5 Essential Steps to Measuring Entity Data Quality

Use these five steps and reduce your costs associated with data quality.

Take Advantage of New Technology

By using new technology, firms can scan their data and identify problem areas to gain a quick overview of the state of their entity data. New technology can upload data records and perform hundreds of quality scans, covering data completeness, consistency, duplication and more. You can even uncover data by attribute, and assess dozens of aspects that define quality.

Today, technology can read information from hundreds of sources just like a human and identify names, addresses, relationships, and other information…just like a human. Think about what could happen if your technology can’t readily match the right name with the right address.

Leverage Knowledge

Data quality analysis tools will not solve the problems for you, but they can empower you with the information needed to succeed with entity data management. After pinpointing problem areas, you can then prioritize the actions you need to take to make improvements.

Organizations have room for improvement. On average, more than 20 percent of organizations believe they have inaccurate data. That’s a missed keystroke, outdated information, or incomplete/missing data.

Your tool should discover and reveal erroneous records and mistakes that can be addressed in the source system. You can then perform ongoing checks and measure progress and improvements in quality. Meaning you have time to solve your list of critical data problems that influence the risk, compliance, marketing and sales organizations.

Tell Data Stories

It’s essential to ensure everyone is on the same page. Spreading the word about the firm’s approach to entity data, the governance processes in place, and the expected benefits, raises the chances of success and reduces the push and pull that can increase costs in a lot of programs. As with any good story, show examples and make it personal by talking about the hierarchies, countries, business units, and even the clients themselves that are reflected in the entity data.

Optimize Your Costs

To succeed with entity data management, it helps to incorporate data quality measuring activities into standard processes. As entity data is regularly affected by name changes, merger activities, office moves and more, you can now scan your entity data on a daily, weekly or monthly basis to effectively maintain the data and ensure the quality remains at a sufficient level. This ensures high levels of data quality at lower ongoing operating costs vs. having teams of hundreds of data stewards or operational staff chasing the latest data update.

Risk and Reward

Finally, many data initiatives today are driven from regulatory mandates or next generation risk programs. These programs require reliable, robust entity data to meet the demands of regulators and risk officers. With any risk or compliance data initiative, take time to also meet with the business units that drive revenue and show them the data. Many times they’ll see an opportunity to either use the data themselves to drive revenue, or may have ideas to provide more data. By leveraging the work to date, you can begin to leverage your data investment even more, which builds organizational credibility and momentum.

If you’re doing all five well, congratulations. You’re on your way to providing the type of value the business needs. If you want to improve, start with a data management assessment. But for the more advanced organizations that want to reduce their spend on inefficient data-related process and third party data, take a look at a platform-driven solution that can seek out, identify, extract and update unstructured data from a wide variety of sources.