Meet Scott Lydon, he is a good friend of mine who got his first job in the city because of commonalities he shared with an interviewer who went to the same private school he did and spotted it on his CV.
I grew up in a low income community in north London and always felt like two worlds collided went I started working in tech. One the one hand there is this world where I see people creating the world we live in. On the other hand I lived in a community where they lived in a world they had barriers to opportunities to create this world. However, I have always known that there are others like me from my neighbourhood who have high potential to be high performers in tech.
We take such pride at times of the fact that tech startups are so different from traditional industries in their culture, ways of working and building products customers love. However when I look across a trading floor at an investment bank, a law firm and a tech startup there is a startling similarity in the makeup of the workforce.
Distinctly when I look at leadership, investors and staff there is a lack of representation across the board from traditional to new economy companies. Hardly any women, black people or talent from lower income communities.
I believe the main stumbling block causing this is “the traditional CV.” People are subjective and over index on selection bias, based on commonalities in terms of work experience, skills or even past schools attended.
The problem is that these credentials correlate with social economic background, which leaves millions of people worldwide undervalued by a labour market that relies on CVs
Imagine if we could redistribute exceptional people from low income communities in jobs at risk of being displaced like a truck driver or driving instructor and train them to become data scientists, software engineers or UX Designers for example.
How can we assess people more on cognitive abilities and potential rather than past record of employment and skills. The skills largely can be taught and the subjective biases need to be removed completely. Cultural add, values and the cognitive behaviours are the things we need to learn how to assess more using data and technology.
Background should not be a barrier to opportunity for exceptional talent who have potential
In the UK there is 65 million people. Let’s say a quarter of these people are undervalued in this way. That is 16 million people. If even 10% of these people are exceptional. That is over 1 million people without access to pathways to great jobs they would be exceptional at.
Let’s rethink how we find and hire exceptional talent from all backgrounds.
Just a though inspired by Catalyte