Voluntary employee turnover can have a direct financial impact on organisations. And, at the time of this pandemic outbreak where the majority of the organisations are looking to cut down their employee costs, voluntary employee turnover can create a big concern for companies. And thus, the ability to predict this turnover rate of employees can not only help in making informed hiring decisions but can also help in saving a substantial financial crisis in this uncertain time.

What Drives Job-Hopping?

Acknowledging that, researchers and data scientists from Sapia, a AI recruiting startup, built a language model that can analyse the open-ended interview questions of the candidate to infer the likelihood of a candidate’s job-hopping. The study — led by Madhura Jayaratne, Buddhi Jayatilleke — was done on the responses of 45,000 job applicants, who used a chatbot to give an interview and also self-rated themselves on their possibility of hopping jobs.

The researchers evaluated five different methods of text representations — short for term frequency-inverse document frequency (TF-IDF), LDS, GloVe Vectors for word representations, Doc2Vec document embeddings, and Linguistic Inquiry and Word Count (LIWC). However, the GloVe embeddings provided the best results highlighting the positive correlation between sequences of words and the likelihood of employees leaving the job.

Researchers have also further noted that there is also a positive correlation of employee job-hopping with their “openness to experience.” With companies able to predict the same for freshers and the ones changing their career can provide significant financial benefits for the company.

Regression Model To Infer Job Hopping

Apart from a financial impact of on-boarding new employees, or outsourcing the work, increased employee turnover rate can also decrease productivity as well as can dampen employee morale. In fact, the trend of leaving jobs in order to search for a better one has gained massive traction amid this competitive landscape. And thus, it has become critical for companies to assess the likelihood of the candidate to hop jobs prior to selections.

Traditionally this assessment was done by surfing through candidates’ resume; however, the manual intervention makes the process tiring as well as inaccurate. Plus, this method only was eligible for professionals with work experience but was not fruitful for freshers and amateurs. And thus, researchers decided to leverage the interview answers to analyse the candidates’ personality traits as well as their chances of voluntary turnover.

To test the correlation of the interview answers and likelihood of hopping jobs, the researchers built a regression model that uses the textual answers given by the candidate to infer the result. The chosen candidates used the chatbot — Chat Interview by Sapia for responding to 5-7 open-ended interview questions on past experience, situational judgement and values, rated themselves on a 5-point scale on their motives of changing jobs. Further, the length of the textual response along with the distribution of job-hopping likelihood score among all participants formed the ground truth for building the predictive model.

To initiate the process, the researchers leveraged the LDA-based topic modelling to understand the correlation between the words and phrases used by the candidate and the chances of them leaving the company. Post that, the researchers evaluated four open-vocabulary approaches that analyse all words for understanding the textual information.

Open vocabulary approaches are always going to be preferred over closed ones like LIWC, as it doesn’t rely on category judgement of words. These approaches are further used to build the regression model with the Random Forest algorithm using the scores of the participants. Researchers used 80% of the data to train the model, and the rest of the 20% was used to validate the accuracy of the model.

Additionally, researchers also experiment with various text response lengths, especially with the shorter ones, which becomes challenging as there is not much textual context to predict. However, they found a balance between the short text responses along with the data available and trained the model predicts for even those.

To test the accuracy, the models are evaluated based on the actual likelihood of the turnover with relation to the score produced by the model. To which, the GloVe word embedding approach with the minimum text of 150 words achieved the highest correlation. This result demonstrated that the language used in responding to typical open-ended interview questions could predict the chances of candidates’ turnover rate.

Wrapping Up

Leveraging data from over 45,000 individuals researchers built a regression model in order to infer the likelihood of the candidates leaving the job. It will not only remove the dependency of companies on candidate resumes and job histories but also enhances the process of hiring into a multi-measure assessment process that can be conducted digitally for recruiting.

By Sejuti Das, Analytics India Magazine, 02/08/2020

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Eighteen months after we were all forced abruptly to work from home, it seems as the world cautiously opens up and employers are looking to return workers to offices, having the flexibility to work from home is an increasing demand that people aren’t willing to give up.

Earlier this year, Amazon laid out plans for most of its 60,000 workers in the Seattle area to return to the office later in the year. But, it wasn’t good news to everyone with hundreds threatening to quit.  Microsoft, at Redmond in California, took a softer approach saying employees could work from home, the office or in a hybrid arrangement. Google, Hubspot and Intuit are some of the other companies that have opted for hybrid models going forward.

Others like Atlassian, Twitter, Shopify, Spotify and Slack have decided to become fully remote.  Recently, Slack CEO Stewart Butterfield declared that digital life has moved too far forward during the COVID-19 pandemic for companies to return to former ways of office-based working, even if they wanted to.

While these are some of the world’s most influential companies, it’s a conversation that almost every employer is having right now.

The reality is the demand for remote or hybrid work is fast becoming part of hiring negotiations and compensation packages. For many, work flexibility has become more important than pay. 

This has created a new dilemma for hiring managers that’s much deeper than offering strong commitments on flexibility as part of a job offer. 

If work flexibility is the future, how do you determine who’ll thrive in this setup? 

While it’s easy to guess some of the ideal attributes of a remote worker – that is they need to be autonomous, self-motivated, productive and able to collaborate online – there is another key characteristic that has proven vital to strong performance. 

What we’ve seen from companies that have prioritised remote working for a long time such as Automattic, GitLab, InVision and Buffer is the importance of strong written communication. This is because you are no longer relying on face-to-face interactions that occur naturally or through formal meetings in an office. For remote work to be viable communication needs to be predominantly textual and mostly asynchronous. 

When building a remote organization, Automattic CEO Matt  Mullenweg has said that at some point you realise how crucial written communication is for your success, and you start looking for great writers in your hiring. For this reason, Auttomatic job interviews are conducted via text only.

Mullenweg says the true asynchronous nature of a written interview reflects the remote work reality compared to real time video interviews, which are not scalable in an organisation. I think most of us found that out the hard way during the pandemic. 

So how can companies hire for remote capabilities?

In order to be effective remote and hybrid companies we need to rethink our hiring processes. To be frank, current hiring practices are just not going to cut it. CVs do not reveal the soft skills we need them to, and video is so inherently biased and stressful for candidates that many companies which opted for this early on in the pandemic are abandoning it as a top-of-the-funnel filter. We have several customers who have explicitly ditched video interviews.

The risk of making bad hires when you throw remote work into the equation is higher than if you’re bringing people into an office environment. You need to trust them from day one without any of the  ‘visibility’ you get from seeing someone everyday.

We need a new way of selecting candidates that can accurately identify soft skills like accountability,  autonomy, drive and writing skills. Can a text based interview reveal these qualities, while providing a great candidate experience and being highly relevant to the remote work context?

Mullenweg’s idea of a text only interview is not as radical as some might believe. We do thousands of them every day across the world, for a number of varied companies. We are able to reveal people’s character traits with over 90% accuracy (we know because we ask them).

It’s scientific, based on data and is the only accurate way you can identify both the written communication proficiency and soft skills required to work remotely.

How we do it

Our text interview includes open-ended questions on situational judgement and values, similar to a structured interview. When responses are analysed for skills that pertain to remote work it takes into account a multitude of features related to language fluency, proficiency, personality traits, behavioural traits, and semantic alignment. 

This allows a recruiter to quantify and compare a candidate’s written communication skills immediately as well as their suitability to the work environment. 

The revealing nature of text interviews is not just limited to the skill of writing, but also to the motivation behind expressing something in writing, which requires more effort and thinking than speaking it out. If someone is not motivated to express themselves in writing when a job is on the line, you can assume what it might be like once they are working in a role. 

Conclusion

While many companies are already scrambling to update their remote work policies and rethink their office space needs, if they are not reconsidering their hiring processes as part of this inevitable shift, then they are exposing their company to risk. 

Just because people want to work remotely, doesn’t always mean they can thrive in it. While you may be doing the right thing in offering flexibility for candidates, you also need to make sure that you are doing right by your company by understanding how well these candidates will thrive remotely.

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Wondering how our Ai recruitment assessment tool can identify soft skills in candidates? Find out here.

We’re thrilled to announce that along with our customer Iceland Foods, we won the award for Best In-House Innovation in Recruitment at the 2021 Recruiter Awards in London.

Established in 2002, the Recruiter Awards gala is the UK’s largest event for the entire recruitment community recognising outstanding achievements by agencies and in-house recruiters.

The award recognises the partnership between  Iceland and Sapia that saved their store leaders 24,000 hours a year by implementing transformational change – during a pandemic.

Iceland receives a high volume of applicants – more than 120,000 per month – and faced a crisis in 2020: increased trade and Covid-19 absence meant that surge hiring needed to be automated, without losing the personal touch.

Automation was critical to increase the time store managers had to trade in their stores.

It had to be a simple solution that store managers would understand quickly and trust. The candidate experience had to be fast, inclusive and human. 

The tool needed to work for the candidate market which is as diverse as the general population. The team settled on Smart Interviewer as their solution of choice. 

Candidates have reacted well to the technology, with 99% positive sentiment towards the process  and 77% of candidates more likely to  recommend Iceland as an employer of choice.

There was 5x payback in four months, giving back 8,000 hours to the business and costing less than £1 per applicant.

On top of this there was zero gender and race bias, ensuring people hires are as diverse as the applicant group.

The Judges comments were that: “ this simple, straightforward submission ticked every box by demonstrating the contribution the recruitment function played to the success of their overall business. They also clearly demonstrated thoughtful consideration to the fact that many candidates would be applying for jobs at Iceland following the decimation of their previous career paths, for example, aviation industry employees.”

Read the case study of Iceland and Sapia innovated during the pandemic here.