Reduce bias and attract the best candidates with our job description tool 

With Applied's Job Description Tool, you can write engaging ads that help attract the best talent, build diverse teams and create a fair and unbiased candidate experience.

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Fill the gender talent gap with inclusive language

Women are 50% less likely to consider roles that have a coded gender bias.

It’s time for a new, data-driven and ethical approach that addresses the gender imbalance seen across a range of industries, whilst also helping businesses source skilled and valuable talent from a wide pool of candidates. One of the main features of our job description analysis tool is a gender decoder that detects implicit bias in job descriptions.

The words you use in your job descriptions convey subconscious meaning. For example, by using masculine-coded language, you’re signalling that a male would be a better fit. This could range from common words such as 'ambitious' and 'competitive' and industry buzzwords like 'rockstar' or 'hacker'. Research has proven that gender-coded language in job descriptions is a common barrier to creating inclusive workplaces.

How our tool could help close your gender talent gap

Gender-neutral job descriptions lead to a 49:51 ratio of male to female applications.
You are 1.4x more likely to hire a female with feminine-coded job descriptions.
Removing gender bias from your job descriptions could increase the volume of applications by 10-15%

Focus on key requirements

By listing an excessive amount of requirements, you could be needlessly limiting your pool of candidates. This has particular implications for gender diversity in hiring.

Research has found that women tend to only apply for jobs when they meet 100% of the criteria, whereas men will do so when they meet only 60% of the listed requirements.

Our Job Description Analysis Tool will help you strip out unnecessary or low-priority requirements and focus on essential skills. This will encourage a more diverse variety of applicants with a range of transferable skills. Someone who may previously have felt they wouldn’t make the cut could turn out to be your perfect candidate!

Analyse ease of reading

7-8 seconds: The length of time it takes to make a first impression on candidates.

You may be a well-regarded organisation with a fantastic company culture and excellent progression, but if that isn't properly conveyed in your job postings, you won't attract the best of the best.

‍Language in job descriptions should be clear and accessible to ensure a wide applicant pool. If you don't need a PhD to do the job, you shouldn't need one to understand the job description!

Today's job seekers have a world of opportunities at their fingertips, and they don't want to spend their time deciphering overly complex language in job descriptions. Our writing platform assesses job descriptions based on the well-known Flesch reading standards alongside a variety of analytical techniques. This way, your job ad won't exclude anyone who may end up being your dream candidate.

Eliminate biased language

Acronyms and buzzwords are just some examples of common language bias that can introduce ambiguity, signal belonging (or not) and exclude people who are older, younger or from different socioeconomic backgrounds.

Applied wants to ensure that your approach to hiring is based purely on the key skills and attributes that each candidate has to offer. By using inclusive language, you can attract job candidates from a wide range of backgrounds for a fair and unbiased hiring process. Furthermore, by helping managers make the right decisions the first time around, we can help ensure a clear alignment with business goals.

The Job Description Tool uses innovative language analysis, highlighting and removing unconscious biases to craft inclusive job posts, creating a fair and level playing field for all potential candidates.

Stop relying on education

Did you know that education is one of the least reliable predictors of a candidate’s actual abilities? Studies have shown that educational background, as well as years of experience, tell us remarkably little about whether a candidate is the right fit for a particular role.

A person’s educational background can also lead to unconscious bias. For instance, a hiring manager may have an implicit preference for someone because they attended the same school or university.

That’s why at Applied, we ditched educational background as a requirement for jobs. Instead, we take our candidate’s word for it that they can do what is being asked of them. Interested in following our lead? Use the Job Description Tool to discover if your job descriptions are placing too much emphasis on educational requirements instead of key skills.

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