HR Tech Interview with Siadhal Magos, Cofounder and CEO at Metaview

Siadhal Magos, Cofounder and CEO at Metaview joins us to talk about his innovative platform and the story behind it while sharing a few thoughts on today’s evolving workforce trends in tech:

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Tell us a little about yourself Siadhal…and the story behind Metaview

I grew up in London, to an Irish mother and Hungarian father, which explains the unique name! I went to university and studied history, but once I graduated I really started to develop an obsession with startups and tech…this obsession – via a few pitstops – led me to becoming Head of Product at a startup called Osper, before going on to lead a product team at Uber. Who – at the time – were the fastest growing company ever, and just an incredibly exciting place to be They have a large site in Amsterdam, which is where I was based. I absolutely loved it there!

In those last two roles I developed a new obsession: people. At Osper, we were a post series-A startup, I was working directly with the CEO there, and every hire felt like we were adding someone to the family, so we really obsessed over getting it right. Then at Uber, I saw an elite hiring machine in action that was bringing top-quality people in at unprecedented scale.

While I was at Uber, my now co-founder was on a similar journey as a Tech Lead at Palantir. We were jamming one day and came to a fundamental realisation that led to Metaview: Interviews are the most outcome-defining part of a recruitment process, yet there is essentially zero data coming out of them.

Once we’d discovered this, we knew that the best way to solve it was to make use of the latest breakthroughs in NLP and speech processing. That way, we could turn interviews in to troves of data for high-performing organizations that are looking for an edge in the war for talent.

Now at Metaview, we use speech-to-text to help organizations uplevel the most important step in their hiring process: their interviews. We do this by enabling:

• Interviewers to focus on the interview at hand rather than taking notes.
• Hiring decision makers to collaborate and make decisions based on the actual evidence, rather than feelings or memories.
• Talent leaders to understand the health and performance of their interview process at scale. Then, we give them awesome tools to improve them!

More broadly, we believe conversations are the next frontier for data-driven organizations. And we want to capture them and use them to help reimagine teams get built.

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What plans do you have in terms of the platform’s evolution – what can users look forward to from this platform as it develops?

We’re really only getting started, but we’re already THE platform for any organization that takes interviews seriously.

In the future, customers can expect even better collaboration features, deeper and more informative data about the health of interviews, and even more timely and effective automated interviewer coaching.

How do you feel HR teams can benefit from interview intelligence and insights, what are the additional ways in which this automated intel can further their efforts?

Fundamentally this is about building exceptional teams. That is what every organizations wants to do, and certainly what every talent professional wants to do. So the question our customers ask themselves is: “what is standing in the way of me reliably building exceptional teams?”

Often we find the answer to this is that they compete to source candidates, and convince them to enter an interview process, then it all becomes opaque.

As well as helping improve hiring decisions and uplevelling interviewers, we’ve also used our data to:

• Identify bias in the interview process. There is lots of activity around DE&I – which is awesome – but it’s impact is always going to be limited by the aptitude, consistency, and fairness of interviewers… as they make the final decision.
• Identify how hiring surges impact quality of interviews and, therefore, time to hire and quality of hire.
• Identify interview techniques that result in more efficient hiring funnels for our customers.

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Over the years in tech, how have you observed HR leaders try to optimize their interview process for evolving roles in tech – what are the top thoughts you would share here?

What I saw about say 5 years ago was a push in to more online tools for assessing the hard skills of a technical candidate. Platforms like HackerRank, TripleByte, Coderpad were all part of this movement. These are great, because they enable you to filter against your technical bar more efficiently. Indeed, we use them here at Metaview for our own hiring.

But they don’t tell you the whole story. What I’ve seen in the last few years is an increase in focus on values-alignment, and softer skills such as collaboration, grit, and communication. This is because everyone in tech is now so in demand, that you really want your team to work well together, otherwise people will move on.

We’re getting very close to a reality where technical skill is measured. It’s completely transparent, and not an area where a hiring organization can gain an advantage in their ability to identify talent (as they all have access to the same information). Where elite hiring organizatons will differentiate themselves is on their ability to pick for those softer skills. And this is obviously something that we are incredibly passionate about.

As roles across tech get more automated, what are some of the newer skills that today’s workforce should be equipped with as a basic standard?

There are two major trends to be aware of.

Firstly, automation efforts are funneling into rote, predictable tasks. Not creative jobs. Right now, many people that have creative jobs, still carry out a handful of rote tasks as part of that. These will go away, enabling them to focus more on differentiated, creative tasks. In Metaview’s case, this means no more taking interview notes, or churning out the same one-size-fits-all interview training again and again, among many other things.

Secondly — and as a result of this — more and more knowledge workers will be expected to be able to manipulate, and massage data themselves in order to make better creative decisions. This means knowledge workers of the  future will be expected to have basic levels of programming knowledge and proficiency. Think about it: you wouldn’t ask someone to look something publicly available up for you, because Google is one click away for all of us. In future, you won’t be asking someone to find an insight or a datapoint for you. You’ll be expected to do it yourself in order to keep the pace of decisions making high and remove dependencies.

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What are some best practices that you’d share with teams when it comes to using and implementing interview intelligence systems?

There are two things to bear in mind when rolling out an Interview Intelligence system.

Firstly, there need to be good systems of record in place. By that I mean, reliable use of an ATS to track candidates and a culture around effective interviewing being important. It is with this footing – which the majority of high performing organizations have – that you can start to introduce more innovative ways to uplevel interviews. Interview Intelligence 10xs the effectiveness of your interview process, so it’s important there is a real process in place already.

Then, there is a cultural aspect. Growing organizations often have a “growth mentality”. By that, I mean that people in the organization want to improve and seek opportunities to do so. This type of mentality is important to instill in order to get the most out of Interview Intelligence systems, as the aim is to help people and processes change and improve.

What are some of the top tech trends and in-demand skills you feel will dominate HR / HR Tech in the near-future?

With the amount of demand on technical skills such as engineering, one of the biggest movements is certainly the changes that are happening in the world of credentials. Up until now, a strong university degree in computer science was often a prerequisite for breaking into the world of tech. This obviously has all sorts of negative consequences from diversity perspective, and in general results in a lot of wasted potential. I see this changing through a new wave of schools such as Lambda School, which confer on its graduates a much more accessible yet equally respected credential. It’s a real game-changer.

Separately, as more and more of what we do (in recruitment, or in general day-to-day work) becomes measurable, HR will become increasingly data-driven. The job here is make sure we are making the most of all this new data that is at our finger tips, while doing it in a way that is beneficial for employees and leadership (not just one or the other). For example, using people data to help improve the performance of individuals is in everyone’s interest. It needs to be clear that this is not just a management tool.