What are skills?
Skills are the specific abilities or knowledge that an employer needs or prefers a candidate to have for a particular role. We identify skills using the text of job postings.
What can I use this data for?
Skills data can be used for a wide variety of activities, from recruiting to workforce planning. For example, skill demand data can help you understand the types of talent your competitors are looking to hire.
Acquire: Where do you get your skills data?
To identify skills, we monitor job postings from thousands of sources, including job boards, corporate sites, partner feeds, news sites, staffing websites, and applicant tracking systems. Every day, we process an average of 1.3 million job postings in 22 different languages. Learn more about our demand data.
Organize: How do you prepare your skills data for analysis?
Job postings are written in any format the employer sees fit. When data is unstructured like this, it must be cleaned and prepared before it can be analyzed. Cleaning and preparation can include translation, stripping punctuation and special characters, and removing extraneous text not related to the job. We rely on natural language processing (NLP) to identify the presence of skills within a cleaned and prepared job description.
Analyze: How do you calculate skills data?
Within each of the 1.3 million job postings we process each day, we look for any of the 30,000 skills currently in our database, making for roughly 39 million daily computations. Through this process, each job posting is tagged with the skills that it contains, with an average of 14 skills tagged per posting. After identifying the skills within job postings, we can provide counts of skills as well as more advanced metrics.
Deliver: How do you represent skills data?
We typically represent skills data either as a count or a percentage of job postings that match your search criteria and contain a particular skill.
More about skills:
How is your skills database compiled? How do you identify new skills?
We rely on a variety of methods to keep our skills inventory as up-to-date and relevant as possible. Our approaches can be classified as user-driven, research-driven, and automated.
User-driven: We welcome users to report a specific skill that we’re missing or to send us a list of skills they’d like to see added to our database. We review all submissions to determine whether they are relevant and appropriate for all users and can react very quickly to these suggestions.
Research-driven: Our team includes a dedicated group of researchers who proactively identify new skills. These researchers review the syllabi and tables of contents of instructional courses and books, follow new product announcements from major companies, and set alerts to be notified when the media discusses cutting-edge skills, among other things.
Automated: We rely on several fully or partially automated methods to continuously look for new skills. For example, we use advanced natural language processing to examine recurring words and phrases in job postings for potential new skills to add to our database.
How often is your skills database updated?
We continuously add, remove, and modify skills in our database in response to feedback from our users and recommendations from our research team. These revisions immediately affect job postings harvested after the update is made. For example, if we add a skill to our database, that skill will be identified in new job postings going forward.
However, changes to skills can’t be applied to already-harvested job postings until we’re able to reprocess our historical postings. For example, if we remove a skill from our database, that skill may still appear in your search results until all historical job postings are reprocessed.
We regularly reprocess our job posting database in batches and are working on ways to increase the size and speed of these batches to minimize discrepancies when skills are added, removed, or modified.
How do you define each skill in your database?
Because the meaning of a skill can vary by industry and employer, TalentNeuron doesn’t have an official glossary of skills and their definitions. The best way to learn more about what a skill represents is to view that skill within the context of the job postings, which is possible in both Plan and Recruit.
What is the difference between hard and soft skills?
All skills in our system are categorized either as hard or soft skills. Hard skills are typically tools, technologies, and subject matter knowledge, while soft skills are typically occupational traits, like “hardworking”, and work requirements, like “ability to travel.” By default, we display hard and soft skills together, though you can adjust the results to show only hard skills.
Why am I seeing a skill in the results that doesn't align with my search?
The skills you see are those found in job postings that match your search criteria. You may want to make sure the filters you’ve applied (like function and occupation) are relevant to your role.
There may also be instances where our system mistakenly identifies a word phrase from a job description as a skill. Often, this content comes from the sections of the job posting that discuss the company and its values, the job benefits, or advancement potential. We are working on solutions to identify and isolate these parts of job descriptions and remove these false positives from our database. In the meantime, please feel free to report erroneous skills by emailing TNSupport@gartner.com.