Win more clients.  Work faster.  Make up to 43% more placements.  True cloud software that never lets you down.

Wall Street encourages poor diversity levels with new hiring strategy

For many organisations, staff turnover can prove costly in terms of both time and money

There are many different recruitment processes in the modern world, with the more traditional including recruitment agencies, relying on in-house HR departments, personality testing and various theory-based interview techniques. These more traditional processes are taking a back seat as computer-based algorithms are becoming the norm, but do these create a diverse workforce?

Many are trying to reduce these costs and create an efficient hiring process through the use of computer-based algorithms in the hope of ensuring a loyal and committed workforce. This technique has now become questionable after Wall Street increased its use in its hiring strategy.

This form of recruitment is not new, as companies have used personality tests along with aptitude testing to highlight problem candidates and aid in the creation of a shortlist for final interview for many years; however, the more recent algorithms have the ability to highlight key information and trends about specific individuals that a human resources department simply screening a CV may not notice.

By researching data about past employees, including performance levels, powerhouses such as Wall Street can now ensure that their new employees do not share the same traits as their predecessors. This level of screening will help to ensure a loyal workforce and reduce turnover costs.

Whilst proven to be an efficient hiring process, these algorithms are computer based, meaning somebody has to set the criteria for them to work. Due to most people’s cultural beliefs and subconscious pre-composed stereotypes, this input of data can make the whole process incredibly biased.

A huge issue facing companies using this method is diversity, which is an issue already synonymous with Wall Street. Whilst these algorithms do not necessarily cause a problem with discrimination in demographic terms such as race, gender and age, there is reduced diversity amongst skill set, values, education and upbringing due to the nature of the data patterns they are looking for.

Wall Street already has a poor reputation for only hiring privileged candidates from wealthy families for its top-level positions and often excludes women and minority races. In its hands, a computer-based algorithm hiring strategy will only further perpetuate this trend.

Many studies show that only a small number of educational bodies are being targeted when using this method. This small pool of candidates will increase discrimination, ensuring Wall Street only hires its usual stereotype and resulting in a workforce of typically white, rich, well-educated employees.

Whilst computer-based algorithms can be a good recruiting technique, they should not be relied upon as the sole option; otherwise, many candidates will see themselves overlooked for positions even if they are the stronger candidate.

Join Over 40,000 Recruiters. Get our latest articles weekly, all FREE – SEND ME ARTICLES

Recruiters love this COMPLETE set of Accredited Recruitment & HR Training – View Training Brochure

Comment on this story

Your email address will not be published. Required fields are marked *


Join the IOR to be part of creating excellence in recruiting standards & service