The Universal Standard. Derived from real-world postings and profiles.
Our proprietary classification system is composed of 1,800+ Specialized Occupations divided into distinct 4 levels giving you the granularity you require, globally.
The LOT, the standard for understanding occupations across the globe, uses a proprietary classification system of four different levels: career areas | occupation groups | occupations | specialized occupations.
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Career areas (e.g. Healthcare, Finance, Transportation) are the broadest occupational category in the Lightcast Occupation Taxonomy and generally map to different industries. They are designed to be useful in bringing together many similar occupations that are responsible for similar work tasks. Their overarching scope allows for a quick look at broad segments of the labor market. They provide an understanding of the defining skills that are necessary to enter any career within its scope.
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Occupation groups (e.g. Physicians, Banking and Lending, Truck and Bus Drivers) are clusters of occupations that share very similar skill or role requirements. They describe the different “fields” or “disciplines” available in the market for early- or pre-career students. They are subsectors of career areas.
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Occupations (e.g. Physician, Loan Officer, Tractor-Trailer Truck Driver) often overlap with actual job titles. They are designed to align easily with government taxonomies, undergraduate degree programs, and the career aspirations of workers entering a new industry for the first time.
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Specialized occupations (e.g. Surgeon, Mortgage Underwriter, Refrigerated Truck Driver) offer our most granular level of specificity, allowing for the closest look at supply and demand for a given role compared to the market, and also the clearest look at the skills required. They are characterized by unique and value-added sets of skills, roles, and responsibilities, as well as additional education or credentials beyond the minimum requirements of the entry-level role they may extend from.
As we move up in the hierarchy, subsections are exclusive to their associated category. In other words, each specialized occupation is unique to its occupation, each occupation is unique to its occupation group, and each occupation group is unique to its career area. This prevents duplicate or overlapping data when analyzing more than one occupation.
The precision level of the LOT is intentionally designed to be both informative and accurate. It delves deeper into specifics compared to government systems like O*NET and SOC, without delving excessively into the intricacies of individual job titles. The LOT undergoes annual updates, striking a balance between stability and usefulness for longitudinal comparisons, while also promptly capturing newly emerging roles as they formalize within the economy. Read more about how our Lightcast taxonomies are constructed and updated in our ebook: Mapping a Workforce in Motion.
Key benefits:
The Lightcast Occupation Taxonomy provides significantly more granularity than federal or national taxonomies, while maintaining a level of aggregation that allows robust analysis. Users can create meaningful career ladders using Specialized Occupations, showing the skills and credentials required for each.
The Specialized Occupations identify roles that are the same, across employers and geographies, regardless of job title. Job titles can cross occupations (as employers cast a wide net while advertising positions) so the Lightcast Occupation Taxonomy serves to close this language gap.
With a single taxonomy applied globally to postings, profiles, and in relationship with Governmental Labor Market data, you can make truly global comparisons to understand the changing nature of the labor market without relying on a “lowest common denominator” from local taxonomies.
The Lightcast Occupation Taxonomy is updated annually — infrequent enough to make it stable and useful for comparisons over time, but frequent enough to capture new, emerging roles as they formalize in the economy.
How LOT is Unique
Comparative Analysis
