According to Gartner, a research firm - low quality data is responsible for $15 million per year in losses. In 2016, IBM found that bad data costs the U.S. economy a whopping $3.1 trillion annually. Thankfully, there is a way to solve for low quality data from creating better compliance strategies to investing in software that tracks it for your company.
What Causes Low Quality Data
Human Error: When companies rely on those people to manually input data – mistakes can happen.
Compliance & Inconsistent Processes: Not only is it important to create processes around data collection and management – it’s also important that your employees are complying with those practices to eliminate potential errors. In an interview with AutomationWorld, Michael Simms, practice director for data and analytics at Columbus Global recounts, “I once worked with a company on data migration, and we began with mapping their data based on zip codes and states. After a few minutes of combing through the data, I saw an issue immediately: The data showed 253 states because there was no set way to input the state names. Each state appeared multiple times in multiple formats; for example, Nebraska, Nebr., and NE.”
Siloed Data: When data is held in too many places it can become siloed. While it’s true that many software integrations allow the ability to sync data there is still room for error which can lead to critical data getting lost.
Old Data: John Smith may have been the managing CISO at Big Name Tech Company three years ago when his information was collected and uploaded to Salesforce but now he works as a CEO of Startup A. If your marketing and sales teams don’t know this – they are essentially wasting their time and resources setting themselves up for failure. This can lead to low open rates for the marketing department.
Turning Bad Data into Good Data
The first step is realizing that you have bad data. One you realize that – you can begin to fix it.
Perform a data audit: Audits help companies analyze the data they have while discovering bad data and the source of the bad data. From there companies can take what they learned from the audits and create processes to ensure low quality data does not seep into future their data sets. While data audits can be conducted in house – there are also third-party companies that can perform the data audit.
Merge duplicate data: Now than John Smith changed jobs he may be in your database twice. What happens if John Smith decides to change jobs for a third time? He could be in your CRM three times. This means that sales and marketing may think they have three potential leads when they only have one. It’s important that periodically your company merges the data, updating prospective profiles. CRMs like Salesforce can do this for you manually or have a workflow where an administer gets notified if a duplicate exists.
Conduct Regular Maintenance: Why would you go through the time and effort to clean your data once if you don’t plan to keep up with it? Go through your data frequently so you can make sure the data you do have is up-to-date.
Invest in software: There are software that companies can purchase that will automatically track data quality and help customers manage their data.
Now that you know that data quality can be an issue at your company – sign up for an audit, invest in software, and conduct regular maintenance to ensure that bad data doesn’t negatively affect your company.