background
gender
ethnicity
age
education
wealth
circumstances
Most assessment tools don't test how candidates would actually perform in the job
The best way to find someone who’ll thrive on the job is by testing their ability to actually do the job. We make it easy to use work sample based assessments: making sure you filter based on talent not pedigree.
Applied is built around four evidence-based features that ensure you’re hiring bias free.
What you say matters.
Applied helps you to remove bias and stereotype threat from job descriptions. Unlike other text analytics tools that do the same thing, Applied then links your job description language to your actual hiring outcomes. This means you get a picture of the bias that are specific to your organisation, so you can continually improve. If we wanted to be fancy, we'd say we are using Machine Learning.
Missing out on a job is one thing, but missing out and never hearing why is even worse.
Applied automatically shares feedback with candidates, letting them know how they did in the process, and identifies their relative strengths and weaknesses.
For those you hire, having this information documented gives you a head-start on on-boarding and designing tailored training opportunities. For candidates, this information can be invaluable for learning and feeling respected for the time they’ve taken. Applied can even suggest other roles in your organisation that they might be better suited to.
Diversity reporting shouldn't be difficult. Applied is the first recruitment tool to give you:
A real time view of diversity data, so you can see who’s applying to the role, and if any stage is posing a threat to diversity. Then, you get analytics on the performance of different reviewers, helping to harness your hiring teams.
