Why should your organization invest in data quality?
The COVID-19 pandemic has helped make data an integral part of modern businesses. With many companies switching to digital formats—from workplace culture to online sales and customer service—data is more important than ever. Based on Experian’s global data management research study, 72 percent of businesses say an accelerated digital transformation has made them more reliant on data and data insights.
To be able to make reliable decisions based on data, your records have to be accurate and trustworthy. Investing in data quality management lets you make sure your data is correct and can be used for high-level decision-making, whether you’re validating existing data or incoming datasets.
Taking steps to improve your data quality means your business can make more informed decisions. For example, high-quality data could give you a competitive edge in your industry by showing you an untapped market. You can use your data to customize a marketing plan tailored specifically for this market and reach new customers before your competitors.
5 risks of untrustworthy data
1. Wasted time
Each time you use unreliable data, you risk going back and redoing the process with data that’s been verified. This also means you’ll probably have to manually find and fix mistakes in your records, including deleting duplicates. These extra steps mean your employees are spending more time correcting errors than focusing on the projects at hand. Improved data quality helps cut out the number of data entry mistakes that lead to time wasted on correcting entries
through manual processes. Your employees become more productive and your business runs more efficiently.
2. Missed opportunities
Across industries, businesses are trying to use data to find new opportunities and stay ahead of the competition. You can be sure your competitors are doing the same. If your data lacks consistency and reliability, you’re giving your competitors an edge over your organization. Poor data quality can slow down your business, making it less agile and unable to react to changes in the market. You’ll miss opportunities that your competitors may be able to take advantage of. On the other hand, staying on top of data quality can help you find new opportunities before your competitors. This gives you a chance to capitalize on new markets or other opportunities first.
3. Compliance issues
Data issues can cost your business a lot of money. However, it’s not just the time it takes to identify and correct records that will cost your organization. With the introduction of data regulations like the General Data Protection Regulation (GDPR), businesses must be careful how they collect, store, and use data. Violating the terms of the GDPR or other security regulations can come with large fines. Likewise, a security breach could wipe out the public’s confidence in your business. Good data quality helps lower your risk of security issues and keeps you compliant with the latest data regulations.
4. Poor customer experience
How do you feel after a great experience with a brand? More than likely, you’re ready to tell friends and family about this brand and become a repeat customer. What happens if you have a poor experience? You’re a lot less likely to become a loyal customer. Data quality can affect the customer experience. Poor-quality data could cause you to send out marketing materials that don’t resonate; alternatively, an incorrect address could mean a package is undeliverable and is returned to your warehouse. Your customer has to wait longer to get their items. Accurate data, on the other hand, can help you improve targeted marketing and delivery
times.
5. Unreliable decision-making
One of the biggest risks of poor data quality is the inability to make accurate decisions based on the data you have. When your data is low-quality, you can’t be sure the insights you’ve drawn are correct. According to Experian’s research, 55 percent of business leaders don’t trust their data assets completely, making any insights unreliable. Improving your data quality means you can put more trust into the insights you build. You’ll feel more confident in your data and can
be sure your decisions are based on reliable, accurate data records.
4 tips to start improving your data quality
We’ve looked at the importance of data quality for your business—including the risks you take when you ignore data quality. But how do you get started improving your data quality? Is there a way to improve the quality of the data you already have? How do you prevent poor-quality data from entering your database in the future?
The good news is there are tools, processes, and methods to help you answer these questions and create a sustainable data quality management plan. We’ve created a list of the most important tips to help your organization evaluate your data processes from a data quality perspective. We’ll also discuss how you can improve quality across your organization.
First, however, let’s look at how the right technology and employee training can help create a good data quality management plan:
• Technology: Modern data often has to use modern technology to be successful. You’ll want to invest in data quality tools—such as real-time data validation solutions— to help improve your data.
• People: Even if you invest in a variety of data quality tools or resources, you still need engaged employees who will use 12345 data quality processes. The best way to do this is to look for resources and tools that are user-friendly, integrate easily into your existing systems, and make your employees’ tasks easier.
1. Determine data goals and quality metrics
Does your organization have an overall data strategy, or are you collecting data just to collect it? Before you can start improving your data quality, you have to figure out why you want to collect data and what you plan to use it for. Some businesses, for example, want to collect and store customer postal address details for their eCommerce stores. Others are looking to improve customer service response times.
Your business should take the time to plan data goals and strategies. When those goals are identified, you’ll have a better idea of what you have to do to improve data quality while working toward your goals.
2. Standardize and cleanse databases
With data management and data quality plans in place, you can focus on improving the data you already have in your systems. Many businesses started collecting data without a clear plan in place. This means your data could easily be separated throughout your organization in data silos. Existing data may also be outdated, incorrect, or otherwise unreliable.
Data standardization is the process of creating one cohesive system to store and manage your data. This means all of the data you collect is in the same format, making it simple to share data between teams or process different types of data using similar metrics.
Once data is standardized, your business can cleanse your existing databases to find and amend inconsistencies or inaccuracies. Data cleansing uses trustworthy and reliable data sources to validate your existing data records. For example, Experian’s data cleansing services can be used once to validate a database or as a regular data cleaning solution to keep your data current.
3. Fill data gaps
Did you know there’s a way to expand your existing data with additional trustworthy data, such as location details? Data enrichment lets you purchase additional datasets to enhance your existing data records with more details. Enriching your data helps give you a complete view of your customers.
For instance, you can use enriched location data for delivery route planning to increase delivery speeds to your customers. Enriched location data could include geolocation details that point delivery drives to the exact location to deliver a package at a customer’s business.
4. Use technology for data quality maintenance
The right data quality solutions and tools can maintain the quality of your data automatically. Investing in technology that can regularly update your records or automatically validate contact data gets rid of manual tasks that could hold your employees—and your business—back.
Experian, for example, offers a full-service data quality management solution. We not only help you improve the quality of your existing data, but our solutions can help stop poor-quality data from entering your database through real-time validation.
Ready to start improving data quality to unlock reliable insights?
According to Experian’s global data management research, 95 percent of businesses have seen an impact due to poor-quality data. By investing in data quality management tools and resources, you help make sure your organization’s data is of good quality throughout the data lifecycle—from the point of capture to analysis and insights.
Feeling overwhelmed by the idea of creating and implementing a data quality management plan? You’re not alone! Many businesses aren’t sure where to start or what tools they’ll need to get the most data quality improvements.
Get in touch with our data quality experts to learn how Experian can help you better manage your data quality.
