Why Skills, why now?
Skills provide everyone involved in the acquisition and management of talent a common language and granularity required to articulate the real executional muscle necessary to execute the business strategy.
The labour market economy brings together jobs that require particular activities to be executed with people who have the ability to execute that activity. For a recruiter to understand whether an individual has the ability to execute or function well within a set of activities, they must ‘read between the lines’ of job titles and educational degrees to draw their recommendation.
Textkernel’s team of highly-trained data scientists have created a systematic approach to characterizing both candidate information (cvs or resumes) and job vacancies in terms of sets of skills. Based on our proprietary approach, we have been able to curate a highly enriched, multi-lingual classification system.
Skills Demand Analytics is now live for all countries in which we collect labor market data:
Austria, Belgium, Canada, France, Germany, Italy, The Netherlands, Spain, The United Kingdom and The United States.
Our Textkernel Skills Classification is available for the following languages: English, French, German, Italian, Spanish and Dutch.
I am interested in understanding how skills-based analytics can help my organization to attract, hire and manage the best talent.Skills analytics for Corporate HR
Staffing and Recruitment Agencies
I am interested in understanding how skills-based analytics can help our agency better serve the needs of our corporate clients.Skills analytics for Staffing and Recruitment
1. Get the skill demand analytics you need to inform your business strategy.
While business leaders understand that talent is an important requirement to execute their business strategies, it can often be difficult for recruiters to articulate the actual and anticipated challenges in sourcing and matching talent to meet those demands.
Skills analytics arms you with the insights required to build awareness and manage expectations about reasonable time-to-hire and cost-to-hire for critical business roles.
Skills data allows you to anticipate trends and shifts in the marketplace that might impact your ability to execute strategic shifts in the future. Additionally, you can monitor your industries’ and competitors’ evolving skill demands to stay abreast of their strategic moves.
2. Identify adjacent and related skill sets that can widen your candidate reach.
Skills analytics offers you the ability to identify families of related skill sets. In today’s labor market, in which specific skill sets are in high demand, understanding adjacent and related skill clusters will help you to look for candidates who may have relevant skills despite having different job titles. For corporate HR, this can allow you to re-skill employees so they can pivot into new roles across the organization.
3. Build your own enriched, skills-based candidate talent pool.
Go beyond the analytics and apply the Textkernel skills classification to your own candidate pipeline and existing talent pool. This will provide you with more visibility into the skills your recruitment marketing efforts have captured in the past.
Frequently Asked Questions
1) How does Textkernel define a skill?
Textkernel defines a skill as a trait or capacity that could be associated with an individual person in a variety of professional situations or context.
2) How many skill concepts does the Textkernel Skills Classification cover?
The Textkernel Skills classification entails more than 11,000 skill concepts that categorize over 130,000 synonyms across 6 languages.
3) What process did Textkernel use to collect, assess and classify all concepts and synonyms?
As with building any kind of ontology, we began by taking a wide view on several sources of skill concept information including: CVs/resumes, job vacancies, numerous existing gazetteers and existing taxonomies, online sources such as wikipedia, training and development descriptions and syllabuses from various educational institutions.
We then used statistical techniques and machine learning and distill our list into the most recurring concepts and create a hierarchy of terminology. We assessed relevancy by analyzing actual occurrence of a skill concept across millions of job vacancies and candidate CVs or resumes. Finally, our dedicated quality assurance teams extensively inspects and improves the system to guarantee that the skill extraction reflects human intuition.
4) Does Textkernel use a taxonomy?
We don’t impose a taxonomy or hierarchy on the skills. The reason for this is that a hierarchy would quickly become obsolete as skills evolve. Hierarchies are also very use case-dependant and thus might be more or less relevant depending on the context in which they are used. We have four groups “Professional skills”, “Soft skills”, “IT skills” and “Languages” under which we categorize broadly the skills.
5) How frequently will Textkernel add new skills or update the taxonomy?
We generally release updates every two weeks. These updates contain improvements to the skills repository in any the available languages as well as improvements to the extraction method.
6) Can I suggest new skills?
Textkernel welcomes feedback on our skills concepts and we consult closely with several of our key customers on the continued enhancement of our taxonomy. If you are interested in participating in our Ontology Maintenance program, please contact us for more details.
7) How do I get my candidate database to speak your skills language?
Textkernel provides services that parse candidate documents (CVs/resumes, application letters), and can return this data to you in a structured database that includes the latest skill categories. Interested to learn more about our parsing services that include skill categorization? Contact us.
Or learn more about our high-quality parsing solutions.
8) Can you extract skills information from other information types?
Yes, we can! Textkernel’s Extract! enables organizations to parse any kind of document – turning unstructured data into searchable, structured data sources.
For example, you might want to parse your organization’s historical job vacancy postings to determine how the skills demanded by your own organization have evolved over time.
Together with several forward-thinking organizations, we are in the final stages of releasing a solution that will enable you to parse and analyze skills from documentation such as performance reviews, manager’s assessments, learning and development certifications. If this is something that you would be interested to learn more about, please contact our sales teams.
More questions that haven’t been already answered? Please contact us and we would be pleased to share more information with you.