Three Strong Reasons That You Must Apply Skills Ontology for Workforce Analytics

Companies are now applying Skills Ontology, analytics and data science procedures to workforce analytics. Skill Ontology needs to be part of the Analytics Framework—or at least play a more significant role than it is presently. Here’s why: currently, behavioural skills and competencies are often considered – but this still leaves many spots in the big picture. Without any data or reference to functional or technical skills, the skills profile is technically incomplete –only revealing a fraction of an employee’s talent – and the consequences to the company could be enormous. Why must you apply Skill Ontology to Workforce Analytics? Greater Accountability— Skills Ontology needs to be the Scope of ‘Workforce Analytics,’ since there are greater accountability and emphasis inclined on skills, the impact on the business could be a booster. Skills Analysis is currently placed slightly below the awareness point, as they are perceived as an untouchable quality that cannot be measured in a specific manner. More often, it is found after searching across several locations and formats, such as resumes. HR Analytics can only be relevant if it encompasses Skills Analytics. rnAcquiring Data— Currently, obtaining information about a person’s salary or personal information (e.g., date of birth) is accessible, and the data is readily available. However, data about an individual’s skills are not commonly available – and what is available is unstructured – for example, hidden in resumes, and professional social media profiles. A shift is therefore needed, towards utilizing Skills data which is structured– mapping the depth of functional and technical skills of everyone in every department.rnDeveloping Skills Library and Profiling engine, ensure HR and those working in recruitment, have a tool that is easy to use, and also provides the necessary information to make the right decisions for a business. Data should be detailed and easy to create, use and change, if needed – and should replace the resumes, job descriptions and other data sources. This is what the SLP engine does – storing all the required data in one convenient place. The aim is to have data readily available which can become the central point of all employee engagements and HR activities, including performance appraisals and development planning. As a web-based service, it will not disrupt any existing platforms. Therefore, it is crucial to apply Skills Ontology to People Analytics.