Turn clean data into big wins
Thirty-six percent of the obstacles companies face with AI are data-related—and 28% of those stem from something surprisingly simple: poor data hygiene. It’s a clear reminder that even the smartest tools are only as effective as the data feeding them. That idea was front and center at this year’s Engage Boston during the session “Data is the new capital: How to mine yours for gold.” The session featured insights from Melissa Rosen, VP of Global Services Sales at Bullhorn, and Tom Perso, VP of Information Technology at Trillium Staffing. Together, they shared practical tips, effective strategies, and hard-earned lessons to help organisations build databases that truly work for them.
Clean data takes a village
Data hygiene is as much about people as it is about platforms. It shouldn’t be thought of as IT’s responsibility. As Perso noted, “All the way down to the end user, they need to take ownership of the data they’re putting in.” Whether it’s recruiters adding notes or sales teams logging calls, every touchpoint shapes the health of your database. The more each person sees themselves as a data steward, the stronger, cleaner, and more reliable the system becomes.
You need a solid plan
Still, good intentions only go so far. “As soon as you clean that data one week, it’s not clean the next,” Rosen explains. In fact, up to 30% of a company’s data can go stale in just one year–a concept often referred to as “data decay.” Without a clear, consistent maintenance plan, even the most pristine database will quickly lose its value.
The solution? Treat data hygiene as an ongoing program, requiring routine maintenance. That means regular audits, clear standards for data entry, and the smart use of automation tools. When the process is woven into daily workflows, data upkeep will feel like a habit rather than a chore.
Let automation reduce the effort
Manual entry is often where data hygiene begins to break down, making automation and centralised oversight essential. Automation can validate and deduplicate records, auto-fill missing fields, and reduce the risk of human error. More than just improving accuracy, automation gives teams the freedom to focus on the more meaningful, relationship-driven work.
“Recruiters and salespeople do what they do great, which is having human interaction and some of those soft skills,” said Perso. That’s why automation should enhance, not interrupt, their natural workflows: capturing phone calls, tagging emails, and logging interactions behind the scenes. “Have those interactions automatically brought in and tagged to the right person so they don’t have to think about it…that makes them happier people.”
Enrichment—using public data to keep records current—and seamless integrations are also essential to a streamlined workflow. Automated updates are powerful tools, but only when they’re thoughtfully mapped, rigorously validated, and closely monitored.
But automation alone isn’t enough. Clean data may begin at the point of entry, but maintaining it is an ongoing journey. It starts with standardised data collection, followed by validation, deduplication, regular cleansing (whether manual or automated), and consistent audits. Finally, integrating data from everyday tools like email, phone, and scheduling systems ensures accuracy at the point of entry. When data management becomes seamless, your team can focus fully on what drives real results.
Should you throw out old data?
Many wonder what to do about old data. Admittedly, it can be a tough call. On the one hand, outdated records can clutter your system and skew reporting. But deleting them can also feel risky. If a record hasn’t been touched for two years with no signs of engagement, it doesn’t need to stay active in your system—but it shouldn’t just vanish into thin air either. Archiving data provides peace of mind for everyone involved. “I will say in Bullhorn, deleting a record is a soft delete, which is great. If you do it wrong, it’s very simple to go back and un-delete it,” says Perso.
Start small, win big
Don’t try to fix everything at once. If you attempt to overhaul your entire database in one go, you’ll get overwhelmed—and so will your team. Instead, identify one or two problem areas. Maybe it’s duplicate records or missing job titles. Clean those up first, and build momentum through small, visible wins.
Consider appointing a “data champion”—someone who can advocate for change, train others, and sustain momentum. This role helps embed good data practices into everyday routines, making clean data a shared responsibility.
Clean data powers results
Clean data is the quiet force behind every smart business decision. It powers sharper insights, stronger relationships, and more scalable growth. Though data hygiene is never truly complete, the right systems—and the right advocates—can turn your database from a lingering threat to a strategic advantage.
Want to learn more about how you can optimise your business’s data hygiene? Talk to your Bullhorn account manager today or learn more in our step-by-step guide to data hygiene.
