The CareerTech Challenge Prize, launched by Nesta and DfE in 2019, aims to support the development of new solutions to help people find rewarding future careers. The prize has funded 20 innovators who are developing digital solutions that connect people with data-driven information, advice and guidance to help them navigate the labour market. Solutions are helping users identify their own skills, and the skills needed for a rapidly changing labour market, as well as identifying jobs available in local areas, and providing pathways to prepare for and secure new, future-proof roles.

Learning and Work Institute is conducting research with the prize finalists to explore the process of building these data-driven solutions. At this interim stage of the research, we wanted to share how the new solutions are being developed, alongside the key successes and challenges experienced by prize finalists so far. It’s hoped that wider learning generated from the prize can support decision-makers to build better and more effective data-driven solutions in the future.

How are finalists using data to shape their solutions?

All of the prize finalists are using data from multiple sources, including live jobs postings and educational and skills-based courses, alongside labour market data such as Office for National Statistics (ONS) labour market statistics, Education and Skills Funding Agency (ESFA) course data, O*NET European Skills/Competences and qualification and Occupations (ESCO), to name a few.

By combining a range of different data sets, innovators are able to develop careers advice, skills matching and job search tools that are more tailored for those looking to retrain or change careers. For example, one prize finalist uses aggregated data and details about individuals to build job matches underpinned by individual interest and career ambitions. The resulting job options presented (powered by live vacancy data) not only match individual skills sets but, as far as possible, align with career ambitions and personal interests. People can then apply for roles directly through the tool, reducing the need for users to deviate away from the platform and streamline the search and application process.

Another prize finalist is building a solution focused on identifying where skills gaps in local labour markets exist. The tool then identifies and signposts users to online learning and educational courses that ‘match’ these gaps. It is hoped these ‘nudges’ will support people to build relevant skills in sectors and industries where local demand exists. Initial testing suggests this matching has been highly effective. Others are using data to create ‘skills libraries’ to support those looking for new employment to assess their current skills sets against a range of careers. The idea is to break down barriers around job titles and often impenetrable language used in job postings to support users to understand the skills profiles of a range of careers.

Solutions are also demonstrating how combining skills and labour market data and presenting them in accessible formats can offer high-quality solutions to support job matching. For example, the development of platforms that only surface the most relevant information based on user profiles, actively avoiding ‘data and information overload’ for the user that can be off-putting. This has offered careers advice and training providers a more responsive, manageable and personalised way of searching for opportunities for their clients. In some cases, this has begun to increase the efficiency of some providers who are able to use the tool to sift through a high volume of information quickly.

What are the key successes and challenges so far?

• Partnership working is key to building all data-driven solutions. Prize finalists are building good relationships with local enterprise partnerships, training providers and careers advice intermediaries. Some are working on their solution in direct partnership with specific frontline services who have helped shape the operational aspects of tools. Others have built strong partnerships with data providers which has been key to accessing a wider range of data to support personalisation and geographic coverage.
• Data and AI can appear complex to non-expert audiences. There remains work to do on developing accessible communications that showcase how and why data-driven solutions should be part of careers advice of the future. Several prize finalists have invested time and resources in demystifying terminology around labour market data which has supported people to understand better how these approaches can work. Over the coming months, prize finalists hope to build further buy-in with careers advice providers, as well as job seekers themselves, to support the legacy of their solutions and stimulate take-up across the market.
• Iterative testing is supporting readiness for the market. Product testing has been key to refining, simplifying, and improving their usability and readiness for the market. This has formed an important part of the finalists’ work. This is particularly pertinent for those finalists using AI approaches where taking a ‘test and learn’ approach has supported the generation of desirable and attainable job options in testing. Prize finalists have invested heavily in engaging with jobseekers using their solutions, undertaking interviews to support validity.
• Prize finalists face ongoing challenges in accessing timely, good-quality local labour market data. There are limited sources of open data focused on skills demands, and our finalists have experienced further challenges in accessing good-quality local vacancy data. This has resulted in increased efforts to scope out and secure access to a wider range of skills and vacancy-based data held across multiple data owners. A lack of ‘standard format’ and terminology of job adverts has also presented issues for algorithm-based solutions where key information may go uncoded or is missing. For example, skills requirements or contact details of the employer, which has presented some limits to utility for the end user. Prize finalists have worked hard to overcome data issues, but there is more work to be done, working alongside data owners on access and quality issues.

What next?

The CareerTech Challenge Prize has offered a unique and important opportunity for tech to support the skills and employment sector to navigate an increasingly complex labour market. However, this is only one piece of the puzzle. People in roles at risk of displacement have unique personal circumstances; many have worked in the same industries for decades, having had limited or no experience of retraining or changing careers. It is vital therefore that future solutions work in combination with human-based approaches that are focused on building confidence and skills to navigate the job market. There is no doubt though that tech offers an exciting opportunity to work alongside data-driven solutions that support people to truly envision their working futures.

On Tuesday 23 March 2021 we will be holding an event to unpack the ways in which innovation can help people to navigate the changing world of work. Based on learnings from CareerTech Challenge we’ll be showcasing our platforms and research, inviting experts to discuss key issues facing workers in the future, and announcing the winner and runner-up of the CareerTech Challenge Prize.