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Fast Futures

FastFutures is a free learning programme designed to help young people from underrepresented backgrounds find employment with businesses that struggle to attract and hire people from diverse backgrounds.

We were asked to create an inclusive hiring process that fostered diversity but didn't positively discriminate.

We were aware that many of the candidates may be neurodivergent or have learning difficulties and it was important to be able to cater to any accomodations that they needed to make an interview.

They outsourced the hiring to us.


The total project lasted 6 weeks, including operational management. To achieve our goals we;

  • Advertised through our outreach partners to attract hard-to-reach young people: (Street League,, Smart Works).

  • Created and delivered training on diversity, equity, inclusion, unconscious bias, discrimination, and competency interviewing.

  • Used immersive learning techniques to further challenge unconscious and implicit biases.

  • Used technology to allow candidates to request for any accommodations needed to attend the interview.

  • Implemented a blind CV interview process - no CVs were used, interviewers only had access to candidate's contact details

  • Conducted interviews over the phone to further reduce the potential for bias.

  • Used a structured, competency interview process that used inclusive and neutral language and encouraged candidates to use examples from any area of their life to give everyone the same opportunity to succeed.

  • Used a clear scoring system to ensure that candidates were assessed objectively and fairly.

  • Provided an interview team who themselves came from diverse backgrounds.


  • We hired 1,000 people for the programme with a diversity breakdown of 61% female, 58%

    from minority ethnic backgrounds, 55% from low socio-economic backgrounds, 10% LGBTQIA+, and 7% who said they had a disability or learning difficulty.

  • We have now worked on 4 cohorts with FastFutures, delivering 4,500 learners with an overall diversity breakdown of 64% female, 63% from minority ethnic backgrounds, 60% from low socio-economic backgrounds, 11% LGBTQIA and 8% who said they had a disability or learning difficulty.