As humans, we often don’t trust what we can’t see and we can’t trust what we don’t understand.
Transparency and explainability are fundamental ingredients of trust, and there is plenty of research to show that high trust relationships create the most productive relationships and cultures.
We are committed to building ethical and engaging assessments. This is why we have taken the path of a text chat with no time pressure. We allow candidates to take their own time, reflect and submit answers in text format. Apart from the apparent errors related to facial expressions, we believe that technologies such as voice to text can add an extra layer of errors. We also refrain from scraping publicly available data such as LinkedIn nor do we use behavioural data like how fast a candidate completes or how many corrections they make. Lastly, we strictly use the final submitted answers from the candidates and nothing else.
Our approach has led to candidates loving the text experience, as measured by the feedback they leave and NPS.
No demographic details are collected from candidates nor used to influence their ranking. Only the candidates answer to relevant interview questions are analysed by our scientifically validated algorithm to assess their fit for the role.
Biases can occur in many different forms. Algorithms and Ai learn according to the profile of the data we feed it. If the data it learns from is taken from a CV, it’s only going to amplify our existing biases. Only clean data, like the answers to specific job-related questions, can give us a true bias-free outcome. We continuously test the data that trains the machine for known biases such as between gender and race groups, so that if ever the slightest bias is found, it can be corrected. Potential biases in data can be tested for and measured. These include all assumed biases such as between gender and race groups that can be added to a suite of tests. These tests can be extended to include other groups of interest where those groupings are available like English As Second Language (EASL) users.
Here are a few examples:
Sapia uses all of these tests and more.
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In June 2022, we announced that, thanks to our partnership with AWS, we now have introduced regional data hosting. This means that customers and their candidates will have increased speed when they use the Sapia platform, and means companies using the platform can have confidence that candidate data is treated in line with data sovereignty legislation, such as the EU’s General Data Protection Regulation (GDPR).
Here is the full list of improvements to data security and sovereignty for Sapia customers.
Sapia’s platform is built on AWS, and is protected by anti-virus, anti-malware, intrusion detection, intrusion protection, and anti-DDoS protocols. We comply with most major cybersecurity requirements, including ISO 27001, Soc 2 Type 1 (Type 2 in progress), and GDPR.
We use AWS’ serverless solution, which can automatically support billions of requests per day. Our sophisticated tech stack includes React.js, GraphQL, MongoDB, Node.js and Terraform.
Regional data hosting
Sapia offers regional data hosting via AWS. All data is processed within highly secure and fault-tolerant data centres, located in the same geography as the one in which the data is stored. All data is stored in and served from AWS data centres using industry standard encryption; both at rest and in while transit.
Availability and reliability
Sapia uses a purpose-built, distributed, fault-tolerant, self-healing storage system that replicates data six ways across three AWS Availability Zones (AZs), making it highly durable. Our storage system is automatic, features continuous data backup, and allows for point-in-time restore (PITR).
You know the common definition of insanity? The one where the same thing gets done over and over again, but the end result doesn’t change? It might not be a big deal when talking about your daily commute, but taking the same old approach to hire key personnel could be an expensive mistake.
Industry studies estimate bad hires cost up to 2.5 times the dollar amount of that person’s salary – and the damage doesn’t end there. Mismatched employees disrupt workplace chemistry, productivity, and profitability.
In response to poor hiring decisions, a growing number of companies now employ predictive screening and hiring models. Engaging predictive analytics and artificial intelligence (AI) – or algorithms that ‘think’ like humans – to help with the legwork historically performed by recruiters.
AI and predictive analytics look at historical data and then apply the learnings to new data to predict future outcomes. So, predictive hiring models can predict who will make it through the interview process, outperform their peers and still be around a few years down the road.
“Today, HR has a seat at the table, and in order to maintain that business partnership, you need to have an analytics framework.”
Andy Kaslow, CHRO, Cerberus
A 2016 survey revealed a strong desire to drive talent acquisition through data and analytics. Two hundred executives at large U.S. firms want technology to play a bigger part in the hiring process. And the clamour for analytics isn’t confined to a younger crowd. Two-thirds of decision-makers who desire data-driven solutions fell between the ages of 45-64.
Although there is a general consensus that data-driven and predictive hiring will make hiring decisions more accurate, many HR professionals still view it as cumbersome and costly to implement.
And it can be true.
Understanding the data needed to make an impact, and figuring out the best techniques and algorithms to use is difficult.
And it can be expensive to hire data scientists, and other key technical personnel needed to implement a full scale HR analytics system.
But, there’s no need to go it alone or to do it all at once.
Rather than setting up in-house HR analytics teams, most companies opt to engage a vendor who specialises in custom predictive screening and hiring models. Finding a vendor that works with you to solve your hiring challenges will significantly cut cost and time to implement.
The crucial first step of any successful project is to define what that success looks like. And implementing predictive hiring isn’t any different.
Have a think about the biggest issue your organisation is facing at the moment that better hiring decisions will solve.
For example, you might have the issue that a lot of new hires are leaving your organisation after a few months. Or you might have a company culture in need of strengthening, and need to hire people who fit with your ideal culture.
When you have honed in on the issue you want to solve, you also need to start thinking about the data that will be required to solve your challenge.
To give you an indication of the type of data you might need, consider these examples;
(These indications are based on the data required if you were working with us at PredictiveHire)
After defining the issue you want to address with predictive hiring, it is time to find a shortlist of vendors that can help you achieve your goal.
Make sure you look for vendors who are able to build predictive hiring models focused on your specific issues, whilst making sure the candidate experience isn’t compromised.
When you have your shortlist of vendors narrowed down, make sure you perform your due diligence. Some vendors will be a better fit for the challenge you wish to solve with your predictive hiring model.
Make sure your shortlisted vendors address these key questions;
All of these questions are important to address to ensure the project’s success.
Implementing new software and processes will always require some level of change management, for example; following the ADKAR or Kotter change management approaches. Make sure you are comfortable with the level of support the vendor will offer you during the roll-out.
Following these three steps will ensure you are off to a good start with your predictive hiring project – and can start reaping the rewards quickly.
Resisting this change may put your company at a distinct disadvantage in the marketplace.
A recent MGI study found that AI can significantly improve the bottom line for businesses willing to incorporate them into their core functions. And the time really is now. Early adopters will enjoy a significant data-advantage in only a few years.
“[Leading businesses] use multiple AI technologies across multiple functions. As these firms expand AI adoption and acquire more data, laggards will find it harder to catch up.”
McKinsey Global Institute, June 2017
In the words of Gartner Research’s senior vice president Peter Sondergaard, “Information is the oil of the 21st century, and analytics is the combustion engine.”
It’s a fact: People lie on resumés, whether the format is a LinkedIn profile, or an old-fashioned document.
Checkster reports that 78% people who applied for a job in 2020 lied about their skills or experience.
Another poll by LendEDU found that 34% of LinkedIn users lie, to some extent, on their profiles. Of that number, 55% said they padded out their ‘Skills’ section. To win roles, it seems, many of us are not above a little trickery.
In 2023, when talent acquisition specialists and hiring managers have hours (and sometimes less) to assess candidates, interview them, and woo them, the risk of resumé skill-creep is magnified.
For a rushed and overworked hiring manager, who is fed up with losing talent and looking bad because of it, the process of vetting becomes less about careful analysis and more about keyword-matching.
All of this culminates in a series of statistics that should not be surprising: According to a 2022 Aptitude Research report of more than 300 HR leaders at major companies, 50% of companies have lost quality talent due to the way they interview and hire.
At the same time, 50% of companies do not measure the ROI of their interview process. One third are not confident in their interviewing game as a whole.
The process is broken.
That same Aptitude Research report examined the average company recruitment funnel, laying out the points at which candidates typically drop out. It found that, on average:
So you might be losing anywhere from 20 to 40% of your talent pool while you spend time vetting resumés and sifting through cover letters.
Aside from the fact that this is a massive time-waster and a prime source of frustration of hiring managers, enforcing the use of resumés is not an effective way to ensure quality of hire.
That’s for two reasons:
Therefore, our over-reliance on resumés creates problems when we go to interview candidates. It’s a classic problem: Overworked hiring managers formulate questions on-the-fly after making cursory glances at candidate submissions.
It’s little wonder that 25% of candidates bail at this point – often, they’re just reconfirming information they’ve already told you about who they are and what they’ve done.
There is an alternative: Structured interviews. Schmidt and Hunter found that structured interviews are the best predictor (26%) of on-the-job success.
The biggest companies are starting to focus more on this.
According to the Wall Street Journal, employers like Google, Delta and IBM are combatting the tight labor market by easing strict needs for college degrees, focussing instead on interview and assessment processes that accurately measure soft skills and behavioral traits.
In its simplest form, the structured interview is based around a predefined set of questions.
These questions are typically behavioural and situational in nature: It’s about giving candidates the opportunity to explore how they think, solve problems, formulate plans, and deal with success and failure.
Therefore, questions like ‘Tell me how you’d respond if [specific situation] occurred’ don’t belong in a structured interview.
Instead, you might ask, ‘Tell me about when something went wrong with work, and you had to fix it. How did you go about it?’
Importantly, the questions you ask must be the same for all candidates. A critical component of the structured interview is fair and balanced comparison of candidates.
If you ask each candidate something different – as so often happens in a fast-paced hourly hiring setup – you can never accurately compare one candidate against another.
In that uncertainty, bias creeps in. It becomes a case of ‘I like this guy, he leans forward when he speaks.’
We’ve developed a handy tool to help you get started with structured interviews today: Our HEXACO job interview rubric. It comes with step-by-step instructions to help you figure out what skills and traits you need based on your open roles and company values.
From there, we’ve supplied you with more than 20 science-backed questions and a scorecard. It’s something simple enough for a busy hiring manager to use.
There is a possible world in which the resumé serves hiring managers as a kind of back-up validation document, used purely to verify the veracity of a candidate’s skills and experience.
In this world, the first stage of your recruitment funnel is the actual candidate interview.
That’s what our Ai Smart Interviewer can do. It’s a conversational Ai that takes candidates through a chat-based interview, using questions tailored to your open roles.
Candidates give their responses – with plenty of time to think – and Smart Interviewer analyses their word choices and sentence structures using its machine learning brainpower.
A candidate may be able to lie about their years of experience, or their knowledge of CSS, but our Smart Interviewer can accurately determine their cognitive ability, language proficiency, and personality traits.
Then it can make recommendations to you on the best candidates, according to the criteria you’ve set – and, at this point, you haven’t even looked at a single resumé.
But, as with traditional processes, you have the final say in who you hire.
In 2023, the name of the game is efficiency. Success will be measured in time saved NOT having to screen, review resumes and cover letters, compile candidate feedback, communicate with candidates, or improve hiring manager interview techniques.
When you’re saving that much time and money, your recruitment (or HR) function has more bandwidth to focus on long-term talent acquisition and people initiatives.
Don’t struggle in 2023 – speak to our team today about how we can solve your hiring challenges.