The secret to securing great talent is a first-rate candidate experience. If you have been in any way entangled in the aftermath of 2021’s Great Resignation, you know that even an attractive remuneration package, with compelling benefits, is not enough: Now, more than ever, prospective hires will want to see the best of your organisation, and that includes the best of you. You must be fast, decisive, and flexible, from the point of first contact.

This is a problem amplified by scale. If you’re responsible for hiring 100,000 employees per year, for instance, you may find you are required to provide a top-notch candidate experience for that many prospects. You could decide that it is better to do things the old fashioned way, but it is more and more likely that, in doing so, you will miss out on great talent. The cost of such losses is best avoided.

Automation, be it through an assessment tool, conversational Ai platform, or Applicant Tracking System (ATS), is the simple key to solving volume hiring in a chaotic market. However, understandably, many high-volume hiring managers tend to think that automation comes at the cost of personalisation and human contact. If, for instance, you’re processing 5,000 prospects to fit 300 job openings, how do you ensure your candidates are met with the high-touch journey they expect? Is an automated Ai conversation, in the minds of candidates, not just as impersonal as older methods of qualification?

What ‘high-touch’ actually means, and its purpose

On the face of it, ‘high-touch’ implies an emphasis on person-to-person, face-to-face contact in your hiring process. If you can see your candidates, if you can greet them warmly and exalt your free-breakfast policy, you can make them feel special. Sending an email or a link to a form is impersonal, outmoded, and risks alienating the people you want to attract. 

What if, instead, high-touch is a stand-in for meaningful contact, instead of lots of contact? What if you could conduct a smooth, quick, and painless interview process that:

• Asked the best from candidates, and allowed them to provide thoughtful responses in their own time
• Explored the human aspects of their personality, and not just the line items on their CV
• Ignored, by design, the aspects of candidates prone to bias (such as appearance, ethnicity, age, and so on)

Is that not more effective than a by-the-book interview in which you smiled a lot, engaged in forgettable small talk, and discussed a laundry list of perks?

Woolworths, Australia’s largest private employer, adopted the smart-touch automated hiring approach, and won handsomely for it. They used our Chat Interview (chat-based) and Video Interview (video-based) solutions to assess nearly 9,000 candidates, achieving a candidate satisfaction score of 9.2 out of 10. We saved the hiring team time and money, helped give each of their candidates the fairest possible go, and best of all, helped them achieve their hiring targets. 

Woolworths wanted the equivalent of a high-touch candidate experience, and judging by these candidate testimonials, they certainly got it:

“The chat makes you feel like you’re in a safe space – it gives everyone an equal opportunity instead of an in person interview as people can get extremely nervous”.

“I found the process to be reflective and I liked how they wanted to know about me”.

“Everything was amazing! By far the best interview system I’ve encountered! It allowed me to be comfortable and be myself, it really allowed me to take my time with my responses rather than stutter over my words”.

“It was great. I like the potential to retake videos and how quick you’ve responded”.

There you have it: That is how a small hiring team can process nearly 10,000 candidates, using conversational Ai, and offer a truly high-touch candidate experience. But the benefits don’t stop there.

With a smart-touch automation solution, Talent Analytics can heighten your touch

When you entrust your hiring process to Smart Interviewer, our smart interviewer, you automate the process of meaningful data collection. That data is then transformed into actionable insights that help you improve your hiring processes. With TalentInsights, you could learn:

• Your average time to hire
• Estimated time saving in hours (incidentally, we’ve helped our customers save a total of 530,000 hours that would have been spent in cumbersome, high-touch interviews)
• The quality of your candidate pool overall, or by gender
• Overall candidate engagement scores

And much more. Suddenly, you have the numbers to back your wider hiring strategies, be they focussed on DEI, or fairness, or another goal. You can show your business that you are making real, quantifiable strides, and leading the way in efficiency and social responsibility.

The appetite for good, actionable data in HR is higher than it has ever been. Hiring managers are waking fast to the realities of the Great Resignation – that we just don’t know as much as we should about what constitutes good talent and candidate experience. In other words: We don’t really know why people are leaving, and we don’t really know why they do or don’t choose us in the first place.

According to a recent study by Madeline Laurano, founder of Aptitude Research, only 50% of the companies that invest in Talent Analytics actually trust the source of their data. When you consider that around 80 million American workers are hourly workers, one of the hardest-to-recruit employment segments of the moment, it becomes clear that the need for useful data is absolutely critical. 

What approach will you take? What kind of experience will you provide your candidates, before and after hiring? What kind of data will guide your decisions? Remember: The choice to do nothing is still a choice, and it has an indeterminate cost.

To find out how to improve candidate experience using Recruitment Automation, we also have a great eBook on candidate experience.

There is no doubt that older Australians have been hit hardest by the health impacts of COVID-19, but it is, by far, the younger generations that will bear the economic brunt. According to official figures, there are almost 360,000 fewer jobs than there were 12 months ago, and approximately 937,400 Australians are currently looking for work.

But, with more than 1,500,000 people on JobSeeker benefits (due to end in March), those unemployment numbers are likely to skyrocket in the next few months. And the majority of these people are under 35.

Government initiatives such as the JobMaker scheme and JobTrainer fund will of course help, but so much more needs to be done to support our young people through this difficult period.

Scaffolding for these initiatives that will determine their success is missing. And it needs to be implemented from the moment our young people begin thinking about their working future.

Barb Hyman, CEO Sapia

In my experience, career counselling is almost non-existent in many schools. Without a tailored, thoughtful approach to this, how can teenagers begin their careers well?

I’m not suggesting school counsellors are doing a poor job, but that they can do a better one with the aid of technology.

The next step of the career ladder is wobbly at best.

The interview process, whether it be for part-time school and uni jobs or for full-time employment, is one that discriminates against young people and, in many cases, shatters self-worth.

I am hearing stories from many parents of big and small companies alike ghosting when recruiting! For those not familiar with the term, it means, usually once an interview has finished, the interviewee never hears from the company or potential employer again.

No reasons are given as to why the candidate wasn’t successful, no suggestions as to how they could do better next time, no feedback at all, and no closure. This a bleak situation indeed and can be incredibly damaging for those starting out.

How has this situation evolved?

Is it fear of confrontation or lack of care or empathy?

Why can’t we tell an unsuccessful candidate where they can improve, to set them up for success, instead of leaving them guessing?

What I do know is that technology, particularly artificial intelligence, can play an important role here.

It can ensure that unconscious bias (often directed at young people) is not part of the recruitment process.

It can provide valuable feedback and identify candidate strengths and weaknesses which is hugely valuable to employers and employees.

And it can free humans to do the jobs that AI still can’t. We owe it to our young people to provide them with the kind support and mentoring that will help them become the future leaders that our country deserves.

This cannot happen without a commitment from the public and private sectors. Governments need to provide more than just funding. Business needs to provide more than just a rejection email. Taking the time to treat our young people with respect and provide them with feedback and answers is such a small ask. It is the most basic of human interactions and the return on investment for society will be enormous.

Technology can aid us with this process but humans need to be the driving force behind it.

Source: Barbara Hyman, Smart Company, January 21, 2021

A koronavírus-járvány kezdete óta számos vállalat fordult okos algoritmusokhoz, hogy kiderítse, ki a legjobb jelölt a nyitott pozíciókra. Leggyakrabban arckereső programokat, játékokat, kvízeket és más vizuális vagy nyelvi mintázatokat vizsgáló szoftvereket vetnek be, hogy eldöntsék, ki kerül be az interjúkörbe.

A jelek szerint a 2013 októberében alapított, ausztrál PredictiveHire nevű cég ennél is sokkal tovább ment: olyan gépi tanuláson alapuló algoritmust fejlesztett, amellyel felmérhető, hogy egy adott jelölt esetén mekkora a gyakori munkahelyváltás valószínűsége – írta a héten az MIT Technology Review.

Barbara Hyman, a HR-cég ügyvezető igazgatója szerint ügyfeleik olyan munkáltatók, akiknek rengeteg jelentkezést kell feldolgozniuk, és egyebek mellett az ügyfélkiszolgálás, a kiskereskedelem, az értékesítés vagy az egészségügy területén aktívak.

Első körben chatbot dönt a jelentkezőkről

Amikor valaki a HR-cégen keresztül jelentkezik állásra, először egy chatbotot kell „meggyőznie” értékeiről. Az algoritmus nyitott kérdések sorát teszi fel, és olyan személyiségjegyeket elemez, mint a kezdeményezőkészség, a belső motiváció vagy az ellenálló képesség.

Sőt, az algoritmus a jövőben a gyakori munkahelyváltás valószínűségét – vagy ahogy a PredictiveHire honlapján reklámozza, a „menekülés kockázatát” – is vizsgálhatja, még teljesen pályakezdő jelöltek esetén is. A HR-cég legújabb tanulmányának fókuszában ugyanis egy olyan gépi tanuló algoritmus fejlesztése áll, amely kifejezetten ezt igyekszik előre megmondani. A kutatás keretében 45899 jelöltet vizsgáltak meg, akik korábban a PredictiveHire chatbotján keresztül válaszoltak a tapasztalataikról és helyzetmegítélő képességeikről szóló 5-7 nyitott kérdésre.

Ezek olyan személyiségjegyekre kérdeztek rá, amelyek korábbi kutatások – például a PredictiveHire saját kutatása – alapján szoros összefüggésben lehetnek a gyakori munkahelyváltásokkal, például az új élmények iránti nagyobb nyitottság vagy a gyakorlatiasság hiánya.

Algoritmusok a béremelés ellen

Nathan Newman, a New York-i John Jay College of Criminal Justice egyik egyetemi docense, aki 2017-ben arról írt tanulmányt, hogy a nagymintás adatelemzés a munkavállalók diszkriminációján felül hogyan használható a bérek letörésére, az MIT Technology Review-nak azt mondta, a PredictiveHire legutóbbi munkája

az egyik legkártékonyabb módja a big data munkaügyi alkalmazásának.

Ide tartoznak a gépi tanuláson alapuló, egyre népszerűbb személyiségtesztek is, amelyek azokat a potenciális munkavállalókat igyekeznek kiszűrni, akik nagyobb valószínűséggel támogatnák a szakszervezetekbe tömörülést, vagy hajlamosabbak béremelést kérni. Mindezt úgy, hogy az MIT Technology Review szerint a munkáltatók egyre jobban szemmel tartják dolgozóik e-mailjeit, online beszélgetéseit és minden olyan adatot, amelyből leszűrhetik, hogy az adott kolléga távozni készül-e, és kiszámolhatják, mi az a minimális béremelés, amellyel még adott esetben maradásra bírhatják.

Az Uber algoritmus alapú menedzsment rendszerei állítólag úgy igyekeznek távol tartani a munkatársakat az irodáktól és a digitális helyszínektől, hogy még véletlenül se tudjanak szervezkedni és kollektíven jobb fizetést vagy bánásmódot követelni.