Simplifying Labor Market Complexity
With a comprehensive workforce dataset built on a foundation of world-leading taxonomies.
Simplifying Labor Market Complexity
The labor market is a vastly complex landscape of skills, occupations, and human potential. In recent years technological disruption, global economic shifts, and rapid innovation have added significantly to this complexity. To make sense of this ever-changing world of work, we need a comprehensive workforce dataset that can simplify this complexity. A dataset that is global: enabling apples-to-apples comparisons across the world. A dataset that is granular: helping us to identify niche changes to occupations and skills. A dataset that is responsive: adapting to take account of workforce flux across the world.
Our world-class occupation and skills taxonomies have enabled us to develop exactly this type of comprehensive dataset. You can read more about why we've built these taxonomies and how we built them here. But now we want to show you what they enable us to do - and what they can enable you to do. In the page below, we've used three sectors as examples of how this comprehensive workforce dataset, based on the foundation of our world-leading taxonomies, is able to simplify labor market complexity. Here's what you'll find:
Using the example of R&D in Advanced Manufacturing, we show how our internationally-sourced taxonomies have given us the basis for developing a universal language of workforce data that crosses national boundaries.
Using the example of Cybersecurity, we show how our taxonomies have enabled us to create a workforce dataset that is organized in a way makes sense of vast labor market complexity, and helps us identify niche trends and changes.
Using the example of Clean Energy, we show how our regularly updated taxonomies have given us the ability to build a highly fluid and constantly evolving dataset that responds to change far quicker than official taxonomies and datasets.
Global Data
How our internationally-sourced taxonomies have enabled us to create the world’s most global language of workforce data crossing national boundaries.
R&D in Advanced Manufacturing
Just as today's interrelated world requires a common language for people to be understood across borders, the interconnectedness of global labor markets has created the need for a common language of data to make sense of global workforce changes and enable meaningful comparisons of global trends. The example below shows how we do this, using the Lightcast Occupation Taxonomy as a foundation to identify trends in Advanced Manufacturing Research & Development across ten countries. Using this truly global taxonomy enables us to glean a wealth of international insights, such as: Chart 1: International comparisons of occupation demand in the sector over time. Map: Top hotspots for employer demand in the sector across the ten countries. Chart 2: Cross-country comparisons of the most in-demand occupations in the sector.
Examples of Use Cases for our Global Data
Companies thinking about where to locate their next center can use our global data to identify hotspots of workers in their sector across the world.
Universities or Business Schools looking to attract students can use our global data to see where companies are recruiting for these jobs globally.
Public sector and government organizations can use our global data to compare employment in their area to similar areas across the world.
Granular Data
How our highly detailed taxonomies have helped us build the world’s most granular workforce dataset, making sense of labor market complexity and identifying niche trends.
Cybersecurity
Making sense of vastly complex labor markets requires a highly organized system for classifying data in a hierarchical way that makes it easy to comprehend, as well as the ability to drill down to highly granular details. In short, it must enable us to see both the forest and the trees. With its 28 broad Career Areas and 1,800 Specialized Occupations, the Lightcast Occupation Taxonomy is designed to do this, as is the Lightcast Skills Taxonomy, with its 30 broad Skills Categories and more than 33,000 Specific Skills. The example below uses both taxonomies to give us insights on the Cybersecurity sector, including: Chart 1: A comparison of official occupation taxonomies with our Occupation Taxonomy. Chart 2: The top skills across all the specialized occupations identified by our Taxonomy. Chart 3: The top specialized skills for each of the 12 Cybersecurity Occupations we've identified.
Examples of Use Cases for our Granular Data
Companies trying to understand how the occupations and skills in their workforce relate to the wider labor market can use our granular data to do this.
Universities or Business Schools can use our granular data to get a better understanding of the roles they should be training for in a given sector.
Public sector and government organizations can use our granular data to get a far richer view of jobs and skills in their area than from official taxonomies.
Responsive Data
How our regularly updated taxonomies have enabled us to develop the world’s most responsive workforce dataset that responds to change far quicker than official datasets.
Clean Energy
With labor markets subject to rapid change, a comprehensive language of workforce data needs to be fluid, evolving with the labour market it purports to describe. Whilst most official occupation taxonomies are only updated every ten years, the Lightcast Occupation Taxonomy is updated every two years, meaning that new occupations appear much sooner in the data. Together with the Lightcast Skills Taxonomy, which is updated with new skills every month, we are able to offer a dataset that is genuinely responsive to change, quickly. The example below uses both taxonomies to give us insights on the Clean Energy sector, including: Chart 1: Fastest growing common and specialized skills in the Clean Energy sector. Chart 2: Demand for occupations we've recently added to the Lightcast Occupation Taxonomy. Chart 3: The companies that are leading demand for these new Clean Energy occupations.
Examples of Use Cases for our Responsive Data
Companies looking to understand how which skills are emerging in their market and amongst their competitors can do this using our responsive data.
Universities or Business Schools can use our responsive data to identify the emerging workforce skills that they should be incorporating in their courses.
Public sector and government organizations can use our responsive data to create a foundation for reform of the skills system to ensure future needs are met.
Summary
The data we've shown above is just a drop in the ocean of the data we have. The kinds of insights we've provided above can be replicated far wider than the 10 countries we've shown, far broader than the three sectors we've picked, and far deeper than the national geographies we've shown, down to regional and local labor markets. And the best news is that this data is available to you.
Whether your company is thinking about where to locate its next operation across the world, understand how your workforce relates to the wider labor market, or want to understand which skills are emerging in your market – it starts with Lightcast.
Whether your institution is looking to attract more international students, get a better understanding of the roles you should be training for, or identify the emerging workforce skills to incorporate in your courses – it starts with Lightcast.
Whether your organization needs to compare your area's labor market to similar areas across the world, get more detail on jobs and skills than official taxonomies offer, or underpin the skills system with solid evidence – it starts with Lightcast.
Contact us to discuss how our world-leading taxonomies can help your organization thrive.
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