Why recruiters cannot fix bad ATS data
Recruiters already work under pressure. They are expected to fill roles, keep candidates warm, and close deals. Adding data cleanup to that list is unrealistic. The problem is not motivation. The problem is that manual cleanup does not match the work recruiters are hired to do. Clean, complete, current data inside the Applicant Tracking System (ATS) does not happen through extra effort. It needs structure and automation.
4 expensive problems of messy ATS data
The scale problem
Most agencies hold thousands of profiles inside the ATS. Many are outdated, incomplete, or duplicated. Typical issues are:
Duplicate candidates with slightly different details
Missing skills or old job titles
Inconsistent company names or industries
Partial contact details
If a recruiter spends five minutes on each record, cleaning 5.000 profiles becomes 400 hours of work. That is two months of full time effort. Even if you forced it, the data would be out of date again the moment candidates change jobs or update skills elsewhere. Manual upkeep cannot keep pace with the volume.
The cognitive load problem
Recruiters are hired to judge talent and move people through a pipeline. Asking them to classify records, correct labels, or tag skills forces them into data entry mode. The mental switch slows them down. Errors become likely. Most will skip the work to get back to sourcing and selling. The result is a database that never reaches a stable, usable state.
The inconsistency problem
Even motivated recruiters will not apply the same rules. One calls someone a software developer. Another uses backend developer. Skills get abbreviated in different ways. Company names drift. Without a shared taxonomy, each attempt to fix data creates more variation. The ATS fills with subtle contradictions that break matching, reporting, and boolean search.
The opportunity cost problem
Every hour spent correcting data is an hour not spent on revenue. Recruiters drive income by:
Speaking with clients
Engaging candidates
Matching profiles to open jobs
Manual cleanup does not win business. It does not speed up a hire. It does not help clients. It pulls your most valuable people into low value work and slows the whole operation.
Why agencies need a system
No team can manually maintain clean ATS data at scale. You need consistent inputs, a shared taxonomy, and automated enrichment that updates profiles continuously. A structured system can:
Standardise job titles, skills, and industries
Resolve duplicates
Fill missing fields
Keep information current
When these mechanics run in the background, the ATS becomes searchable again. Recruiters stop starting from LinkedIn every time because the card index is finally in order.
The takeaway
Expecting recruiters to clean your ATS is unrealistic. The volume, cognitive load, and inconsistency guarantee failure. Agencies that want reliable search, accurate matching, and faster shortlists need clean, complete, current data at the foundation. Daidalo keeps your ATS updated and structured automatically. Recruiters stay focused on sourcing and selling. The database stays usable. Your workflows stop breaking.
