Growing companies often find themselves floating on an “ocean” of underutilized or misused data – data that doesn’t reach the people who would most benefit from it or reaches them at the wrong time. Preventing these issues is one of the primary objectives of Data Governance. It helps companies keep their customers satisfied with their products and services by boiling down this ocean of data to actionable items that are delivered to the right person at the right time. Data will only continue to grow as an economy, and Data Governance is the key that unlocks the door to future growth.
Understanding Data Governance
At the base level, Data Governance consists of a framework and the actors who interact with that framework. Data Governance is concerned with the management of data, making it available, usable, reliable, and secure to the users who need it most in an organization, as well as making sure that personally identifiable information (PII) provided by clients remains private from third parties.
One function of Data Governance is to ensure that algorithms and systems are connected correctly. Data Governance can help identify the key people in an organization – the data stewards of an enterprise’s key systems. Perhaps the biggest challenge in any organization is dependency. This can either be a complete dependency on programs and algorithms or a dependency on the workers who maintain these systems. Data Governance can help expose these dependencies and help to alleviate them.
Role of Data Governance in Business
Data Governance has both internal and external components. The internal involves getting reliable data to the right person at the right time for it to have the most impact. An example of this would be making sure an insurance claims agent receives fraud data and analytics to make more informed decisions. The external component involves protecting PII, following the laws governing usage such as General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA).
Sophisticated enterprises have become savvier about embracing the principles of Data Governance and see the value in a systematic approach that strives to amend the issues caused by ad hoc systems of Data Management. Such enterprises are increasingly staffing a chief data officer, who serves as a liaison between stakeholders and data information specialists. Chief data officers may often find themselves in need of convincing stakeholders about the value of adopting Data Governance frameworks, leading to a need to develop business cases to facilitate buy-in.
Risks and Rewards
A key component of business cases is understanding the risks and rewards of adopting a certain policy or program. The biggest risk to consider is that without Data Governance, an organization’s systems will not be working at peak efficiency, thereby missing out on identifying fraud or taking advantage of business intelligence that can have long-term effects on company survival. The reward here would be in the implementation of the Data Governance solution where the right person gets the right data.
Another risk is that with so much data to govern, databases and data warehousing need to be safeguarded from hackers who are intent on capturing PII to commit fraud. Without Data Governance, it becomes harder to identify what potential avenues unauthorized users may try to access sensitive data.
5 Suggestions and Best Practices
To get the most from Data Governance initiatives, companies can implement these best practices:
- Integrate Data Governance into the software development lifecycle. This can ensure high quality of data creation, simplifying maintenance and thus, help reduce outlay and keep budgets tight from a Data Quality and governance standpoint.
- If information is going to be siloed, it is important to make sure everything is synced so that business definitions for data remain constant. Some companies like to keep information in silos, but then they run the risk of having different definitions for data in those instances. If there is a need to compartmentalize information that way, it is best to keep an eye on integration so people and systems can work together efficiently.
- Train teams so they understand deliverables. The most useful products arising from the Data Governance process are data catalogs (both business and technical). A data catalog can be thought of as a directory or “yellow book” for all the company’s key data entities, allowing the business definitions of every piece of data within a company to be searchable, from text to complete algorithms.
- Know what the difference is between business lineage and technical lineage. Data lineage is the trail that helps keep track of where data originates and enables the ability to locate inconsistencies quickly.
- Recognize that Data Governance requires collaboration with your stakeholders. Getting buy-in can be a considerable hurdle for chief data officers, making the need for convincing governance business even more important.
The Business Case for Data Governance
Today’s market floats on a sea of data, and Data Governance is the structure keeping organizations afloat. Companies that do not understand the importance of Data Governance run the risk of having poorly developed products or less useful, more insecure data. Data Governance involves convincing stakeholders of the value of implementing Data Governance policies.
One way to think about the importance of Data Governance might be using an analogy to a streaming service like Netflix. Movies have ratings and genre tags that help users determine what they would like to watch or possibly what is safe to watch with children. Without a tagging system like this and the ability to access the data by these filters, it would be impossible to make informed decisions about what to stream.
Creating a solid Data Governance business case is a key part of getting buy-in for chief data officers, allowing them to show the value of implementation within an organization. With a solid business case, it is possible to show stakeholders how Data Governance can help the organization achieve its key business objectives. For data-driven organizations, there is no apparent alternative to Data Governance other than not utilizing it, which means companies are less responsive to customers, potentially less innovative, and more open to fraud by bad actors who can exploit blind spots in an organization’s data.