There is a growing interest in data governance recently, as many companies are identifying a wider swath of data that they must manage. However, data governance is not merely a project with a definitive start and end; it is an operational capability and requires an effort that is geared to change the culture of the organization. If your company has decided to start a data governance program or is considering one, there are four key elements which will help you design success; data discovery, sound project management, engaged key stakeholders, and a toolset that supports your goals. Include these in your project planning to improve data quality, ensure data alignment, and further leverage your data to boost your bottom line.
1. Encourage Data Discovery
For many years, there have been several pushes for companies around data; to think of data as an asset, encourage business involvement in data projects and use data for decision making. That’s all well and good, but what is data an asset for? Companies must determine what they are looking to implement through their data governance projects. Data governance should go well beyond determining common definitions of data elements, ensuring data standards, and reusing key references or master data. Internally, you must identify additional information about your data to understand what your governance strategy is achieving. This must include:
There is not a comprehensive list, as there is limited space in a blog post. However, if you are interested in other key information to collect during data discovery, shoot us a note here.
It is important to remind stakeholders not to get in the way of data discovery. In-depth data knowledge is gained through direction and clarity, but discovery phases will be unsuccessful if there is a suffocated data flow or experimentation with constrictive processes. Consider data governance as an enablement and empowerment core capability and you will find greater success in its implementation.
2. Establish Program Purpose, Metrics, and Timeline
The tactics to implement data governance and to determine the scope of a data governance program can range can vary widely, from reducing compliance risk to improving data quality. No matter your organization’s focus, establishing a goal is crucial to the success of the program. Today, most stakeholders have an understanding that data is an asset and a company-wide responsibility. What is not as widespread a belief is that data governance should not be just an IT initiative or just a business initiative; without good data, it is challenging to make decisions, create new products, retain customers, or perform many other vital business functions. Set specific goals for the program that align with organizational strategy, and define metrics for success so that you can track progress and troubleshoot issues. Allocate adequate time to implement, test, and monitor the solution as well. Lastly, select a place where data governance and overall data management should live in your organization. Traditionally placed in the hands of the IT organization, data is really a business asset. Strong program management in the form of purpose, metrics, and a timeline will set you up for success.
3. Include Key Members of Your Enterprise
Ensure key members of your organization, from both the business and the IT sides of the house, are involved in the effort to achieve success. Enterprise-wide data governance is founded on the notion of collaboration, meaning that data used across business units and IT groups must be linked together into an organic whole. Including both sides of the house will make for better data, but it will also facilitate a general understanding of business issues by IT and IT issues by the business. Feedback and concerns from IT and business should then be combined in a tool with metrics, rules, and procedures to identify, remediate and prevent business rule failures, data duplication, and other organizational issues that impact the bottom line.
4. Choose a Toolset that Supports Defined Program Goals
Not all data governance tools are created equal. The underlying philosophy of data governance is to strengthen business goals with enterprise-wide data, thereby unlocking additional utility of that data. Whichever tool you select, make sure it supports this collaborative nature. Some of the key functionality a data governance tool should have are:
We believe that Collibra is the ideal data governance toolset, as it includes all of the functionality above and has been written from the ground up expressly to support, enable and enhance the organization’s collaborative efforts from a business users point of view. NEOS has partnered with Collibra specifically for that reason (plus, the technology is top-notch). To learn more about Collibra, click here.
Kicking off a successful data governance program requires knowledge of existing data, cross-sector program management, stakeholder engagement, and the right tools. Most importantly, make sure that accountability and ownership are bestowed to the correct organization at your company. Data governance is not always best owned by the technology group.
Keep these four points in mind to help you plan and execute your program. To learn more about how NEOS views Data Governance, watch our webinar, “Top Practices for Achieving Data Governance.”