When each hiring manager writes their own JD and each recruiter screens their own way, nothing downstream is comparable. TalentGraph normalizes both ends — the role and the candidate — so hiring data across departments lines up and the process is the same whoever is running it.
The three complaints we hear most from teams in this seat.
One manager writes four bullet points, another writes three pages, and neither maps to a job architecture.
Two candidates for the same role get two different conversations and two incomparable notes.
Time-to-shortlist by department sounds simple until you realise the data was never structured.
Four steps, none of which involve reading a CV that was never going to fit.
The JD Generator drafts a complete, consistently-shaped job description from a one-line brief, ready for the manager to edit.
The Job Parser maps whatever the manager called the role onto the O*NET occupation taxonomy.
Every applicant is parsed and scored against the same structured requirement, with the same fit dimensions.
Structured candidates, structured roles and structured scores — a hiring dataset you can actually report on.
The value for us was consistency. Every req now produces the same shape of data, so the quarterly review stopped being archaeology.
Start with these; the rest of the pipeline is there when you need it.
Bring a handful of real CVs and one open requisition. Ten minutes is usually enough to tell whether this fits how you work.