To find out how to improve candidate experience using Recruitment Automation, we also have a great eBook on candidate experience.
A major study has validated the ability of AI-powered, chat-based interviews to assess personality traits and job fit.
The analysis of Sapia’s model, which uses text-based communication to interview candidates, has been published in peer-reviewed journal IEEE Access.
The researchers used data from more than 46,000 job applicants who completed an online chat interview and a questionnaire based on the six-factor HEXACO personality model. The HEXACO traits are honesty-humility, emotionality, extraversion, agreeableness, conscientiousness, and openness to experience.
Personality models such as the Big Five and HEXACO are based on the ‘lexical hypothesis’. That is personality characteristics are encoded in language, showing the foundational impact of language in defining identifiable personality traits, the researchers say.
After the applicants’ personality traits were assessed they were asked to provide feedback on the accuracy of how they were described. Also, the researchers found 87.8% of the participants agreed with the description given for each of the six traits.
Behavioural questions
Sapia CEO Barbara Hyman tells Shortlist that in the Sapia interview question, they aim to avoid focusing on hypothetical scenarios that create the potential for candidates to give similar answers to others. Additionally, the interviews are oriented towards behavioral, not situational questions.
Candidates can likely work out what trait is being assessed by each question. However, they can’t “game” their responses with pre-rehearsed scenarios, she says.
Examples of the questions used in the interviews include:
- Which of our values do you really connect with, and why?
- Explain to us the one thing you really want to learn from someone else that you work with and why?
- What is a goal that you’ve set for yourself and what did you learn from achieving it (or not)?
- Sometimes things don’t always go to plan. Describe a time when you failed to meet a deadline or personal commitment. What did you do? How did that make you feel?
- What motivates you? What are you passionate about?
- Not everyone agrees all the time. Have you had a peer, teammate or friend disagree with you? What did you do?
- In sales, thinking fast is critical. What qualifies you for this? Provide an example.
- Would you rather win, or be happy? Explain your answer.
- Tell us about a time when you went above and beyond to do something for someone; how did that make you feel?
Sapia: Making recruitment easy!
Candidates respond to the assessment questions with a noticeable sense of intimacy and authenticity, even including emojis in their answers. “The same way they would respond to a friend”, says Hyman.
Finally, she adds that a text-based approach leaves less room for recruiter partiality compared to CVs, psychometric assessments, and video interviews.
Predicting personality using answers to open-ended interview questions, IEEE, June 2020
Source: Shortlist.net.au | Wednesday 15 July 2020 9:21am
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Sapia named top performing HR vendor
Top performing HR vendor
The HR Service Provider Awards 2020 hosted by HRD Mag sets out each year to find the best HR vendors in Australia.
Sapia Awarded A Silver Medal in the Category Of Recruitment Systems & Technology
Taken from the HRD website:
The winners are selected from a pool of submissions from vendors providing an overview of their business or product, insight into their point of difference in the industry, statistics around market share and growth over the past 12 months, and other relevant information such as industry accolades, client testimonials, and the like.
Finding a dependable service provider can be quite a daunting task for HR professionals. From an impressive array of vendors offering their expertise, HR professionals need to choose the one that suits their company’s unique needs.
To assist HR professionals with this challenging task, HRD’s annual Service Provider Awards recognises the industry’s top performers. The Sapia submission was judged by a panel of HR leaders who determined the top performers in this category.
Thank you HRD for recognising Sapia as a top-performing HR vendor in your fourth annual Service Provider Awards report!
About Sapia
Sapia automates interviews so that every applicant is interviewed in-depth and at scale for you. All by using a text chat so that you can get to the best people fast.
Much faster: Candidates are assessed, scored and ranked using Ai, dramatically reducing recruiter time and effort. 90% recruiter time savings, against standard recruiting processes.
Improves candidate experience: An accessible, mobile-first familiar text experience that candidates enjoy with no confronting videos interviews or questionnaires. 99% candidate satisfaction and 90% completion rates.
Inclusive and fair: Blind screening at its best using Ai with the same structured behavioural interview for every candidate. Gender/Ethnicity/Indignity mixes preserved through recruitment stages due to Ai objectively assessing performance/personality, not their background.
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Egy HR-algoritmus Képes Megmondani, Milyen Gyakran Fogsz Munkát Váltani
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.
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Job hopping personalities
In the current world, websites like LinkedIn have become a great platform for people to seek out new job opportunities. Same for organisations.
The Best and The Worst of Social Media
Given the current COVID-19 crisis, almost daily I come across 2 or 3 posts of people seeking to find a job as their company let them go, due to the economic situation.
Such posts are very popular. The power of social media is really unravelled in these times with a clear case multiple strangers coming to rescue to the person who starts the post. This help is extended either in case of connecting for an opportunity or by simply commenting so that more and more see in their personal feeds and the post goes viral.
I am sure many prospective candidates or affected people may have found their job of choice or compulsion with this. Great effort indeed!
But this also brings out the fact that many people (and companies) may be little hasty in making the job decision.
Given that hiring is an expensive process, HR leaders and hiring managers have often struggled with the possibility of the candidate leaving the job in a few months or years from joining.
Problems become more complex with the fact that the current breed of young workers rate company loyalty relatively lower in their ranking of traits of a dream job. A better brand, a better culture or better compensation can sway them to the other side of the door.
Another study found that in some sectors, the average stay in the company is reducing rapidly due to the high attrition.
What are Job Hoppers?
People who move from one job to the other very often are popularly known as ‘Job Hoppers’.
One study says that in 2018, the turnover cost was $680 Billion in the US economy. Here is the link to the study.
As a phenomenon, job-hopping has been an area of significant interest for both industry and academia.
How do you recognise ‘Job Hoppers’?
Now a new study may have found the solution to this problem with the help of Artificial Intelligence techniques.
The study titled ‘Predicting job-hopping likelihood using answers to open-ended interview questions’ scanned through over 45,000+ interview responses to correlate them with personality types using multiple AI techniques to lead to conclusion.
The personality types were identified using the following model –
- HEXACO Personality – Link here
The correlation models used for assessment of the personality types derived from the interview responses with the propensity of job-hopping are below –
The conclusion of the study is –
- Candidates with ‘Openness to Experience‘ personality type on HEXACO are most likely to indulge in job-hopping
- And candidates with ‘Agreeableness‘ trait dominant in their personality type are least likely to indulge in it.
The full study with details of the future work prospects in the area can be found here.
Amitesh Tyagi, Grow Daily, 25/07/2020
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