Latest Client Algorithm
Latest Client Algorithm
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What they asked us
A leadership team in the aerospace industry came to us with a hiring problem that felt familiar, and expensive. They were bringing people into highly trusted roles — the kind of work where judgment, care, and how you treat the public all show up on the same afternoon — and the usual assessments were not helping them see who would actually thrive here.
They already knew what “good” looks like on a hard day. They wanted that knowledge in the process, not only in the heads of a few trusted people.
What we made together
We took that brief and built it into an application, with the candidate experience as the front door. The algorithm sits underneath. What the person feels is simpler: they are walked, one screen at a time, into a moment they would face in the role they are applying for. Not a riddle. Not a personality quiz. More like being asked, “the request is incomplete and someone is waiting — what do you do next?”
Because the path is calm and clear, people stay with it. And because they stay with it, the application can collect the kind of answers that are actually useful — how someone works, how they choose when the easy path and the right path are not the same, and whether that story holds together from one moment to the next.
Under the surface, the scoring is tailored. Everyday situations and role-specific situations are read together. Each role family has its own idea of “strong,” the way you would not hire a bedside nurse with the same checklist you use for a shift supervisor. Culture is in the same picture: the values this place will not trade away, weighted the way they are lived. Recruiters then receive a full, readable report they can use immediately with the person they’re interviewing — who is close to the work, who is close to the culture, where a conversation will matter most, and who to spend time with first.
If this sounds like your organization
You do not have to be in aerospace for this to be yours. If you can tell us the roles that matter and the values you will not compromise, we can shape a scoring engine and a candidate experience around your world — hospital, studio, public service, high-growth team, or something we have not built yet.
The point of the application, and of the algorithm underneath it, is straightforward: help you find the person who fits the role and the culture. When that match is better, teams stay longer, the work moves with less friction, and the culture you already have is the one that keeps showing up.
If that is the problem you are carrying, we would like to hear it. We will build the algorithm with you.
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