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Mapping Career Causeways

User Guide by Nesta: “This user guide shows how providers of careers information advice and guidance, policymakers and employers can use our innovative data tools to support workers and job seekers as they navigate the labour market.

Nesta’s Mapping Career Causeways project, supported by J.P. Morgan as part of their New Skills at Work initiative, applies state-of-the-art data science methods to create an algorithm that recommends job transitions and retraining to workers, with a focus on supporting those at high risk of automation. The algorithm works by measuring the similarity between over 1,600 jobs, displayed in our interactive ‘map of occupations’, based on the skills and tasks that make up each role.

Following the publication of the Mapping Career Causeways reportdata visualisation and open-source algorithm and codebase, we have developed a short user guide that demonstrates how you can take the insights and learnings from the Mapping Career Causeways project and implement them directly into your work….

The user guide shows how the Mapping Career Causeways research can be used to address common challenges identified by the stakeholders, such as:

  • Navigating the labour market can be overwhelming, and there is a need for a reliable source of insights (e.g. a tool) that helps to broaden a worker’s potential career opportunities whilst providing focused recommendations on the most valuable skills to invest in
  • There is no standardised data or a common ‘skills language’ to support career advice and guidance
  • There is a lack of understanding and clear data about which sectors are most at risk of automation, and which skills are most valuable for workers to invest in, in order to unlock lower-risk jobs
  • Most recruitment and transition practices rely heavily on relevant domain/sector experience and a worker’s contacts (i.e. who you know), and most employers do not take a skills-based approach to hiring
  • Fear, confidence and self esteem are significant barriers for workers to changing careers, in addition to barriers relating to time and finance
  • Localised information on training options, support for job seekers and live job opportunities would further enrich the model
  • Automation is just one of many trends that are changing the make-up and availability of jobs; other considerations such as digitalisation, the green transition, and regional factors must also be considered…(More)”.
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