The Candidate the System Couldn't See

The candidate the system couldn’t see

Over the last few months, I’ve been helping a former colleague find his next role.

After spending six months travelling, he returned to a job market that felt increasingly difficult to navigate. Applications were submitted. Rejections arrived. Then more applications. Then more rejections.

At one point he was applying for thirty or forty roles a week.

What stood out was not the number of rejections. It was how similar they felt.

Different companies.

Different industries.

Different recruitment platforms.

The same outcome.

The same generic response.

After a while it became difficult to escape the feeling that nobody was really reviewing the application at all.

What made it particularly frustrating was that I knew how capable he was.

Not because of what was written on his CV.

Because I had worked with him.

I had seen how he approached problems. I had seen how quickly he learned. I had seen him take on responsibilities that extended well beyond the expectations of his role. I had seen the quality of his thinking.

The challenge was that very little of that was visible to the systems making the initial decision.

Experience and capability are not the same thing

On paper, his experience suggested one thing.

In reality, his capability suggested something else entirely.

He was applying for roles that represented a significant step forward from his previous position. The problem was that most recruitment processes begin by looking backwards.

What was your job title?

How many years have you spent doing this?

Where have you worked before?

These are reasonable questions.

The difficulty is that they are all measures of experience.

They are not measures of capability.

Anyone who has managed people will recognise the distinction immediately.

Some individuals perform exactly as their experience suggests.

Others consistently outperform it.

The challenge is identifying the second group.

Is a human sift any better?

This is where the conversation becomes more interesting.

It would be easy to frame this as a story about AI getting it wrong and a human getting it right. The reality is more complicated than that.

Human recruiters have biases too. They work under pressure. They make assumptions. They can be influenced by previous employers, education, job titles, and countless other signals that may or may not predict future success.

The difference is not necessarily that humans make better decisions.

The difference is that humans can ask a second question.

A recruiter can look at a CV and wonder whether the title fully reflects the responsibility. They can explore how somebody thinks. They can challenge their own assumptions. They can investigate weak signals that suggest capability beyond what is immediately visible.

An automated screening system can only work with the evidence it has been instructed to evaluate.

That distinction matters.

What the system could see

Modern recruitment processes are designed to handle scale.

When hundreds of applications arrive for a single role, some form of filtering becomes inevitable.

The systems look for signals.

Job titles.

Keywords.

Qualifications.

Years of experience.

Previous employers.

These are useful indicators.

But they remain indicators.

They are not capability.

They do not tell you how somebody performs when faced with ambiguity. They do not tell you how quickly they learn. They do not tell you whether they can operate effectively at the next level.

The system can only evaluate what is visible.

The advice that changed everything

Eventually, we stopped focusing on applications.

Instead, we focused on people.

My advice was simple.

Talk to recruiters.

Build relationships.

Have conversations.

Give somebody the opportunity to see beyond the document.

The goal was not to bypass the recruitment process.

The goal was to reintroduce human judgement into it.

That changed everything.

The first meaningful opportunity that emerged led to an interview for a Senior Data Consultant position.

What made that particularly interesting was that his previous role had been Operational Performance Analyst.

On paper, it looked like a significant leap.

In practice, it was simply an opportunity for somebody to see what had been there all along.

Over the following weeks, we worked together on his CV, interview preparation, and a case study presentation.

The case study itself was interesting. Like many consulting exercises, it was designed in a way that encouraged candidates to jump immediately towards technology solutions, platforms, and architecture decisions.

The stronger answer was not to decide everything from six slides of information.

The stronger answer was to demonstrate curiosity, challenge assumptions, and show how you would engage with people before making expensive decisions.

That shift in thinking was what transformed the presentation from a technical proposal into a consulting approach.

Shortly afterwards, it became a job offer.

What this taught me

This experience reinforced something I keep seeing across technology.

The challenge is rarely the technology itself.

The challenge is deciding where judgement should sit.

Recruitment systems are useful.

AI is useful.

Automation is useful.

But there are some questions that become harder when we remove the opportunity for people to challenge the initial conclusion.

Capability is one of them.

Capability often exists in context rather than keywords.

It reveals itself through conversation rather than classification.

It appears in judgement rather than pattern matching.

The things we cannot easily see

One of the recurring themes across this blog has been visibility.

What we measure influences what we see.

What we see influences the decisions we make.

The danger comes when we start assuming that what is visible is all that exists.

Capability.

Curiosity.

Adaptability.

Judgement.

These things are often difficult to identify through systems designed to process information at scale.

That does not make them less important.

Quite often, they are the things that matter most.

The candidate who got the job was always capable of doing it.

The challenge was finding someone who could see it.