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Written by Nathan Hewitt

skills-testing

With so many candidates in the market, it’s more important than ever to create an engaging and human candidate experience. But you need to balance that with finding the best talent for your role.

Skill testing can give recruiters a competitive advantage in today’s job market. Candidates who are hired on merit, rather than background, tend to stay longer and perform better over the long term. Here’s how to use skills assessments to fill your open positions, no matter how many applicants you are dealing with.

Your Guide to Skill Testing

What is a Skill Test?

A skills test is an assessment used to provide an unbiased, validated evaluation of a candidate’s ability to perform the duties listed in the job description.

Typically, a skills test asks a variety of questions in different formats to see how candidates perform on-the-job tasks. A good skills test includes questions that are capable of being answered by someone already doing the job and can accurately measure key performance metrics. Questions should also be specifically tailored to relate to the responsibilities of an open position. Many skills tests include immersive experiences, like coding challenges or job simulations, to mimic how a candidate performs when faced with a real-life scenario.

Other types of job-readiness evaluations deploy validated psychometric assessments to identify those in-demand soft skills: things like motivation, conscientiousness, resilience, and emotional intelligence. A personality assessment varies from a skills test in that it predicts how a person will behave in a specific scenario, rather than their ability to complete a task.

While skills test cover task-related abilities, like coding, copywriting, or sales, some pre-employment assessments integrate the less tangible capabilities – things like teamwork and leadership. These qualities are sought after by executives at more than 900 companies, according to a Wall Street Journal survey of executives.

Yet, 89% of those surveyed said they have a “very or somewhat difficult time finding people with the requisite attributes.” Where traditional hiring methods fall short, a skills test can easily clarify a candidate’s true talent.

“Many service companies, including retailers, call centers, and security firms, can reduce costs and make better hires by using short, web-based tests as the first screening step. Such tests efficiently weed out the least-suitable applicants, leaving a smaller, better-qualified pool to undergo the more costly personalized aspects of the process.”

Research by John Bateson, Jochen Wirtz, Eugene Burke and Carly Vaughan via Harvard Business Review

Overall, skills tests can play a critical role in predicting on-the-job success. More so than resumes or job interviews, a skills test can assess the true potential of a new hire to go the distance with the company. Here’s how skill testing works, and why more companies than ever are starting to integrate skill testing into the recruitment and hiring process.

How Skill Testing Works

Skill testing works best when the questions being asked are specifically crafted to the role and needs of the team hiring the new candidate. In designing a skills test, combine different types of questions to get a 360-degree view of how a candidate will perform in different scenarios.

There are a variety of ways to set up a skills test – and we’ll get into the mechanics of how to actually run the assessment in the next section. But, designing a thoughtful aptitude test takes some initial foresight on behalf of the hiring manager and team.

Research by Deloitte suggests this sample process for selecting and implementing skill testing questions:

Define the “human elements” needed to perform the job
Compile questions that will measure and predict these human elements
Use the data gathered by the skills assessments to empower the next round of the screening process
Post-hiring, evaluate the efficacy of the hiring assessment to ensure the questions delivered the best result.

Ultimately, the best use for a skills assessment is to help recruiters move away from the resume and allow candidates to prove they are the real deal. Crafting the right series of questions should be a collaborative process between the recruiting team and the team hiring the new employee. Here’s how these teams can set up and run a skills test.

How to Set Up and Run a Skill Test

In designing a skills test or pre-employment assessment, there are a few specific steps to take in order to thoughtfully structure your questions.

Based on our work with over 8,000 customers, we recommend following these best practices in setting up and running your skills test. These tips can help with candidate engagement and lead to high rates of completion.

Your skills test should include a minimum of six questions; somewhere in the eight to ten range is best.
At least a few questions should require text answers; start with a text-based response in the first question, rather than a video or immersive question.
Include an “immersive” style question, in which the candidate edits a document, spreadsheet, or presentation.
To retain a candidate over the entire experience, start with easier questions and build up to more difficult ones later in the assessment.
Try to minimize the use of timers to account for technical difficulties and give the candidate the best chance of success.

We also suggest that video responses not be timed; there are too many technical issues that can result from a candidate trying to film a one-way video interview. If you do wish to set a time limit, make sure it’s at a minimum of five minutes.

Running a skills test through Vervoe, or any other platform, is relatively straightforward. Vervoe’s skills assessments let you select questions from a library of assessment tools, or design your own questions based on the specific needs of your company. The Expert Assessment Library offers questions and trials created by experts in their fields, meaning they have at least 3+ years of experience in their specific area of expertise. You can preview questions from any of the assessments and add them seamlessly through the Vervoe platform.

Now that you know how to set up an assessment, when should you deploy this tool during the hiring process?

Using Skill Tests During Hiring

Timing is everything when it comes to adding a skill assessment to your hiring process.

Research by Harvard Business Review revealed that skills tests should come early in the hiring process. According to their study, “Many service companies, including retailers, call centers, and security firms, can reduce costs and make better hires by using short, web-based tests as the first screening step. Such tests efficiently weed out the least-suitable applicants, leaving a smaller, better-qualified pool to undergo the more costly personalized aspects of the process.”

Skill tests should be used to screen candidates in, not out. The issue many recruiters face is that the volume of candidates makes it impossible to carefully consider each person’s ability. Smart algorithms and AI tools can turbo-charge candidate assessments by scoring results quickly and removing human bias from the equation.

Vervoe’s algorithm scores candidates using a multi-layered approach. Candidates are ranked based on how well they performed, rather than filtered out if they didn’t achieve a certain benchmark. The top candidates easily rise to the top; but no one misses out on being considered for the next round. When used early in the hiring process, skill tests can select a more diverse pool of applicants to continue onto the next phase.

Using Vervoe, you can test relevant skill groups. Results are automatically ranked for you.

Skill Test Examples and Templates

There are many ways to set up a skills test, depending on the position for which you are hiring. Pre-employment skills tests can cover a range of positions: administrative assistant, finance and accounting, and call center reps are just a few roles that companies hire for using skills assessments.

With Vervoe, you can set up immersive, and niche skill tests for roles, including coding

Excel skill tests, coding skill tests, typing skill tests, and other computer skill tests are the most common forms of pre-employment assessments. Some companies focus on questions that are task-related, e.g. “Create a Powerpoint Slide that has a video embedded in the presentation.” Questions can get hyper-specific to test a niche skill, like a coding language, or be posed more broadly to test the general requirements for success at a certain level.

You can create skill tests with Vervoe that reflect the role, including document editing.

Some companies choose to focus on verifying the skills that will help a candidate succeed beyond the immediate position. This approach skews closer to a pre-employment assessment, with questions designed to reveal if a candidate can climb the corporate ladder, adapt in a challenging work environment, or respond under pressure.

For example, one call center rep test included questions such as, “You have an elderly customer on the phone who is having trouble understanding your instructions. A colleague is also trying to transfer a call from a customer you served before, and you have a scheduled follow-up call happening in 5 minutes. How would you handle and prioritize in this situation?”

Using open-ended text questions is a great use of using a skill test to ask structured behavioural interview questions.

Multiple choice, open-ended questions, and pre-recorded video responses are all great ways to see if a candidate has what it takes to do the job well. But, do candidates enjoy answering these types of questions?

Do new hires like doing skill tests?

By most accounts, candidates appreciate the opportunity to showcase what makes them great at their job. Orica, the world’s largest provider of commercial explosives, integrated skill-testing into their interview process to the delight of their job candidates. In revamping the interview process for graduate students looking to join the Orica team, recruiters consolidated their online evaluation components into one platform, Vervoe. The skill assessment combined questions focusing on skills, logic, and values.

An average of 86% of candidates completed the online process, and the reviews were mostly positive. Here’s what the candidates had to say about the skills test:

“The tests required total engagement and thought, and were a clear demonstration of what makes Orica different from any other company.”

“I think the questions were very diverse and it allowed me to showcase myself, my skills and abilities in different ways.”

“It gave me an opportunity to showcase who I am as well as challenge my skills”

This is just one example of how a skill test can change the entire interview process for a potential new hire. In a job market where people spend an average of 11 hours a week looking for a new job, it’s easy to get burned out, fast. Every job description starts to look the same; every interview begins to feel stale.

When given the opportunity to showcase their talent through real-world tasks, job candidates will jump at the chance to be engaged with the job description, rise above their resume, and challenge themselves. Companies that use Vervoe’s assessments experience a 97% candidate completion rate, which is among the highest engagement rates in the industry. Candidates love the opportunity to stand out from the crowd. Even if they aren’t hired, skills testing offers a break from the repetition of the stale interview experience.

What are the benefits of a skill test?

The benefits of a skills test aren’t limited to the candidate experience.

Recruiters looking to hire diverse, high-performing teams with better efficiency and consistency can use pre-employment tests to their advantage. Skills tests are a better predictor of performance than resume screenings or traditional interviews alone. Resume screenings are bad for three reasons. First, studies suggest that it’s common for candidates to lie on their CV. The person you think you’re hiring may not actually possess the qualifications you think they do.

“We just wouldn’t be able to interview 2000 people in two weeks. But what we could do is utilize Vervoe to more accurately and in quite an unbiased way, assess everybody’s application during that period.

Rather than just assess the first 200 [applicants] and maybe hire 150 of them, Vervoe allowed us to actually assess all 3000 applicants in a two week period and still be able to select the best 150.”

Jeremy Crawford, Head of Talent Acquisition at Medibank

Second, resumes only provide a high-level view of a candidate’s credentials and work experience. These items don’t offer qualitative insight into actual on-the-job performance. Coupled with recruiting biases that are built into the process, the third threat is that recruiters are privileging candidates based on background and demographics, rather than talent. Perhaps this is why new hires crash out as often as they do. According to one study, 46% of new hires “fail” within the first 18 months of being hired.

Vervoe's candidate cards show you detailed information about the skills of each candidate.

Skill tests can help take some of the bias out of the interview process, give recruiters a new evaluation metric to consider, and lead to happier, long-term hires. There’s ample evidence to suggest they really do work better than many of the other traditional hiring methods recruiters have relied on in the past.

Do skill tests work?

In our experience, skill testing works better than traditional hiring methods – with some caveats.

Without a doubt, aptitude tests can be used to replace resume screening. This style of sorting through candidates increases the chance that the best candidates will be unfairly eliminated. Good people get screened out, rather than screened in. So-called “pedigree proxies” – resumes and cover letters – are not indicative of job performance, yet they are often the quickest way a recruiter or algorithm can think of to cut down on their stack of candidate resumes.

Skills tests improve time to hire while allowing the hiring manager to see how someone will do the job, before they get the offer. This reduces turnover costs, which add up quickly: the cost of making the wrong hire can be up to 2.5x salary, easily over $100,000. Working with Vervoe’s skills assessments, on the other hand, can help a recruiter identify the best people at under $100 per hire.

The best skills tests, however, need the right formula to help the candidates succeed. Some recruiters focus narrowly on the skills that will help a new hire succeed in the immediate position for which they are hiring. Yet, many CEOs emphasize the importance of soft skills – things like leadership and teamwork.

New hires may end up being disappointed and leaving because they lacked the soft skills needed to adapt to their new team, not necessarily the skills to perform the job. Recruiters must integrate questions into their skill assessment that focus on critical soft skills that predict long-term success. These validated psychometric assessments are key to assessing “culture fit” without defaulting to recruiter bias.

Is skill testing valid?

With any kind of assessment, there’s a common concern that’s quite commonly raised: is this assessment valid?

In summary:

Any test that directly mimics what a person will do on the job can be considered “validated.”
Tests of personality and soft skills are a riskier prospect even when they are “validated,” because they often lack the proper validation required to be EEOC compliant.
Positive candidate experience and perceived fairness are two of the primary reasons why skill testing is an effective and expedient hiring practice.

There are many types of validity, and it’s rare that a test will satisfy every type. Looking specifically at tests for finding job fit, there are a few different types of validity that are particularly relevant, not just to ensure that the hire is a good one, but to ensure compliance with EEOC regulations.

Types of Validity

Face validity
The most basic form of validity, and sometimes the only one that can be obtained when a test is first created. Face validity essentially asks whether the test looks like it’s assessing what it claims to measure.

One example is testing someone’s arithmetic skills. A set of math problems would have more face validity in this instance than, say, a word problem because a word problem is assessing both arithmetic skills and comprehension.
Content validity
For skill tests used in recruitment, the question of validity should be most focussed on this kind of validity. Content validity asks whether the test covers the full range of the construct that it’s supposed to measure.

This means that in any assessment, the group of questions being asked needs to cover a wide enough range of skills, so that the person evaluating can be sure that the results show the candidate is capable of doing the tasks required on the job.
Construct Validity
When people ask if a test is “validated” or has “psychometric validity,” this is the kind of validity that they’re usually talking about. Construct validity asks whether the test actually measures the theory-based construct that it claims to measure.

So, if you’re testing for general cognitive ability or personality, construct validity is absolutely essential, because they are indirectly related to whether someone can perform the job.

But when it comes to testing skills that used directly on the job, face and construct validity are far more important.
Predictive/External Validity
This kind of validity is about whether or not the assessment predicts performance in other situations. So, if someone scores highly on the test, does that mean they’ll perform well on the job?

There’s a big difference between tasks that are assessed without context, and tests reflect the day-to-day skills and tasks someone would need to have to perform the role.

Related: Skill Testing Validity

In all cases where assessments are used, and in every step of the recruitment process, it’s essential that employers track and remain aware of differences in performance that are biased toward particular demographic factors. At Vervoe, we constantly monitor assessments to make sure candidates take tests that are fair, and based solely on skills that reflect how they would perform on the job.

Skill tests vs. interviewing

In conclusion, we’ll leave you with few thoughts on skill tests compared to interviews.

First, interviews, in general, need a total overhaul. Recruiters have been asking the same, outdated interview questions for decades. Many candidates get overwhelmed by the performance anxiety inherent in the interview and may make (forgivable) mistakes. Nevertheless, many recruiters like the security of meeting someone before making an offer.

Many recruiters seek the same insight from a group interview or case study that they would get from an individual skill test. Unfortunately, using these methods can’t give you the same valuable information as a straightforward aptitude assessment. Case studies can be too conceptual; rather than seeing how a candidate will approach the work listed in the job description, case studies ask abstract questions. The goal of asking “how many tennis balls can fit on a Boeing 757” is not to see if the candidate can guess the right answer, but to see how they approach the question and reason through their response.

But this knowledge doesn’t always serve a recruiter with the best predictor of on-the-job success.

Group interviews provide more insight – into a candidate’s teamwork, leadership, and communication, for example. Yet, in a group scenario, extroverts tend to dominate. It can be difficult to see how each candidate performs as an individual while trying to consider the group at once.

In summary, skill testing is all about understanding whether a candidate can do something or knows something. It’s about verifying their ability to go the distance with your company. Pre-employment assessments differ slightly in that they focus on predicting how a candidate will behave in certain scenarios, not what they can do. By combining questions from skills testing and pre-employment assessments, recruiters can get a more accurate picture of the candidate’s ability.

Additional Resources

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This AI Model Can Predict If You Are A Job Hopper Or Not

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.

Some examples of questions asked.

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.

Model accuracy vs minimum text length in words

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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Hiring automation: It’s Time To Use Your Words

This Recruiter Says How You Write and What You Write Can Tell an Employer a Great Deal About Your Fit.

Barbara Hyman believes the most important skill for people looking for a job in the post-COVID world will be the ability to write.

“People who think clearly, write clearly,’’ says the chief executive of the artificial intelligence-powered recruiting firm Sapia, which judges its candidates on the most basic of skills.

The firm, which has big-name backers including Myer family member Rupert Myer, former Aconex founder turned venture capitalist Leigh Jasper, fund manager Dion Hershan and former JB Were partner Sam Brougham, gives every job candidate a first interview by asking them five text-based behavioural questions on their phone that take around 20 minutes to answer.

Then the company’s predictive models assign a “suitability” score to each candidate using over 80 features extracted from their responses and the system specifically precludes the use of names, gender and age to determine the recommended shortlist, removing unconscious bias from the recruitment process.

The company’s technology has already been used by 400,000 candidates looking for roles in retail, healthcare, customer service, hospitality, contact centres and graduate and trainee roles across 34 countries.

Its clients include Qantas, Bunnings, the Iceland Group grocery chain in the UK and Spanish telecoms giant Telefonica.

But Hyman says her biggest target client in the post-COVID world is government.

She believes the economy can only be sustainably reactivated through large-scale job security and that requires redeploying existing skillsets to meet in-demand industries.

“This requires a sophisticated and scaleable solution to find jobs for those whose industries have been decimated by the pandemic and have no jobs to return to. Our solution can immediately activate these job seekers into the new economy, steering them to the jobs they will be good at, she says.

She claims if the government activated this sort of technology for a range of growth industries the economic and social impact would be unprecedented.

“In a healthy economy, the cost benefit in Australia alone is $1bn net benefit (cost) for every 100,000 workers that get back to work one month earlier through reduced welfare payments and increased consumer spending. That is significantly higher when accounting for government subsidies as a result of COVID,” she says.

“A big part of getting back to work is the confidence and the mindset. We are exploring different avenues to allow people to use our chat bot to find their true role in the new economy. This is the vision we are trying to sell to government – you have your own personalised career coach that helps you find the ideal role.”

Hyman said one of the company’s big-name backers Rupert Myer, the chair of the Australia Council for the Arts and an emeritus trustee of The National Gallery of Victoria, had given her “amazing introductions” into the government and university sectors.

“When I came into the business in February 2018 it was running out of money. I had to get a bunch of the existing investors to support me,’’ says Hyman, a former chief human resources officer at REA Group and a human resources and marketing director at Boston Consulting.

Her data science leader at Sapia is Sri Lankan-born Buddhi Jayatilleke, who has a diverse background in machine learning, software engineering and academic research.

The firm has raised $4m in the past 2 years, including bringing in Australian global recruitment and talent management firm Hudson as a strategic investor last year.

“That gave us credibility because the number two recruitment firm in the market believes in what we are doing,’’ Hyman says.

“Whether you like it or not, there is enormous amount we can learn about you in 200 words. Just the very fact we don’t use any secret or behavioural data, you have to build trust from the beginning with your candidate. The completion rates are 95 per cent, the engagement rates are 99 per cent. But the key point is when we give you back your feedback. It is effectively a public service we are performing with this feedback.”

One of the firm’s initial backers was Rampersand, the venture capital firm which has a focus on early growth stage tech businesses.

Rampersand co-founder Paul Naphtali says the firm invested in Sapia for its ability to put data at the centre of a company’s people strategy.

“It’s a massive challenge for a start-up to aggregate the data and build the algorithms that can identify an individual’s suitability to a role quickly and accurately. It was a bold and ambitious plan from the beginning, and Sapia is now well on its way to becoming that data-centric engine,’’ he says.

“The company started with working to turbocharge the recruitment process by quickly identifying the right talent for the right roles.

“It’s taken time to build the tech and the data sets, but it’s paying off as a number of Australia’s leading companies now have Sapia as a default part of the process.”

He says the firm is now entering a new phase “where it also powers internal people management as well as for job seekers, which is obviously very relevant in the current environment”.

Recently in London Sapia was awarded the TIARA Talent Tech Star which honours the businesses globally in the talent acquisition industry.

Source: DAMON KITNEY, The Australian, October 30, 2020

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Algorithmic Hiring to Improve Social Mobility

It is a widely held belief that diversity brings strength to the workplace through different perspectives and talents.

The value is greatest when companies harness the differences between employees from multiple demographic backgrounds to understand and appeal to a broad customer base. But true diversity relies on social mobility and therein lies the problem: the rate of social mobility in the UK is the worst in the developed world.

The root cause of the UK’s lack of social mobility can be found in the very place that it can bring the most value – the workplace. Employers’ recruiting processes often suffer from unconscious human bias that results in involuntary discrimination. As a result, the correlation between what an employee in the UK earns today and what his or her father earned is more apparent than in any other major economy.

This article explores the barriers to occupational mobility in the UK and the growing use of predictive analytics or algorithmic hiring to neutralise unintentional prejudice against age, academic background, class, ethnicity, colour, gender, disability, sexual orientation and religion.

The government wants to promote equal opportunity

The UK government has highlighted the fact that ‘patterns of inequality are imprinted from one generation to the next’ and has pledged to make their vision of a socially mobile country a reality. At the recent Conservative party conference in Manchester, David Cameron condemned the country’s lack of social mobility as unacceptable for ‘the party of aspiration’. Some of the eye-opening statistics quoted by Cameron include:

7% of the UK population has been privately educated.
22% of FTSE 350 chief executives have been privately educated.
44% within the creative industries have been privately educated.
By the age of three, children from disadvantaged families are already nine months behind their upper middle class peers.
At sixteen, children receiving school meals will on average achieve 1.7 grades lower in their GCSEs.
For A levels, the school one attends has a disproportionate effect on A* level achievement; 30% of A* achievers attend an independent school, while children attending such schools make up merely 7% of the general population.
Independent school graduates make up 32% of MPs, 51% of medics, 54% of FTSE 100 chief executives, 54% of top journalists and 70% of High Court judges.
By the age of 42, those educated privately will earn on average £200,000 more than those educated at state school.

Social immobility is an economic problem as well as a social problem

The OECD claims that income inequality cost the UK 9% in GDP growth between 1990 and 2010. Fewer educational opportunities for disadvantaged individuals had the effect of lowering social mobility and hampering skills development. Those from poor socio economic backgrounds may be just as talented as their privately educated contemporaries and perhaps the missing link in bridging the skills gap in the UK. Various industry sectors have hit out at the government’s immigration policy, claiming this widens the country’s skills gap still further.

Besides immigration, there are other barriers to social mobility within the UK that need to be lifted. Research by Deloitte has shown that 35% of jobs over the next 20 years will be automated. These are mainly unskilled roles that will impact people from low incomes. Rather than relying too heavily on skilled immigrants, the country needs to invest in training and development to upskill young people and provide home-grown talent to meet the future needs of the UK economy. Countries that promote equal opportunity for everyone from an early age are those that will grow and prosper.

How are employers supporting the government’s social mobility policy?

The UK government’s proposal to tackle the issue of social mobility, both in education and in the workplace, has to be greatly welcomed. Cameron cited evidence that people with white-sounding names are more likely to get job interviews than equally qualified people with ethnic names, a trend that he described as ‘disgraceful’. He also referred to employers discriminating against gay people and the need to close the pay gap between men and women. Some major employers – including Deloitte, HSBC, the BBC and the NHS – are combatting this issue by introducing blind-name CVs, where the candidate’s name is blocked out on the CV and the initial screening process. UCAS has also adopted this approach in light of the fact that 36% of ethnic minority applicants from 2010-2012 received places at Russell Group universities, compared with 55% of white applicants.

Although blind-name CVs avoid initial discriminatory biases in an attempt to improve diversity in the workforce, recruiters may still be subject to similar or other biases later in the hiring process. Some law firms, for example, still insist on recruiting Oxbridge graduates, when in fact their skillset may not correlate positively with the job or company culture. While conscious human bias can only be changed through education, lobbying and a shift in attitude, a great deal can be done to eliminate unconscious human bias through predictive analytics or algorithmic hiring.

How can algorithmic hiring help?

Bias in the hiring process not only thwarts social mobility but is detrimental to productivity, profitability and brand value. The best way to remove such bias is to shift reliance from humans to data science and algorithms. Human subjectivity relies on gut feel and is liable to passive bias or, at worst, active discrimination. If an employer genuinely wants to ignore a candidate’s schooling, racial background or social class, these variables can be hidden. Algorithms can have a non-discriminatory output as long as the data used to build them is also of a non-discriminatory nature.

Predictive analytics is an objective way of analysing relevant variables – such as biodata, pre-hire attitudes and personality traits – to determine which candidates are likely to perform best in their roles. By blocking out social background data, informed hiring decisions can be made that have a positive impact on company performance. The primary aim of predictive analytics is to improve organisational profitability, while a positive impact on social mobility is a healthy by-product.

An example of predictive analytics at work

A recent study in the USA revealed that the dropout rate at university will lead to a shortage of qualified graduates in the market (3 million deficit in the short term, rising to 16 million by 2025). Predictive analytics was trialled to anticipate early signs of struggle among students and to reach out with additional coaching and support. As a result, within the state of Georgia student retention rates increased by 5% and the time needed to earn a degree decreased by almost half a semester. The programme ascertained that students from high-income families were ten times more likely to complete their course than those from low-income households, enabling preventative measures to be put in place to help students from socially deprived backgrounds to succeed.

What can be done to combat the biases that affect recruitment?

Bias and stereotyping are in-built physiological behaviours that help humans identify kinship and avoid dangerous circumstances. Such behaviours, however, cloud our judgement when it comes to recruitment decisions. More companies are shifting from a subjective recruitment process to a more objective process, which leads to decision making based on factual evidence. According to the CIPD, on average one-third of companies use assessment centres as a method to select an employee from their candidate pool. This no doubt helps to reduce subjectivity but does not eradicate it completely, as peer group bias can still be brought to bear on the outcome.

Two of the main biases which may be detrimental to hiring decisions are ‘Affinity bias’ and ‘Status Quo bias’. ‘Affinity bias’ leads to people recruiting those who are similar to themselves, while ‘Status Quo bias’ leads to recruitment decisions based on the likeness candidates have with previous hires. Recruiting on this basis may fail to match the selected person’s attributes with the requirements of the job.

Undoubtedly it is important to get along with those who will be joining the company. The key is to use data-driven modelling to narrow down the search in an objective manner before selecting based on compatibility. Predictive analytics can project how a person will fare by comparing candidate data with that of existing employees deemed to be h3 performers and relying on metrics that are devoid of the type of questioning that could lead to the discriminatory biases that inhibit social mobility.

“When it comes to making final decisions, the more data-driven recruiting managers can be, the better.”

Bias works on many levels of consciousness

‘Heuristic bias’ is another example of normal human behaviour that influences hiring decisions. Also known as ‘Confirmation bias’, it allows us to quickly make sense of a complex environment by drawing upon relevant known information to substantiate our reasoning. Since it is anchored on personal experience, it is by default arbitrary and can give rise to an incorrect assessment.

Other forms of bias include ‘Contrast bias’, when a candidate is compared with the previous one instead of comparing his or her individual skills and attributes to those required for the job. ‘Halo bias’ is when a recruiter sees one great thing about a candidate and allows that to sway opinion on everything else about that candidate. The opposite is ‘Horns bias’, where the recruiter sees one bad thing about a candidate and lets it cloud opinion on all their other attributes. Again, predictive analytics precludes all these forms of bias by sticking to the facts.

https://sapia.ai/blog/workplace-unconscious-bias/

Age is firmly on the agenda in the world of recruitment, yet it has been reported that over 50% of recruiters who record age in the hiring process do not employ people older than themselves. Disabled candidates are often discriminated against because recruiters cannot see past the disability. Even these fundamental stereotypes and biases can be avoided through data-driven analytics that cut to the core in matching attitudes, skills and personality to job requirements.

Once objective decisions have been made, companies need to have the confidence not to overturn them and revert to reliance on one-to-one interviews, which have low predictive power. The CIPD cautions against this and advocates a pure, data-driven approach: ‘When it comes to making final decisions, the more data-driven recruiting managers can be, the better’.

The government’s strategy for social mobility states that ‘tackling the opportunity deficit – creating an open, socially mobile society – is our guiding purpose’ but that ‘by definition, this is a long-term undertaking. There is no magic wand we can wave to see immediate effects.’ Being aware of bias is just the first step in minimising its negative effect in the hiring process. Algorithmic hiring is not the only solution but, if supported by the government and key trade bodies, it can go a long way towards remedying the inherent weakness in current recruitment practice. Once the UK’s leading businesses begin to witness the benefits of a genuinely diverse workforce in terms of increased productivity and profitability, predictive hiring will become a self-fulfilling prophecy.

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