Job postings written to attract diverse candidates by using gender-neutral language, removing unnecessary requirements, focusing on essential role responsibilities, and clearly communicating a commitment to inclusion and accommodation.
A skills ontology is the data foundation that makes enterprise-scale skills intelligence possible — without a consistent semantic structure defining how skills relate, every people analytics query produces inconsistent results because 'data analysis,' 'data analytics,' and 'analytics' are treated as different entities rather than equivalent ones. Building or adopting a skills ontology is a foundational infrastructure decision: organizations that build proprietary ontologies gain competitive advantage in internal mobility precision but carry maintenance overhead, while those adopting commercial standards gain speed and ecosystem compatibility but less customization. The most common implementation mistake is adopting a generic ontology without customizing it for organization-specific and industry-specific skills that the generic taxonomy does not adequately represent.
What the research says about employee engagement.
Other ways this term appears across industries and languages.
Common questions about employee engagement.