Why am I here?
We're still working on life's existential questions, but you're here specifically because your organisation uses Applied to hire new team members. Applied's software provides an end-to-end hiring process for your team to attract, assess and hire the best talent while being data-driven and tracking stats for fairness and diversity.
Is Applied just another hiring platform?
Applied is different from other recruitment platforms. While many other systems concentrate on number of applications and speed, our focus is on quality and diversity. We achieve all of this by removing noise (i.e. bias) from applications so you can focus on what really matters. Don't worry, we haven't compromised speed in the process - in fact, our customers have reported saving 2/3 of their time spent recruiting.
What is bias?
We think of bias as your brain's way of making mental shortcuts and allowing you to make more decisions more efficiently. If you were offered a scoop of either chocolate or strawberry ice cream, you could probably give an immediate answer based on existing knowledge and experiences stored in your mind. Your mind likes to use these mental shortcuts, but they can be problematic when used to make more complex decisions, like who to hire. One typical bias is known as confirmation bias, where we confirm.
How do I avoid bias?
It's very hard to avoid bias by yourself, especially when you are unaware you might have one in the first place. Some organisations offer unconscious bias training but research shows this is ineffective in nearly all cases and even has adverse effects in others. A better way to avoid bias in hiring is to assess how candidates would approach specific situations that relate to the role you are hiring for. You'll see in the below chart that the best predictive methods for how well a candidate will fulfil their role is through work sample tests and structured interviews, while the information on a standard CV is the least predictive.
Why can't I just use CVs?
CVs are full of bias and irrelevant information. Where or if a candidate went to university could influence how highly you think of them - especially if they went to your university! The problem is that this has no real relevance to the vast majority of jobs, so why include it? Also you just learned from the chart above, CVs usually contain the least predictive information, such as reference details, years of experience and years of education.
How does Applied fix this?
Your team uses Applied to manage its hiring process. Candidates apply by answering work sample questions. These questions asses their input on real issues that they would face in the role. The responses are then anonymised, chunked, randomised and reviewed by team members before the scores are aggregated to create a leaderboard.
What does all of this mean? Anonymisation is becoming more common in recruitment as teams look to remove the influence that names, gender and age have on the hiring process. At Applied, all parts of the application are anonymised, so the reviewers will never know whose answer they are reading. Chunking means Applied puts all of the answers to individual questions into one bucket to be reviewed, instead of reviewing one candidate at a time. This helps avoid biases such as the halo effect. Randomisation means that the candidates and their questions appear in different orders for different reviewers. This ensures the order in which their seen doesn't impact their scores.
At the end, all of these scores are averaged. The independent nature of the reviews means that you've used crowd wisdom to evaluate candidates, giving them the most accurate score possible.
Trust data, not your gut
Applied makes hiring teams more data-driven than ever before. By shortlisting candidates based on aggregated scores and tracking demographic trends throughout the process, your organisation is able to build a hiring process that gets the best candidate for the job, regardless of their background.
What does reviewing add to the process?
If you're a reviewer of the candidates' application answers, you're really adding value to the process. From the scores at this stage of the process, Applied can predict the best candidate for the role 86% of the time. But don't panic, we still recommend interviewing each candidate in the shortlist to be sure they're the best fit for the role!