of their close relation. However, it is worth clarifying the differences.
Data management is a wider-reaching concept encompassing the entire data lifecycle needs an organization has. Data governance lies at the core of this data management and creates connections to other areas including data security, data warehousing, and database operations, to name just a few.
Data governance also differs from master data management (MDM). The latter is concerned with the quality and integrity of an organization’s data. Those responsible for your company’s MDM need to ensure you have the most accurate information available.
Whilst the two fields are not identical, they are closely related. Data governance provides the framework for MDM by defining access, data curation, and master data models. They cannot work as efficiently as possible without each other.
How Data Governance Aids Business Performance
Ensuring proper data governance limits an organization’s exposure to risks arising from badly managed data and insecure handling of information.
Most businesses have some level of data governance in place, even if it is informal and varies between individual departments. At a practical level, ensuring governance is about clarifying who has responsibility for and formal control over data-related processes.
When companies grow, leaving an individual in charge of data governance becomes less efficient. This is when businesses have to formalize their approach to governance, putting it on a more systematic basis.
Systematic data governance creates the basis for integrating data across the entire organization. If your business has different departments with a range of legacy systems in place, data governance allows the business to unify those.
After an initial transition period, the business will save on data management costs. The organization no longer needs to support different systems which require different qualifications, various levels of funding, and operations.
By providing clear rules for the transition process and the handling of data overall, any company’s business and IT processes become more agile. As the business grows, it is easier to scale one centrally managed system to reflect the growth.
High-quality data and well-established processes can confidently be reused across the entire organization. Plus, clearly defined data governance and adherence to those rules make it easier to comply with local and international data protection and privacy regulations.
Who Is Responsible For Data Governance In A Business?
Establishing a solid data governance strategy is a team effort. The responsibility for both strategy and implementation does not only lie with your IT department. It also involves business executives, often at the senior management level.
Large companies often choose to have a data governance steering committee. The committee is generally made up of representatives from different parts of the business. Whilst they are rarely the people who decide data policy and standards, they will approve relevant proposals, policies, and rules. Individual committee members also help resolve potential disagreements between different parts of the business.
If your organization has a chief data officer (CDO), they are most likely the person to oversee your data governance strategy. Their role would also entail securing funding, approval, and sufficient staffing for the program.
It takes a team to fully implement the strategy. Roles within this team include a manager and additional team members who look after the day-to-day specifics of the program. They would also be tasked with reaching out to analysts and data engineers to address any errors.
Data stewardship is closely related to data governance, and an organization’s data stewards are often closely associated with the data governance team. Because their role includes oversight, they need to be independent of daily governance implementation.
How big your data governance team needs to be, depends on the amount of data your organization handles and where you are starting from in the strategy’s implementation.
Data Governance Best Practice
- Secure Internal Buy-In
- Set Clear, Realistic Goals
- Stay Close To Your Business
Secure Internal Buy-In
To create a strong, well-supported data governance strategy, you need to secure internal buy-in across the organization. Especially where there are strong legacy systems in place, convincing different business units and departments of the benefits of data governance may take some time.
Making a case for data governance will be easier if you have a strong business case and communicate consistently. Not many people truly like change, but if they understand the benefits brought about by the change, they are likely to support it.
Focusing on the value data governance will create for the business and creating a clear connection to the organization’s business goals helps you make that case. Clearly showing savings and efficiencies created by the strategy will convince management and staff. If you can connect the expected positive outcomes to business goals that have already been defined, it will be easier to secure support.
Just like any other business communication, your data governance strategy needs to be upfront, open, and consistent. Introducing data governance into an organization for the first time is bound to hit roadblocks. Share them with the team and make it clear how you are addressing them.
Set Clear, Realistic Goals
As the saying goes, “Rome wasn’t built in a day”. The same is true for your organization’s data governance strategy.
Even interim goals must be measurable. Without a clear metric, it is almost impossible to determine when your goal has been achieved. On the other hand, defining goals allows you to celebrate milestones and clearly demonstrate the project’s progress to internal and external stakeholders.
Goals also need to be practical and realistic. It is impossible to unite several different customer relationship management systems into one system in one single step. At the very least, it would be a very high-risk strategy. Instead of taking that risk, start by integrating two systems, then add another. Not only does this allow you to show successful steps. It also allows you to address mistakes on a more manageable scale and adjust your tactics as necessary.
Stay Close To Your Business
No two businesses are alike. To be successful, your data governance strategy needs to reflect the nature and the needs of your business.
Start by looking at your business model and identifying how data governance will support it. Your goal is to create a customized governance strategy. As much as a degree of standardization is a part of that, the strategy as a whole will only succeed if it reflects the business as a whole.
Data Governance Examples
- Preservation And Storage
It is easier to convince your team or your entire organization to use your data if that’s their easiest choice. Making data accessible and easy to understand is the first step in the process. Organizing data in a simple, logical way should be normal, but too many systems do not yet work like that.
Listen to the input from your team. Assuming you would like your salesforce to use a central customer relationship management (CRM) tool rather than a hardcopy notebook, it is worth asking why they prefer the notebook.
Consider the need for training sessions. Not everyone has grown up around data and databases, and some of the team may require a bit more support.
It’s almost impossible to follow the news for even a single day without reading or hearing about a data breach.
When you are setting put your data governance strategy, it is important to balance accessibility and usability with data security. Imagine your business deals with healthcare. Health records are among the most sensitive personal data and keeping the information safe is a priority.
The responsibilities of your data governance team include limiting access to specific data to selected individuals only and deciding who these individuals should be.
Preservation And Storage
Notebooks run out of space, sales staff leave, but well-built data storage facilities scale with your business.
We have already established that any organization will have data that staff need to access all the time, whereas other information is needed only infrequently. Over time, some information may be needed so rarely that it can be archived or deleted. A solid data governance strategy needs to define those categories and create clear guidance on how they will be handled by the organization.
Data security needs to be a priority, whilst ensuring data is easily found when it is needed.
Today’s economy is led by data. Even hands-on businesses like – for example – construction contractors hold customer information, supplier details, and most of them will use technology to handle their bookkeeping and accounting.
Every single business holds a huge amount of data. Handling this data safely and reliably is easier with a clear data governance strategy. Data governance also allows companies to make the most of the data they hold. However, its main objective remains to encourage responsible handling of data and avoid breaches. Developing and implementing a strategy based on these principles supports business performance and longevity.
Need help with your data governance strategy? Let us know!