Poor quality data can lead to inaccurate insights, wasted resources, and decreased customer satisfaction. It is essential to ensure that all of your data is accurate and up-to-date to make the best decisions. Still, common issues and mistakes costs organizations millions of dollars annually in lost revenue opportunities and resource productivity.
Thankfully, these pitfalls are well known, and easy to fix!
Duplicate data occurs when the same information is entered into the same system multiple times. This can lead to confusion and inaccurate insights. For example, if you have two records for the same customer in your CRM system, notes, support cases, and even purchase data can be captured on different records and leave your organization with a fractured view of a single customer.
Perhaps worse than having duplicate data is having incomplete data. Missing data occurs when some of the necessary information is missing from the system and can lead to incomplete insights. Many systems allow application owners to determine required data fields to prevent missing data.
While capturing and retaining historical data can be very beneficial, especially regarding customer data, it’s critical that data is kept current. It’s essential to have a regular process to ensure that your organization purges information that is no longer relevant or up-to-date.
Date formats, salutations, spelling mistakes, number formats. If you work with data, you know that the struggle is real. It’s also probably one of the trickier problems to address. Data integration platforms like DataConnect can allow data teams to establish rules that ensure data is standardized. A simple pass/fail ensures that all your data follows the established formatting standards.
Imagine buying a house without having the most current interest rate information. It could mean the difference of hundreds of dollars on a mortgage. But many companies are making decisions using days, weeks, or months old data. This may be fine for specific scenarios, but as the pace of life continues to increase, it’s essential to ensure you’re getting accurate information to decision makers as fast as possible.
Tips for Improving Data Quality
Data quality is an ongoing practice that must become part of an organization’s data DNA. Here are a few tips to help improve the quality of your data:
- Ensure data is entered correctly and consistently.
- Automate data entry and validation processes.
- Develop a data governance strategy to ensure accuracy.
- Regularly review and audit data for accuracy.
- Utilize data cleansing tools to remove outdated or incorrect information.
Data quality is an important factor for any organization. Poor quality data can lead to inaccurate insights, wasted resources, and decreased customer satisfaction. To make the best decisions, it is essential to ensure that all your data is accurate and timely.