It’s a cliché, but nonetheless true, that as time passes all processes become dated.

Some might need to be thrown out completely. Many more need to be adjusted and refined to keep up as workplaces and ways of working change.

I’m not old enough to remember the recruitment days of Rolodex and faxed documents. But I’ve heard the stories. Paper mountains of resumes teetering on desks. Consultants queuing at the one office fax machine to send their applicants’ profiles to clients.

Who knew that today we’d be communicating almost instantly by email, on our own computers, or sifting through resumes using Applicant Tracking Systems? In the 1980s that would have sounded like something from Doctor Who.

Since then, it’s all slowed down a bit.

Sure, ATSs take a lot of the legwork out of choosing who to interview. But they’ve also led to Resume Optimisation tools to help applicants beat our filters.

How can we avoid picking only the people who are best at gaming the system? How do we know we’re not missing our perfect applicants?

Now AI is taking the hiring process another leap forward. It’s speeding up the more process-driven elements and helping us select interviewees who are more likely to fit into our businesses.

And that means we need to re-examine two elements of that hiring process – the resume and the interview.

First, let’s tackle the resume.

Why resumes aren’t worth the paper they’re written on

Here’s a challenge for you. Find five well-known businesses that don’t ask for a resume on their careers page. Difficult, isn’t it?

Now think about the resumes you’ve seen recently.

I’ve seen resumes that are well-constructed, professionally crafted prose. And others that are complete works of fiction.

You’re as likely to find glaring spelling mistakes, a messy layout, and a shameless plea to be considered as you are a concise summary, an attractive photo and carefully chosen keywords. If you’re really unlucky you get all of these in one “super-resume”.

A quick search on “How are resumes used?” reveals the astounding advice that applicants should “know the facts in detail, as they may be questioned” about them. That just confirms my suspicion that these documents are more like scripts than records of facts.

And, there’s one more thing that recruiters know about resumes, even if they don’t all admit it …

Not one CV is properly read when they’re selecting applicants for interview.

According to research by the Cambridge Network, some recruiters give CVs a six-second speed-read and many recruiters spend just under 20% of their time on a profile … looking at the picture!

Resumes are rarely used correctly or understood properly, by applicants or recruiters. They most certainly do not predict how successful an applicant is likely to be in a role. Instead, they’re a minefield of potential bias: year of graduation (age bias), name (racial / gender/identity bias), experience in a similar business (confirmation bias), and so on.

So isn’t it better to put some truly intelligent AI for HR to work instead?

How new AI for HR makes resumes redundant

I was astonished to see that 96 per cent of senior HR leaders understand the benefits of using artificial intelligence in their HR and talent functions. But there’s a big gap between recognising the benefits and reaping them.

The canny HR leaders who are already adopting AI techniques will have a head start on their slower rivals.

Some more traditional HR tech providers have evolved their recruitment tools, presenting them as predictive. However, they’re more likely to be creating profiles of your better staff and matching these profiles to the external candidate market, not predicting how they will perform.

Instead, the new wave of HR tech uses well-constructed algorithms, created using a business’s performance data, to provide an unbiased shortlist of candidates far more likely to succeed within the business once hired.

HR tech uses well-constructed algorithms

The algorithm can’t be misled by optimisation techniques, personal feelings or prejudice. Instead, it uses objective data, science and evidence to find the people who are most likely to be a good fit and perform. For this role, in this business. And it will help uncover applicants we might have otherwise overlooked when their resume didn’t match our expectations.

The better solutions work by identifying the defining characteristics of the whole performance group within a business (superstars through to under-performers) and then predicts where external applicants will sit on your performance scale once/if hired.

These advanced solutions then go further via validation reports to prove their better predictions are turning into better new hires. They then use Machine Learning to ensure each unique model continues to learn more about the performance of each business, further improving its predictive power over time.

These two additional steps mean that whilst us humans are still required to make the final hiring decision, we will get better results for our applicants and our businesses. Maybe that’s where the resume might still have a role – as the frame for some reasonable high-level questions to help us understand the person in front of us in more depth, once they’ve got through the first stage.

The most sophisticated algorithms are already outperforming humans in the selection and identification of suitable candidates – and by that I mean candidates who go on to become productive, valuable and loyal employees.

Decision time for CHROs

So, what would you rather have?

– A shortlist of candidates chosen because of what they’ve selected to include in (and omit from) their resume?

Or

– A shortlist of candidates you know are likely to do well in your workforce, because they’ve been chosen using statistically-proven, company-specific performance drivers validated by behavioural science?

Not that tricky a question, is it?

And very easy to see how, with the advent of AI for HR, resumes will soon be as much a part of recruitment as faxes and Rolodex.

Suggested Reading:

https://sapia.ai/blog/cv-tells-you-nothing/

Our colleagues at Cornerstone are wizards at recruitment. They help organisations streamline hiring, so they can find the best people.  Now, you can take Cornerstone ATS further and get ahead by adding Sapia’s interview automation for even faster, fairer and better hiring results.

Remove hiring complexity

There’s a lot expected of recruiters these days and it isn’t easy! From attracting candidates from diverse backgrounds to delivering an exceptional candidate experience, all whilst selecting from thousands of candidates.

The fantastic news is that technology has advanced to support recruiters. Integrating Sapia artificial intelligence technology with the powerful Cornerstone ATS facilitates a fast, fair, efficient recruitment process that candidates truly enjoy.

You can now: 

• Reduce your screening time by up to 90%
• Increase your candidate satisfaction to near 100%
• Achieve interview completion rates over 90%
• And reduce screening bias for good

Sapia + Cornerstone

Gone are the days of screening CVs, followed by phone screens to find the best talent. The number of people applying for each job has grown 5-10 times in size recently. Reading each CV is simply no longer an option. In any case, the attributes that are markers of a high performer often aren’t in CVs and the risk of increasing bias is high.

You can now streamline your Cornerstone process by integrating Sapia’s interview automation with Lumesse.

We’ve created a quick, easy and fair hiring process that candidates love.

1. Create a vacancy in Cornerstone, and a Sapia interview link will be created. 
2. Include the link in your advertising. Every candidate will have an opportunity to complete a FirstInterview via chat.
3. See results as soon as candidates complete their interview. Each candidate’s scores, rank, personality assessment, role-based traits and communication skills are available as soon as they complete the interview. Every candidate will receive automated, personalised feedback.

By sending out one simple interview link, you nail speed, quality and candidate experience in one hit.

Integrate Cornerstone and get ahead

Sapia’s award-winning chat Ai is available to all Cornerstone users. You can automate interviewing, screening, ranking and more, with a minimum of effort! Save time, reduce bias and deliver an outstanding candidate experience.

Experience the Sapia Chat Interview for yourself

The interview that all candidates love

As unemployment rates rise, it’s more important than ever to show empathy for candidates and add value when we can. Using Sapia, every single candidate gets a FirstInterview through an engaging text experience on their mobile device, whenever it suits them. Every candidate receives personalised MyInsights feedback, with helpful coaching tips which candidates love.

Together, Sapia and Cornerstone deliver an approach that is: 

• Relevant—move beyond the CV to the attributes that matter most to you: grit, curiosity, accountability, critical thinking, agility and communication skills
• Respectful—give every single person an interview and never ghost a candidate again
• Dignified—show you value people’s time by providing every single applicant personal feedback
• Fair—avoid video in the first round interviews and take an approach that’s 100% blind to gender, age, ethnicity and other irrelevant attributes
• Familiar—text chat interviewing is not only highly efficient, it’s also familiar to people of all ages  

There are thousands of comments just like this …

“I have never had an interview like this in my life and it was really good to be able to speak without fear of judgment and have the freedom to do so.

The feedback is also great. This is a great way to interview people as it helps an individual to be themselves.

The response back is written with a good sense of understanding and compassion.

I don’t know if it is a human or a robot answering me, but if it is a robot then technology is quite amazing.”

Take it for a 2-minute test drive here > 

Recruiters love using artificial intelligence in hiring

Recruiters love the TalentInsights Sapia surface in Lumesse as soon as each candidate finishes their interview.

Together, Sapia and Cornerstone deliver an approach that is: 

• Fast—Ai-powered scores and rankings make shortlisting candidates quicker
• Insightful—Deep dive into the unique personality and other traits of each candidate 
• Fair—Candidates are scored and ranked on their responses. The system is blind to other attributes and regularly checked for bias.
• Streamlined—Our stand-alone LiveInterview mobile app makes arranging assessment centres easy. Automated record-keeping reduces paperwork and ensures everyone is fairly assessed.
• Time-saving—Automating the first interview screening process and second-round scheduling delivers 90% time savings against a standard recruiting process.

Don’t believe us? Read the reviews! 

See Recruiter Reviews here > 

HR Directors and CHROs love reliable bias tracking

Well-intentioned organisations have been trying to shift the needle on the bias that impacts diversity and inclusion for many years, without significant results. 

Together, Sapia and Cornerstone deliver an approach that is: 

• Measurable—DiscoverInsights, our operations dashboard that provides clear reporting on recruitment, including pipeline shortlisting, candidate experience and bias tracking.
• Competitive—The Sapia and Cornerstone experience is loved by candidates, ensuring you’ll attract the best candidates, and hire faster than competitors.
• Scalable—Whether you’re hiring one hundred people, or one thousand, you can hire the best person for the job, on time, every time.
• Best-in-class—Sapia easily integrates with Cornerstone to provide you with a best-in-class AI-enabled HRTech stack. 

Getting started is easy

Let’s chat about getting you started – book a time here > 

There are some steps we can take to eliminate bias in recruitment and it begins with not relying on CVs as a method of evaluating candidates.

CVs are full of information that is irrelevant to assessing a person’s suitability to do a job. They instead highlight things that we often use to confirm our biases, and draw our attention from other key attributes or aptitudes that might make someone especially suitable for a job.

For example, if a CV mentions a certain university it might pique our attention (a form of pedigree bias). This is problematic, as there may be socio- economic reasons why someone attended a certain university (or did not attend another) and CVs do little to reveal this. Situations like this confirm the bias that lead to it in the first place, compounding bias for these long-term systemic issues.

Additionally, CV data reduces a candidate pool in a way that is not optimising for better fits for the role, by relying on the wrong input data and criteria to find a candidate. Amazon discovered this when it abandoned its machine learning based recruiting engine that used CV data when it was discovered the engine did not like women.

Automation has been key to Amazon’s dominance, so the company created an experimental hiring tool that used artificial intelligence to give job candidates scores ranging from one to five stars.

The issue was not the use of Ai, but rather its application. Amazon’s computer models were trained to vet applicants by observing patterns in resumes submitted to the company over a 10-year period. Most came from men, a reflection of male dominance across the tech industry. As a result of being fed predominantly male resumes, Amazon’s system taught itself that male candidates were preferable. It penalised resumes that included the word ‘women’ as in “women’s chess club captain.” It also downgraded graduates of all-women’s colleges.

Studies have shown systemic unintended bias occurs when reviewing resumes that are identical apart from names that signify a racial background or gender, or a signifier of LGBTQIA+ status. The solution for this has been to remove names or any identifiable data from an interview or CV screening, but these have still experienced bias issues like those discussed earlier.

In order to be truly blind, any input data needs to be clean and objective. This means that it gives no insight into someone’s age, gender, ethnicity, socio-economic standing, education, or even past professional experience.

To truly disrupt bias, recruiters and hiring managers should utilise a new wave of HR tech tools such as Sapia, stepping away from using CV data as a way to determine job suitability.

____________________

We cover this and so much more in our report: Hiring for Equality. Download the report here.