Summary: The Phase NLP platform identifies and extracts skills from employee resumes and profiles, enabling you to discover gaps and opportunites in your talent pool.
HR and people teams are actively trying to close the skill gaps at their companies. The gap between skills employees have and the skills companies need can lead to lower customer satisfaction, product delays, and loss of revenue. And yet, few companies actually have data about skills in their workforce.
A new study from McKinsey indicates that 9 in 10 executives and managers currently face skill gaps or expect skill gaps in their workforce within the next 5 years. In order to address skill shortages, companies are scrambling to audit and analyze their employee skillsets. This type of benchmark allows businesses to strategically seek out new talent, redirect existing talent, and make efforts to build skills in their workforce.
Conducting a skills audit starts with identifying what skills employees currently have. We know that most companies have already collected this information. The source? Employee resumes.
Today it’s an incredibly tedious and onerous task to go through each resume to identify and document skills. We used our smart match tool to automatically search for and extract skill sets across employee resumes. This is also known as a “semantic search” as we searched for words or statements that contain related language and meaning to a core skill set.
Examples of an automated smart match search of employee resumes:
|Skill sets we searched for||Search results included|
|communications, public relations, speaking||communications, public relations, speaking, speech writing, promotion, journalism|
|data modeling, Python, visualization||data modeling, Python, visualization, predictive modeling, time series forecasting|
For each of the results, we retrieved results that included not only the original language but also related language and concepts. This way, we capture a range of skills that are related to specific tasks or roles but are unique and important to capture individually.
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