Canadian datarun 2022.3 was retired on September 11, 2023. Only one datarun (2023.1) will be available in Canada until the next fall release.

Concentration datapoints (previously known as LQs) have been made widely available across multiple Table, Map, and Comparison reports (in the US). Now users can easily rank regions, occupations, and more by their preferred supply and demand concentration metrics.

You can read more about how we define concentration in the KB article here, and below are all the reports where you can access these powerful datapoints.

With the 2023.3 datarun, Lightcast fixed a bug that misstated "self-employment" counts in the 2022.4, 2023.1, and 2023.2 dataruns. This bug had overstated the number of self-employed individuals in large counties within each state, while understanding the number of self-employed individuals in small counties.

As a result, any comparisons to to prior dataruns will reflect these movements, with self-employment totals decreasing for large counties and increasing for small counties. Lightcast recommends shifting analyses to use 2023.3.

ISCO, also known as the International Standard Classification of Occupations, is a system developed by the International Labour Organization (ILO) to categorize and classify various occupations globally. It provides a standardized framework for organizing and comparing different types of jobs across countries and industries.

The ISCO classification system is designed to facilitate the collection, analysis, and dissemination of occupational data. It helps in understanding the composition of the workforce, analyzing employment trends, and comparing occupational structures between different countries or regions.

Now all global job postings are available by ISCO search.

This release includes the update to NAICS 2022 taxonomy, as well as the addition of OEWS wage and employment data for 2022.

The 2023.1 release has been retired and is no longer available in the tool.

Lightcast has updated its classification of companies in Canada, following on from work done earlier this month in the United States. With this, Lightcast will display better normalized company subsidiaries, and have better coverage of small employers. Posting counts for employers may shift slightly from previous analyses due to these improvements.

This release includes the update to NAICS 2022 taxonomy, as well as the addition of OEWS wage and employment data for 2022.

Canadian datarun 2022.3 will be retired on September 1, 2023. At that time, only one datarun (2023.1) will be available in Canada until the next fall release.

The release of Lightcast Sectors brings Lightcast's research expertise directly into the Analyst platform US data. Each sector is built as a collaborative effort between Lightcast researchers and external experts, and provides a way to research and quantify job posting data for a specific, often niche segment of the labor market.

Lightcast Sectors are posting-based, rather than standard groups of occupations or skills or industries.

The initial release of Lightcast Sectors includes:

Learn more in this article.

For details on the datarun, see this article.

On June 15, 2023, updated Canadian data was released in beta to customers. With this release, Canadian occupations are updated to the most recent taxonomy: NOC 2021. See here for more details.

Two notable changes to the taxonomy and tagging:

This Broad Occupational Category has decreased significantly, with many of the roles moving to other categories. This is reflected in both employment and postings data.

For a crosswalk of changes, see here.

Users now have the ability to get more granular job postings results with the new advertised salary filter, available in the left side bar of all job posting reports.

The default option is to include all job postings in your results, but now you can limit your results to only those job postings with salary observations. Then you’ll be given the additional option to narrow your results by an annual or hourly range.

For more details on how we calculate advertised salary in job postings, see our job postings methodology article here.

A Location Quotient (LQ) is a way to quantify how concentrated a characteristic of a particular region is compared to the nation. It is a powerful datapoint, but its name has often been an educational barrier that prevents many users from quickly understanding its value. That's why we're bringing clarity to the matter by removing the name "Location Quotient" altogether and renaming it to be more descriptive of the regional characteristic it's calculating.

You can access these datapoints in a number of table, map, and comparison reports. If you'd like to learn more about the subject, check out our Knowledge Base article here.

Lightcast has updated its classification of companies in the United States. With this, Lightcast will display better normalized company subsidiaries, and have better coverage of small employers. Posting counts for employers may shift slightly from previous analyses due to these improvements.

Lightcast updated its job postings feed, resulting in a decrease in total postings for March and April of 2023. See here for more details.

Many of you have requested the ability to search job postings by all industries and not just 2-digit or 6-digit. You finally can! Now every level of the standard NAICS taxonomy is searchable in all job posting reports! (See the difference between Lightcast NAICS and standard NAICS in the article here).

In addition, the Top Industries ranking in Job Posting Analytics/Competition now has a level selection so that you can specify the industry level of interest without starting over in the report setup page.

We’ve introduced a new filter to the Profile Analytics report that lets users filter their data by graduation year.

This filter is particularly useful for identifying emerging trends in profile data. Additionally, the graduation year filter can be used in combination with the Institution, Program, and Education Level filters to gain even deeper insights into the data.

For details on the 2023.2 datarun, see this article.

The Job Posting Competition/Analytics summary packet at the top of the report now includes the total number of employers that are advertising for the specific role defined in the search parameters and are therefore competing for the same talent. This is contrasted to the total number of employers that are hiring generally within the region. Now instead of forcing users to go to Job Postings Table or Occupation Snapshot/Overview to find the competition data point, it’s right at the top of the report, ready for users to analyze and benchmark against.

The Company Talent Profile report was improved to enable all SOC levels, not just the 2-digit. This gives users the ability to do company research at a much more granular level. For instance, instead of seeing the employee transition “Gain & Drain” chart for a company like General Electric which spans across several occupations, now users can filter by specific occupations like Mechanical Engineers in order to understand General Electric’s competitive and hiring landscape in detail. Also, the number of companies listed in the Gain & Drain chart has been increased from 50 to 100, giving users more data to analyze at a more granular level.

Salary Boosting Skills have been released in Analyst and Developer!

What are Salary Boosting Skills?
Salary Boosting skills are based on an advanced linear regression model that finds which skills have the largest effect on a salary within a particular occupation. We found that skills with this marker lead to a higher average salary in the selected occupation. Salary Boosting skills appear in the platform as a Yes or No visualized through a “” or “X”

Where can I find Salary Boosting Skills?
Salary Boosting skills can be found in the DDN Skills section in Occupation Overview and Snapshot reports.

Lightcast is pleased to announce the release of the DDN Skills framework in Analyst and Developer! A new occupational view into skills!

What are DDN Skills?
DDN Skills are occupation-specific skill categories. Occupational skill categories describe the relationship between an occupation and a skill. This hierarchy begins with skills that are basic foundations of an occupation, graduating to advanced skills required for more senior or specialized roles that will set job seekers apart.

Occupational Skills:

Where can I find DDN Skills?
The DDN skills framework can be found in the Occupation Overview/Snapshot reports in Analyst and Developer. The DDN skills framework requires at least one occupation as an input and since this report is focused on occupations and requires at least a single occupation before it can be run it is a natural starting spot for DDN skills. We will be working in the coming months to continue to expand where and how DDN skills are used in Analyst and Developer.

How can DDN Skills help me?
Viewing skills to this level of granularity and segmentation can be helpful in use cases such as:

Help students develop skills that improve their salary prospects by focusing on acquiring salary premium skills.

For details on the 2023.2 datarun, see this article.

We changed the underlying model in the Talent Supply by Compensation report in order to ensure coverage of all occupations and improve overall results.

The previous model relied on knowledge, skills, and abilities from ONET to determine occupation similarity. While this was mostly sufficient, we implemented a new model that analyzes skills from job postings over the past quarter. This change has led to more accurate and comprehensive results in the report, improving our users ability to analyze supply by compensation.

We updated the internship filter in all of our posting reports for better control and clarity.

Previously users could filter postings by “Exclude Internships” or “Only Internships” with an intern checkbox. This was confusing for many users because there was no option to include internships, which was the default option for the other reports, such as the Occupation Overview. Now all the posting reports have the additional option and default setting to “Include Internships”, which aligns with the other reports across Analyst.

We have released a revised version of demographics projections (2022-2033)

The 2023.1 run incorporated revisions to census estimates for 2020. In some places, those estimates created a break in the timeseries with 2019, and that break in the series unduly influenced projected in-migration and out-migration. Our new projections include newly released birth and death data from the CDC, which helps to mitigate the influence of the revised 2020 data. This said, use demographic projections with caution. Because of changes to birth, death, and migration patterns during COVID in 2020 and 2021, it is uncertain whether those new patterns represent a change in trajectory (for example, people leaving larger metropolitan areas and working remotely becomes a new normal), or a temporary aberration, and the next few years will look more like the late 2010’s rather than 2020-2021. With data currently available, it is not yet apparent which trends will hold and which will break, and therefore there is more uncertainty in the projected population.

Revision to ZIP- and tract-level employment methodology

This datarun introduced new methodology for our ZIP and tract employment calculations. Our main source of employment data is QCEW, which publishes down to the county level, and we then model that county-level employment down to the ZIP and tract level. In our previous methodology, zip and tract distribution was based solely on DBUSA. While this distribution was generally in keeping with our previous distribution methodology based on Zip Business Patterns released by the Census, there were still shortcomings to this approach, particularly when there were mismatches in NAICS classification between QCEW and DBUSA.

Our new methodology seeks to address these shortcomings. In our new methodology, ZIP- and tract-level employment is grounded in the employment figures produced by LODES, which publishes data ZCTA and tract-level data at the 2-digit NAICS, providing a much more grounded high level estimates. DBUSA is then used to distribute employment below the 2-digit NAICS, but has much more rigid guidelines provided by the LODES data. Note that we do not attempt to match LODES exactly, since there are differences between LODES and QCEW – rather, we use LODES as a control to inform our distribution of QCEW employment, without matching LODES exactly.

Now when you enter a job description into the skills parser, Lightcast will use the skills found in the body of text to suggest associated occupations for you to search!

While there previously were only suggestions for skills and job titles, now there are additional suggestions for SOC, LOT, and O*NET occupations. These are determined using a model that intakes job postings data over the past quarter and analyzes the overlapping skill between occupations.

This new feature should help you find the best occupation to search for when working with tough job descriptions.

Now when you enter an occupation into a search input, Lightcast will suggest similar occupations for you to add to your search!

Occupations are considered similar to one another using a model that intakes job postings data over the past quarter and analyzes the overlapping skills between occupations.

Because the analysis is done at the skill level, similarity is only available at lower occupation levels: 5-digit (SOC), Occupations (LOT), Specialized Occupations (LOT), and O*NET. The similar occupation results are based on the first occupation in your search input, not the subsequent occupations.

Not only can this help you choose the right occupation, it also can help you find a more wholistic picture of the labor market. A person’s set of skills can usually be applied in more than one occupation. And so, including occupations with similar skill sets in your search can help you gain more insight on the potential supply or hidden demand.

We now have an integration between Talent Analyst and Talent Transform in BETA.

Talent Transform is another Lightcast product that helps organizations with job architecture. It analyzes and refines roles by building out skill profiles based on our vast open-sourced skill library and maps these skill profiles to standardized occupation taxonomies.

The integration unlocks benchmarking opportunities for Talent Analyst users by giving them the unique ability to search by the same role names used in their organization.

Lightcast released a new report to help our clients understand career pathways. See feeder and next-step jobs, salary differences between job transitions, and the necessary skills needed to move from one job to the next.

Lightcast has released a new and improved version of our proprietary Lightcast Occupation Taxonomy (LOT). Here’s what we’ve changed:

To highlight a few of those new additions, you can now…

Available now in all of our job posting reports, you can run reports for much more specific date ranges! This will allow you to see how job postings and trends in job posting data are changing much more in real-time.

We officially changed the name of our Global Occupation Taxonomy (GOT) to Lightcast Occupation Taxonomy (LOT).

LOT is a proprietary taxonomy composed of 4 different levels (Career Area, Occupation Group, Occupation, Specialized Occupation). This taxonomy has a 1-1 relationship between levels, allows users to start broadly and then get to a level far more granular than O*NET and SOC, and is also updated at least annually. The frequency with which this taxonomy is updated makes it especially useful for identifying emerging roles and occupations.

You can now filter profiles in Profile Analytics by the highest education attainment level.

You can now filter job postings by Program. When a job posting calls out for a specific degree such as business administration or computer science you can now filter and find those postings. This filter is available in all of our job postings-focused reports.

There’s an easy way in Job Posting Competition to navigate up and down occupation taxonomies, and even across from SOC to ONET to GOT.

Find out the minimum education level required in job postings.

Now you can view remote trends by job, location, company, or skill in Report Builder.

It’s back! Median Posting Duration is now available in all posting reports. It was temporarily removed due to backend changes.

Search our job postings reports with new Skill Categories and Subcategories!

Now instead of having to search through individual skills you can just pick a broad category like “Science and Research” and search all skills associated or use a subcategory and get more detailed and search all skills associated with “Data Analysis.”

Skill categories and subcategories are available in the initial menu of our job postings reports and can be visualized in our Report Builder. We will be adding the ability to browse and search the skill categories and subcategories as well as improvements to how they are visualized and displayed in the future.

Now you can see quickly select your desired timeframe at the report page setup and at the top of the left side bar within several of our reports.

We have improved our Remote Job Posting Filter! In addition to Remote or Non-Remote you can now filter by Hybrid and Unknown. These improvements will help you gain a better understanding of how remote work is changing and impacting your markets.

Ranking markets using Supply (Job Family Employment) and Demand (Postings) concentration indices is now available in Geography Explorer and the Job Postings Table.

Now you can create groups of company names to search for across different reports.

New name. Same data. We’re illuminating the future of work as we help our clients unlock new possibilities in the labor market. Find out more here!