Keeping your company’s information updated is vital. Without accurate data, your teams can’t achieve their (or your company’s) goals. After all, poor-quality data can quickly reduce the effectiveness of your internal and external outreach efforts.
Let’s say your marketing team creates and initiates a clever digital campaign aimed toward customers who are at risk of leaving. If the customer contact data in your system isn’t valid, the end users will never see your campaign’s content. As a result, the campaign will likely produce fewer responses. On the surface, it may seem like the campaign wasn’t well-founded. In reality, the campaign failed because of incorrect information.
To avoid this and other data dilemmas, put some tech strategies into practice. Being proactive now will help you avoid preventable data issues.
1. Maintain a Centralized Data Location
When the same data exists in more than one place, mistakes can occur. Consider the case of a team of salespeople. Each salesperson maintains a spreadsheet of personal contacts. However, the spreadsheets aren’t shared, and there’s inevitable overlapping data. When the entire sales department wants to send a single announcement to every salesperson’s contacts, the data inconsistencies between the spreadsheets can interfere with the desired outcomes.
The workaround for this problem is to house all data in a centralized location and insist that the centralized portal be used for all information input as well as updates. It’s important to sync global address list content as part of this effort, too. High-powered tools that are driven by AI can help keep all globally accessible addresses updated. When an address is modified in one place, it is instantly modified in every other place, decreasing the instances of inaccurate data throughout your organization.
2. Reduce Manual Data Input Workflows
Manually cutting and pasting data from one location to another can take time and cause headaches. A single human error could lead to data becoming unusable — or unavailable. Recent statistics suggest that the annual price of human-related data loss is high. From accidental deletions to exposed proprietary information, leaving data movement to people isn’t a wise decision.
Ideally, incoming data — regardless of the source — should enter into your system once and then become part of an automated process. After it’s in your encrypted system, it can be retrieved when needed but not available to just anyone. For instance, when you want to construct a report, you should be able to rely on data software that can access your information and automatically populate your documents. At that point, you can control the data appropriately. But you won’t need to manually find the data, which should improve the confidence you have in your report findings and reduce the chance of data being accidentally deleted, moved, or corrupted.
3. Follow a Consistent Data Retention and Usage Policy
Many businesses hold on to all their data forever. Though you don’t have to purge your data stores, consider moving older data out of your active database at regular intervals. An example of this would be to stop using customer data after the customer hasn’t made a purchase for a certain amount of time. You can base the timeline on your average customer lifecycle.
Remember that newer data is probably going to be more up to date than older information. Therefore, constantly refreshing your data pool should improve the accuracy of your data. As a side benefit, you may realize cost savings, as it can be more economical to store less data. Additionally, getting rid of data may keep you within compliance depending upon your industry’s regulations.
4. Validate Your Business’s Incoming Data
Another solution to keep your data up to date involves data validation. When any information flows into your company, make sure it’s evaluated for mistakes or inconsistencies. Again, this can be done automatically rather than by your team members.
For example, you probably ask customers to input their personal information during the sales checkout process. You can lean on a program to spot discrepancies, like an extra digit in a phone number or text added to a numbers-only field. The customer can be alerted of these mistakes and asked to resubmit the data. When the information enters your system, it should be complete and generally free from errors. Data validation isn’t perfect, but it’s better than having a lot of unstructured and incomplete data.
5. Train Employees on How to Keep Data Clean
Even if your employees are working with data regularly, they might not understand how to keep the data they work with up to date. Providing them with training can ensure that your entire team is working from the same data management playbook. And that’s especially vital if your company operates in a remote or hybrid format since people may be inputting and accessing data without the benefit of in-person supervision.
You won’t need to develop a data management training curriculum in-house. Numerous technical training platforms and providers offer this type of professional development. From webinars to self-directed courses, you can get everyone up to speed and on the same page in very little time.
Your data is one of your company’s most important assets. Yet it can’t help your organization stay ahead of the curve if it’s constantly out of date. Rather than take chances, put some tech tricks to work so all of your information remains clear, reliable, and healthy.
Lynn Martelli is an editor at Readability. She received her MFA in Creative Writing from Antioch University and has worked as an editor for over 10 years. Lynn has edited a wide variety of books, including fiction, non-fiction, memoirs, and more. In her free time, Lynn enjoys reading, writing, and spending time with her family and friends.
