Supply is the estimated number of employed people in the workforce that meet your search criteria.
What can I use this data for?
You can use supply data to understand the talent pool for different roles or locations. Across our tools, supply numbers are always for all employers in your searched locations. In other words, we don't show headcount for specific employers.
Acquire: Where do you get your supply data?
In general, we believe national government censuses and labor market surveys provide the most reliable foundation for estimating supply. Censuses are usually conducted every five to ten years, while labor force surveys are often updated yearly. While some of this data is publicly accessible, we often collaborate with local statistical authorities to acquire sources that aren’t available to the general public.
Though we believe that government data provides the best basis for our supply calculations, we also realize that it is not granular enough to estimate supply at the skill level, nor is it updated frequently enough to indicate real-time market conditions.
We also have more than 1.5 billion digital profiles (not limited to social profiles) and are currently conducting new analysis to determine if this additional data set will improve our supply estimates. If we decide to incorporate these digital profiles into our supply calculations, they will be used to augment, not replace, government data.
Organize: How do you prepare your supply data for analysis?
Generally, government entities provide supply data at varying levels of geography and occupation. In order to accurately compare supply figures across countries, we must map all of our data to a standard taxonomy.
To standardize location types, we map supply to the metropolitan statistical area (MSA) or local country equivalent, since this is the level at which governments typically publish supply figures. If a nation’s government does not use a system similar to MSAs to demarcate their country, we aggregate supply data in a way that is comparable.
To standardize occupations, we map local occupational taxonomies to the Standard Occupation Classification (SOC) system, developed by the United States Bureau of Labor Statistics. We believe that the SOC system provides the best framework for our analysis due to its balance of breadth and depth and the fact that it is regularly reviewed by organizational psychologists.
Analyze: How do you calculate supply?
As stated above, we estimate supply at the occupational level using data from national governments’ census bureaus, and labor market surveys. With this government data as an anchor, TalentNeuron has derived a unique and powerful methodology to estimate the Candidate Supply Count at the skills or keywords level by creating an algorithm that leverages and layers in job demand attributes found in job postings from the past year to then estimate the “skill” ratios or distribution for specific occupations.
Deliver: How do you represent supply data?
We represent supply as an estimated number of individuals that match your search criteria.
More about supply:
What countries do you have supply data for?
We provide supply data for the following countries:
- New Zealand
- South Africa
- United Kingdom
- United States
Why isn’t supply data available for my country?
In many countries, government data simply is not available. In others, the data is available, but the coverage within the country is uneven, or the data itself is unreliable. In these instances, we prefer not to provide data at all than to provide data that doesn't meet our standards.
Other times, we have identified sources for a country, but haven’t yet prioritized that country in our roadmap. If there’s a country you’d like to see supply data for, please reach out to your Account Manager.
What location types do you have supply data for?
We calculate supply data at the country, state, and metropolitan statistical area (MSA) level. If your search includes a location that is less granular (e.g. county or city), the supply will be that of the parent MSA
What search filters impact supply?
We are able to provide supply data for some (but not all) of the job attributes in our search experience: function, occupation, title, skills, credentials, experience level and keywords. In other words, adding these filters to your search will change the supply.
We currently do not provide supply figures for education level and employment type. If your search includes either of these attributes, supply is calculated as if those criteria were not part of your search.
Why do you use government data as the basis for supply?
In 2018, we had more than 340 million social profiles in our database, which our data scientists used for numerous analyses. At the time, we concluded that we weren’t comfortable using social profiles as the sole basis for our supply numbers.
Why don’t we trust social profile data on its own? You may remember the story of the 1948 U.S. presidential election from your history or statistics classes. The Chicago Tribune incorrectly called the election in favor of challenger Thomas Dewey over incumbent Harry Truman based on a flawed political poll that included significant sampling errors. Voters were polled by telephone, and at the time, only well-to-do people (who were more likely to vote for Dewey) owned phones. As a result, the sample population did not reflect the true voting population.
When our team of data scientists considered using only social profiles to estimate supply, testing uncovered significant issues with the analysis due to sampling bias. For example, social data does not evenly reflect all potential candidates in a market. Certain types of candidates, like white-collar workers, are far more likely to have professional social profiles than blue collar workers, engineers, and technicians.
Because government entities are much more purposeful in identifying samples that reflect general populations, we use government data as a foundation and overlay patterns derived from thousands of other sources. We calculate supply data using 6-digit Standard Occupation Classification (SOC) codes. Learn more about occupations.
Today, we have more than 1.5 billion digital profiles (not limited to social profiles) and are conducting new analysis to determine if this additional data set will improve our supply estimates. For the time being, we prefer to use government supply data as a foundation and then apply proprietary algorithms based on patterns identified in thousands of other sources. If we decide to incorporate these digital profiles into our supply calculations, they will be used to augment, not replace, government data.
Why don’t you include unemployed people in your supply estimate?
Unfortunately, many countries around the world lack reliable unemployment data. In order to ensure that our supply data is comparable across locations, we exclude unemployed individuals from all of our supply estimations.
Do you include non-citizens in your supply estimates?
Because most government entities include all employed persons irrespective of their citizenship status in their census and labor market surveys, non-citizens are included in our supply estimates. However, we do not have data on the citizenship status of working populations.
Which employment surveys do you use for each country?
Why do different countries show different minimum supply figures?
While using TalentNeuron, you may notice that supply sometimes appears as “<100” or “<50” for certain searches, and that these minimum values differ between locations. We determine a country’s “supply threshold” based on its population and our confidence level in showing smaller supply figures.
What is the SOC system?
The Standard Occupational Classification (SOC) system is a federal statistical standard used by U.S. federal agencies to classify workers into occupational categories for the purpose of collecting, calculating, or disseminating data. All workers are classified into a detailed occupation based on similar job duties, skills, education, or training. These detailed occupations are grouped to form broad occupations, which are rolled up into minor groups and then major groups.