Right now, there is a controversy surrounding the world of tech talent acquisition, and it all began with a Reddit thread. One engineer created a fake CV with some of the biggest tech names from Instagram to Microsoft in an attempt to test the screening process of some tech employers. Stemming from a lot of rejection, this particular software engineer wanted to ensure that recruiters for tech businesses were correctly reading CVs instead of looking for keywords. This engineer also added some bullet points detailing joke achievements and hyperlinks to a Rick Astley music video as a real test.
You’d expect as a talent acquisition professional that this would be unsuccessful, right? So, of course, we’d spot these fake and joke points. However, we’d be wrong because this engineer got a 60% response rate from the likes of Reddit, Airbnb, Dropbox and more, all of whom were excited to speak with him about open positions.
Naturally, this is causing tech talent to question the screening techniques of some of these tech companies. If qualified people are being turned away, but those who lie and make a joke out of the application process are successful, what does this say about the current state of talent acquisition? Clearly, AI and automations are picking up buzzwords and company names rather than reading resumes in detail. Because of the sheer volume of applications to leading tech companies, these CVs are not being considered in detail. AI can only pick up on keywords and specific criteria, it may be an advanced technology, but it can’t deliver an utterly accurate screening process, especially if candidates include misinformation in their CVs. For large tech companies to rely purely on this technology is lazy, and there’s no wonder that intelligent tech candidates are finding loopholes to break the system and fall through the net.
Big tech gets hundreds of inbound applications for every vacancy. This is because everyone wants to work at these big-name players and exciting tech brands. For internal recruiters, this means a lot of applications to sift through and whittle down, which is why AI is incredibly useful.
Internal talent teams are stretched to the limit, and in situations like this, it shows. The question is, how do you decide which application is better than another if they all share equal skills? Talent teams can’t interview hundreds or even thousands of applicants, so they need to decide what determines success. Does it come down to the prestige of the company or educational establishment, or should you be looking more for personality and cultural fit? This experiment clearly shows large corporations value reputation over all else, which could be incredibly damaging to the tech industry and harder for candidates to break into these top corporations.
When it comes to the phone screening stage, you’d think that recruiters would be able to identify lies and call out any mistruths. However, it could be easy to lie your way through a screening call if the recruiter doesn’t have a good knowledge of tech and the skills required to succeed. Recruiters need technical knowledge to hire technical talent. Otherwise, they could end up hiring anyone and having to provide training or restart the hiring process when the talent proved unsuitable. It’s about asking the right questions but also having an idea of the correct answer, or else what’s the point in screening?
With candidates now assuming that getting into big tech relies more on experience working with similar tech companies or top universities, what does this mean for those who work hard to gain skills in other ways? You can achieve much more experience at a startup, and non-traditional education can be just as beneficial as attending a top university with a massive improvement to online or on the job learning. Suppose recruiters don’t screen properly and just look for business names. Does this mean talented people are left searching for opportunities while those with the audacity to lie to get into top positions?
This also links back to issues of diversity and hiring within your network. How can leading tech businesses truly diversify if company and university names are the criteria they value above all else? How can you benefit from a range of perspectives and experiences if everyone has the same background?
Ultimately though, failing to screen CVs properly will waste everyone’s time. If recruiters let fake CVs like this one slip through the net and reach further stages of the recruitment process, the likelihood is they’ll have to start again once the truth comes out. Restarting the recruitment process is costly and time-consuming, plus there’s a chance you could lose out on talented candidates that have already been rejected the first time around. In a candidate-driven market, these skilled people will likely have been snapped up by the competition. Recruitment teams will double their work, and the role will take longer to hire, which could cause productivity problems later down the line.
These fake CVs highlight how vital the initial screening process is. We can’t simply rely on technology to screen candidates, as tech-savvy applicants have proven they can beat the system, but if tech recruitment teams are stretched, what’s the solution?
If the problem with the screening process stems from talent acquisition teams at leading tech companies being stretched and receiving too many resumes, there are simple solutions.
Firstly, you can invest in AI to screen but make sure you integrate it properly and have regular human intervention to check the CVs which are getting through. AI lends itself to bias because it’s looking for keywords and statements; therefore, having human screening alongside will help your recruitment process be fairer. You’ll also spot these fake and mock CVs more easily. Computers don’t understand humour or sarcasm, they also aren’t lie detectors, so human interaction is necessary. Plus, they can ensure you’re being more diverse and giving talent from various backgrounds a chance rather than just looking for people from top-tier universities. It may take up a recruiters time to sit and screen CVs, but considering the implications of hiring someone lying about skills to get ahead. It will save everyone time and effort in the long run. No one wants to be hiring twice because of half-hearted recruiting the first time around.
Secondly, you could outsource your recruitment. If your talent acquisition teams are stressed, it’s no excuse for poor recruitment. Outsourcing recruitment gives them extra support, with a team embedding into your organisation to ensure the pressure is lifted and you’re still able to hire the best talent. These recruiters can dedicate their time to screening candidates thoroughly (it is their job, after all). If you find the right RPO provider, they should have the experience and technical knowledge to fill these roles successfully. If your team don’t have time to screen CVs efficiently and effectively, outsourcing could be the best solution. Whether you’re an in-demand tech giant or growing startup, asking for support is not an admission of defeat but instead shows you’re being strategic with your talent acquisition. Knowing you need assistance to support the volume of hires of applications means you take the recruitment process seriously and only want to hire the best of the best. An RPO provider will know that the best of the best means skills and cultural fit, not just having Microsoft on their CV.
Finally, you could extend your talent acquisition teams. But, if we’re being honest, outsourcing is more of a risk-free option. Hiring more talent acquisition professions is difficult in this current climate, but it’s a costly and permanent solution. Hiring demand may not always be so hectic, and you may find in a year or so, your existing team can more than handle screening the volume of applications correctly. Therefore, we’d only recommend extending your talent function if you know there will be demand for it for years to come. Otherwise, a flexible approach to RPO can be just as effective in refining the recruitment experience and ensuring quality hires without a long-term commitment.
