Bridging the Skills & Productivity Gap with Big Data

The key is to understand the current skills landscape fully. Only by gaining an accurate picture of the UK’s existing talent pool, the emerging skill trends, and future workforce needs, can stakeholders bridge the gap and unlock the UK's potential.  

The Learning and Work Institute’s prediction that the UK will lose £120 billion by 2030 due to skills gaps highlights the urgency of the problem.

However, no unified system for classifying the skills and competencies needed exists. Current systems are outdated and unfit for purpose, offering limited insights into the specific skills required for different jobs.

But there is hope. By leveraging the power of big data, stakeholders can gain a more in-depth understanding of the skills ecosystem and pave the way for a more productive and future-proof UK workforce.

In this article, we explore how big data analysis could help bridge the skills and productivity gap, the crucial role key stakeholders play, and the potential big wins for the UK economy.

Lost in translation: Why there needs to be a better classification system

There are several occupational skills classification systems. Existing schemes include SIC (Standard Industry Classification), SOC (Standard Occupational Classification), NOS (National Occupational Standard) and ISCO-8 (International Standard of Classification of Occupations).

While the Office for National Statistics (ONS) uses SOC, it lacks precision about the specific skills and knowledge needed for individual jobs. As new technologies and jobs emerge, SOC does not keep pace with changes. The result is a fragmented picture that makes it difficult to spot trends, a misalignment between education and the workforce, and inefficient talent planning.

Notably, NOS used to provide detailed competency breakdowns for specific roles. However, the UK Commission for Employment and Skills (UKCES), the coordinating body for the NOS framework, disbanded in 2017. 

The role of skills classification is now spread across at least three or four government bodies, leading to further fragmentation and a distinct lack of clarity. This makes it extremely difficult for decision-makers to classify job roles, identify skills gaps in new and emerging talent, and spot trends in the skills landscape. 

The only clear outcome is that current occupational classifications confuse rather than contribute to our understanding of the scale of the skills shortages problem.

Harnessing big data for big wins

Isn’t it time there was a comprehensive classification framework for understanding skills and core competencies? Like a book’s ISBN (International Standard Book Number) or a product’s EAN barcode (European Article Number), a new, adaptive ‘occupational identifier’ system would accurately map individual capabilities to specific job roles.

The power of big data could be used to analyse vast datasets to map skills by occupation, find discrepancies in skills, and use predictive analysis of demand for new jobs and skills in quasi-real time. 

There are plenty of data sources. Labour market information on websites and portals offers data on positions and requirements, and tools, such as CV matching services, job ads, and professional networks.

Data privacy is not a concern, owing to the focus of the data analysis being on jobs-related skill and competency attributes rather than individual personality traits.

Stakeholder collaboration is key 

While big data offers a powerful lens, it is just one piece of the puzzle. Collaboration is essential to truly use its potential and tackle the skills and productivity gap. Key stakeholders all have a crucial role to play.

Employers need skilled workers to drive innovation and growth. They can contribute by offering work experience placements and internships, providing students with invaluable practical experience.

Educators equip individuals with the right skillsets for the modern workplace. They can play their part by sharing research and insights on emerging skills with government and businesses and adapting training to meet the evolving needs of the labour market.

The government can foster an environment encouraging lifelong learning by setting the national skills agenda and investing in joint initiatives, such as industry-led training. These programmes can combine employer expertise with educational best practices, maximising impact, and benefit.

However, the time is now to break down silos and forge a collaborative approach. Only through a unified effort between employers, educators, and government can we effectively use big data to address the skills and productivity gap.

The future of work – a unified approach 

Imagine a future brimming with innovation, driven by a skilled and productive workforce that drives our global competitiveness. This vision is attainable, but it demands a unified effort. Employers, educators, policymakers and the recruitment industry - including the REC and recruitment agencies - all have a role in supplying access to the type of big data that could help bridge the gap and build a more prosperous and productive tomorrow.

By leveraging big data and fostering collaboration, we can create a more efficient and effective skills classification system, identify emerging skill needs, and ensure our workforce has the capabilities to thrive in the future.