HR Tech’s decoders

Half a decade ago, or shall we say an eternity ago by today’s standards, a commitment was made to bring to you the best of a promising ecosystem that constantly evolves – the HR Tech. Six editions later of Akoya Start You Up, we have to acknowledge the fact that the technological landscape has evolved considerably. However, we have to be wary of all the buzzwords flooding today’s world, as they often don’t accurately represent what is actually going on “under the hood”. Let’s take a more in-depth look at the situation, without complacency and without jargon!

Statement 1 : « VR is a gadget »

Our analysis: Rather false

All the rage only 3 years ago, virtual reality and its futuristic masks seem to have slowed its rapid growth among individuals, due to limited use cases outside of the video game niche. However, in a professional context, VR is a great media to leverage for an immersive Learning & Development experience. With hindsight, we are starting to get the first feedback on this technology, and the results are appealing: we learn better, faster and cheaper.

Augmented Reality (AR) on the other hand is another story. The technology is perhaps even more promising in a professional context, as it allows to “overprint” information on real life objects, but apart from Microsoft’s HoloLens there is little affordable hardware on the market (where are the smart glasses we were promised 4 years ago?).

Statement 2 : « The personality test tools are not much better than lifestyle magazine test you take on the beach.»

Our analysis: False

Already, not all tests measure the same thing. Cognitive tests, which are somewhat similar to IQ tests, do not serve the same purpose as psychotechnical or psychological tests. Secondly, these testing methods generally rely on statistical samples. However, the exponential digitization of our personal data makes it possible to further improve the accuracy of these tests. What’s more, when combined with a learning machine (an AI that learns and predicts without really knowing how it arrives to a conclusion), it is even possible to predict your personality traits without you having to fill out any questionnaire. If you don’t believe us, go scare yourself by checking out Crystal which will predict your personality based only on your LinkedIn profile!

Statement 3 : « Many start-ups exaggerate when they tell us about AI »

Our analysis : Slightly true

Ah the AI… Who doesn’t do it today anyway? Or rather: who really does? Actually, only 40% of so-called “AI specialized” start-ups actually use the technology. What we see today in the HR Tech is that the rather systematic use of a concept tends to trivialize it, and it becomes no longer a real differentiating factor, to the disadvantage, of course, of certain start-ups that are sincere in their statements.

But when we talk about AI, what exactly are we talking about? For a long explanation, check out our white paper. We’ll look at two main use cases of AI here.

Firstly, AI is often used where language analysis is required. This is often the case with skills repository tools, feedback or listening tools, and of course chatbots. These technologies are very mature, so mature that many “libraries” (kinds of software bricks) developed by third parties already exist. The majority of start-ups are thus more users than they are AI designers.

The second main use case covers anything that concerns a personalized recommendation or matching. Here, there are two main sub-cases: algorithms trained on an initial data set without learning based on new data, which use statistical methods but only apply them once; or algorithms that learn continuously. The two approaches are compatible, but only the second case is purely AI.

Technology is good, sustainable technology is better.

This brief decoding highlights the ephemeral nature of certain innovations (e.g. blockchain), or rather the hype that sometimes surrounds them. Perhaps, rather than jumping on the next hot technology, it would be better if we sometimes stuck to the basics. Many of our clients are reluctant to go digital, either out of fear of redundancy with their HRIS, or out of concern for further fragmentation of their ecosystem.

What if instead of boasting in obscure terms, each in his own corner, about who has the biggest engine that we know will soon become obsolete, we began to talk about the compatibility of each other’s systems, their openness and their complementary workings? To put it shortly: what if we discussed a sustainable and interdependent technology for 2021?