My Startup: Applied

Josh Peachey's picture
by Josh Peachey

Determined to eradicate bias and discrimination in recruiting, Kate Glazebrook and Rich Marr created Applied - a software programme that employers can use to hire the right people for the job, irrespective of their background, upbringing or appearance.

By concealing the information that doesn't really matter for a job application, Applied helps employers remove the bias they weren't even aware of, ensuring that people are fairly hired. 

Founder: Kate Glazebrook, Rich Marr

Founded: 2016

Website: beapplied.com

We spoke to Kate to find out more about Applied.

Kate Glazebrook, Founder and CEO of Applied

What motivated you to start Applied?

My co-founder and I wanted to bridge the gap between what the evidence says about how to hire and what organisations are actually doing. For example, all the evidence says that seeing someone's name and picture can mean you overlook people who don't 'look the part'. Yet most recruiters spend most of their day on LinkedIn, inadvertently doing just that. Additionally, most recruitment platforms are solely focused on how to speed that process up, not how to help you make the best decision. We wanted to tackle that.

Tell us more about the software behind the product

Companies spend billions every year on unconscious bias training (estimated $8 billion by US corporates alone) and yet there's very little evidence that it works. It improves awareness of the issue, which is great, but data show it very rarely translates into changes in behaviour. That's because unconscious bias is hard to retrain out of the brain. We can make an impact if we instead redesign our processes to make it easy to focus on the things that matter, the skills, and not the things that don't, the profile.

Applied removes irrelevant information from applications such as name, address, hobbies and education (both years and institute) which may introduce bias when reviewing candidates and detract from the detail that really matters to perform the job. Candidates are therefore assessed fairly on what they can do, not what they look like.

Additionally, behaviourally-designed algorithms then reshape how people see information to eradicate bias that can creep into an assessment. For example, the platform randomises the sequence of candidate applications to overcome ordering and anchoring effects.

Where are you right now?

Hiring bias is a hot topic right now and we’ve found a nice mix of empirical evidence and bold product design, so there’s a lot of interest right now.  We’re seeing month on month growth so things are pretty busy.

The team behind Applied

What are your aims for the next year?

We want to take what we've learnt working with our pioneering partners to scaling across the economy. There's no shortage of need for platforms that help organisations leverage diverse talent and we're keen to be their first port of call. In addition to scaling our customer base, we're also working hard on the next tier of product features, including our new standalone inclusive job description tool as well as data science on the best way to tie hiring decisions to performance on the role.

What’s been the hardest thing about getting Applied off the ground?

Without a doubt, behaviour change is the biggest barrier. People are so used to evaluating candidates based on their CV, despite decades of research showing that CVs aren’t actually very predictive of ability.

Every new customer is someone that we’ve needed to convince to de-emphasise CVs, or abandon them entirely, from their hiring process. Once they let go of CVs they don’t look back, hiring without them is better, but that initial moment feels scary.

"Applied removes irrelevant information from applications"

Why should more people be using the software?

Applied is helping create more job opportunities for people who would otherwise be eliminated from traditional hiring processes. It means that more people will stand a higher chance of securing work, irrespective of their background.

Employers benefit from improved, streamlined recruitment processes along with the added reassurance that vacancies are being filled by the most appropriate candidate and that unconscious bias isn’t stifling company growth and success.

How much will it cost users? - and why is it worth the investment?

Applied’s pricing is based on organisation size, so it is scalable and accessible from small startups to large enterprises. We focus on enabling higher quality decisions, rather than simply automating existing hiring practices. That improvement in decision quality is measurable and enables savings in other areas such as employee turnover caused by mis-hires, or time wasted interviewing the wrong people.

Our customers keep more of the right people in their hiring pipeline and waste less time interviewing the wrong people. Employee turnover is lower, as are the chances of having to re-advertise the role and onboard another team member.