36 karma · joined March 22, 2018
AI helps us analyze the references, and will be developed more as we grow.
The experience and knowledge of the referencer factors into how we calculate the strength of the recommendation.
> So I'm not sure recruiters and hiring managers need more coddling and new tools to target candidates.
At Searchlight, we don't help companies target candidates. Rather, we help them surface the best candidates within their applicant pool.
I hear your opinion that a hiring process should stay between the employer and the candidate. Unfortunately, the reality is that most hiring processes today depend on a more human element, like a referral. We hope to make it possible for people without this access can also gather support around their candidacy.
Thanks for pointing that out! Our sample is just an example and does not show the answers to questions about developmental areas.
> Me just saying "oh yeah, they're great", or only talking about the positives doesn't really help as much as a full set of questions which also include honest downsides/weaknesses.
That's great product feedback, thank you. Our questions do pull out these details, and we'll emphasize that more in the future. For example, our questions include: "What colleague would best complement this person" and "How would you help a future manager set this candidate up for success?"
These recommendations are based on on both quantitative ratings and open-ended questions like working style and ideal environment. We do use tools to help automate the recommendation calculation, but also currently human QA because we want to get these recommendations right when we're early-stage.
> You are as good as what you are aspiring to and putting in the work to become tomorrow
Yes, this is exactly what we believe!
By re-humanizing this process and getting better data around a candidate, we hope that hiring managers will qualify more diverse candidates and think more long-term.