If you go to technology conferences, you hear the same discussions around data. If you ask about how to glean insight from the massive amount of data you’re collecting or you want to use your data to provide actionable intelligence, make better business decisions and offer a better customer experience, the answer you’re likely to hear is based on the latest analytics tool. While I agree there are several powerful new solutions out there, gaining insight into your data doesn’t start with an analytics tool. In fact, the answer to how you can gain insight from data is simple: Start with a unified governance approach to your data.
"There’s governance for being compliant with regulations, and there’s governance for insights," Vice President and Chief Data Officer for IBM Analytics Seth Dobrin noted at the Fast Track Your Data conference in Munich, Germany. "So how do I use governance to accelerate insights in the company? That’s a shift for most companies. Most companies see governance as a roadblock, [but] governance can be an accelerant for innovation."
Dorbin's comments acknowledge a fundamental truth: No matter how much data there is, and no matter how powerful the insight tools, no company will gain the insight it requires if the data is not properly governed.
Consider how many organizations embark on a big data initiative. They purchase the right technology and begin pooling data from disparate systems into data lakes or data warehouses. But how do they know which data stores to use? How sure can they be of the data’s lineage and integrity? What can they do to ensure that their data lake doesn’t become a data swamp?
Unified Governance
The only way to ensure that the data being used for analytics represents the best possible information is to start treating data as your organization’s most prized possession. This means knowing which data stores are the most valuable, accurate and current. It means knowing which data stores have high levels of security. And it means consistently complying with evolving and increasingly complex regulations, especially in the area of privacy.
Historically, these tasks have been allocated to different departments, including different IT areas and often siloed legal, records and compliance teams. Today, however, all information stakeholders must work together to ensure data accuracy, security and privacy, and internal, regulatory and legal compliance. Operationalizing this interdependency is unified governance.
The main elements of a unified governance approach include:
• Data quality: As noted above, to derive actionable insight from structured and unstructured data, analysis must be performed on the most accurate, up-to-date data. The inability to delete or tier data, or to unify or sync data across multiple systems, may mean that the analysis is being performed on older, inaccurate or inconsistent data, thus skewing the results.
• Data security and privacy: In the wake of highly publicized data breaches, more and more businesses are taking data security seriously. However, major breaches continue to occur, including the recent Equifax incident that affected more than 143 million consumers. There are many reasons these breaches continue, but one of the most important is an obvious governance issue. If you don’t fully understand where your data resides -- in the cloud, on mobile devices, in the hands of partners -- and if you can’t distinguish your most valuable data from redundant, obsolete and trivial data, then you cannot fully understand how to protect it.
• Internal compliance: Complying with internal standards for data storage and access is essential for the health of the business. Users must be sure of the origin and purity of the data and have ready access to the data they need. Failure to maintain internal compliance can easily lead to users not having the business context for the data and using it incorrectly.
• Regulatory compliance: In the face of mounting and evolving regulations around the world, including the EU General Data Protection Regulation (GDPR), which takes effect May 25, 2018, businesses must make regulatory compliance an inextricable process in every data initiative. Failure to do so can lead to significant fines and potential damage to your company's reputation.
• Legal compliance: As the amount of data grows, so do the costs and risks associated with e-discovery requests. If you don’t fully understand who is producing and accessing data and how it is stored, and if you aren’t able to delete old and irrelevant data that you can legally eliminate, then the cost of an e-discovery request can skyrocket, and you will likely be producing far more data than is necessary. This increases the legal risk to an organization, and, as with regulatory compliance, it can undercut the benefits of any big data initiative.
• Information governance: Information governance (IG) comprises the policies, processes and controls that enable an enterprise to ensure data accuracy, assess information value, reduce regulatory and legal risk, and defensibly dispose of information an organization no longer needs. At CGOC, we created the Information Governance Process Maturity Model (IGPMM), which is a guide to maturing these policies, processes and controls. EDRM's Information Governance Reference Model (IGRM) is also designed to help organizations understand the links between the value of information, the duties that must be performed to manage data and the specific data stores that IT manages. Without a solid IG program in place, all the other data management activities are likely to fail.
Conclusion
The foundation for obtaining actionable intelligence, making better business decisions and creating a better customer experience is clear. Your big data analytics must be performed on the highest quality data. To ensure high-quality data, you must develop a governance culture that treats data as your most valuable asset. Doing this requires a unified governance approach. And for this approach to be successful, you must start with a robust information governance program.
