Applicant tracking systems have become a standard part of hiring. They collect applications, organise candidates and help teams keep track of who is at which stage. Many of them also offer automatic screening: rules that filter out CVs that do not match certain keywords, years of experience or qualifications.
For companies that receive many applications, this seems like an obvious time saver. But automatic filtering has a cost that is easy to miss. The candidates it rejects never reach a human, so nobody notices when a good one is lost.
How keyword filtering works
Most screening rules are simple. The system looks for specific words in a CV, such as a programming language, a framework or a job title. It may also check for a minimum number of years of experience or a particular degree. CVs that do not meet the rules are ranked lower or rejected.
The logic is reasonable. If a role requires Java, a CV without the word Java is probably not a fit. The problem is that real CVs, and real engineers, are rarely that tidy.
Why good candidates are rejected
There are many ordinary reasons why a strong candidate might not pass a keyword filter:
- Different words for the same thing. One engineer writes “Kubernetes”, another “K8s”, another lists “container orchestration”. One says “front-end”, another “UI development”.
- Experience described as outcomes. Senior engineers often describe what they achieved rather than listing every tool. The skills are there, just not in the exact words the filter expects.
- Transferable skills. An engineer with deep experience in one language can often become productive in a similar one quickly. A filter sees only a missing keyword.
- Unusual career paths. People who changed careers, studied abroad or worked in smaller companies often have CVs that do not follow the standard pattern.
- Formatting. Some systems struggle to read CVs with columns, tables or unusual layouts, so information is lost before any rule is applied.
- Rigid thresholds. A rule such as “at least five years of experience” will reject someone with four and a half years who might be the best person in the pool.
Bias that automation repeats
Filters are written by people, and they reflect people’s assumptions. If a rule favours certain universities, certain job titles or uninterrupted careers, it will apply that preference to every single application, consistently and without question.
This can quietly narrow the pool. Candidates with career breaks, for example for family reasons, or those from less familiar educational backgrounds, may be screened out more often. Because nobody reviews the rejected CVs, the pattern can continue for a long time without anyone noticing.
The candidate’s side
For candidates, automatic rejection is often frustrating. Many receive a standard message within minutes, or no answer at all, without knowing why. Experienced engineers, who have choices, may simply stop applying to companies with this kind of process. This affects your reputation in a market where good people talk to each other.
Using screening tools sensibly
None of this means applicant tracking systems should be avoided. They are useful for organising a process. The risk lies in letting rigid rules make decisions on their own. A few practices help:
- Keep must-have criteria to a minimum. Ask whether each requirement is truly essential. Often only two or three are.
- Use filters to sort, not to reject. Ranking candidates and still reviewing the lower ones briefly is safer than automatic rejection.
- Include synonyms and related skills. If you use keywords, think about the different ways people describe the same experience.
- Review rejected candidates now and then. A periodic look at who was filtered out quickly shows whether the rules are working.
- Write the job description carefully. Clear descriptions attract better-matched applications, which reduces the need for heavy filtering.
- Tell candidates what happens. Even a short, honest explanation of the process improves their experience.
Where people make the difference
Automatic screening is good at handling volume. It is not good at judgement. Recognising potential, understanding an unusual career or seeing that someone’s experience fits the role in a less obvious way still requires an experienced person reading the CV, and often talking to the candidate.
This is the reason behind our Precision Hiring approach at Boomit. We combine efficient tools with careful human review, so that strong candidates are not lost to a missing keyword. If you are hiring IT specialists and want a process that finds the right people rather than only the right words, we would be glad to talk. You can reach us at boomit.pt.