When a Manager Retires, Their Judgment Leaves With Them
When an experienced hiring manager retires, the pattern recognition they built over decades disappears. They knew which behavioral signals predicted a fast ramp, which resume lines were misleading, and which profiles thrived under pressure. None of that lives in any system. The applicant tracking system stores who was hired. The HRIS stores how they performed. The reasoning that connects the two is lost in conversations and retirements. A decision trace captures that reasoning as a queryable record, so institutional knowledge becomes something the organization keeps.
Source: "Decision Traces," Saad Bin Shafiq, NODES, 2026. Read it on arXiv.
The knowledge that walks out the door
A veteran manager's judgment is real and valuable, but it is tacit. It was built from years of watching who worked out and who did not, and it exists as intuition rather than as a record. When that person leaves, the organization does not just lose a headcount. It loses the accumulated reasoning behind thousands of hiring decisions, and it starts relearning the same lessons from scratch.
Why no system holds it
Each system holds one fragment. The ATS knows what the candidate looked like on paper. The HRIS knows what they produced. The behavioral assessment knows a score. None of them holds the connection, which is the part that matters. The reasoning that links a screening signal to an outcome is exactly what no system of record captures, so it stays trapped in the manager's head. See how a decision trace connects them.
What a decision trace preserves
A decision trace is a structured record that connects screening inputs, assessment signals, and production outcomes for each hire. Built across systems, it turns tacit judgment into a queryable, auditable record. The organization can ask which signals actually predicted production, instead of relying on whoever happens to remember. The knowledge survives turnover.
What the data made testable
In the study, the moment the systems were connected, a long-held assumption became testable. The carrier's team had required insurance experience for years, and several managers had done so for over a decade. The connected data showed their highest-performing agents were disproportionately the ones without it. The judgment that had felt obvious turned out to be wrong, and only the connection across systems could reveal it. See that finding.
Why this is the real goal
Prediction is part of the value, but the deeper benefit is making institutional knowledge explicit, auditable, and transferable. A team that captures its hiring reasoning as decision traces does not lose it when people leave, and it can correct assumptions with evidence rather than defend them from memory.
Frequently asked questions
What is institutional knowledge in hiring? It is the accumulated, often tacit judgment about which signals predict success in a role, built by experienced managers over years and usually held in their heads rather than in any system.
Why is institutional knowledge lost when people leave? Because the reasoning that connects screening decisions to outcomes lives in no system of record. The ATS and HRIS each hold a fragment, and the connection departs with the person who held it.
How do you capture institutional hiring knowledge? By building decision traces that connect screening inputs, assessment signals, and production outcomes, turning tacit judgment into a queryable record that survives turnover.
Can captured knowledge correct bad assumptions? Yes. In the study, connecting the systems showed that a screening rule the team had trusted for years was anti-predictive, something memory alone would never have surfaced.
Related reading
- What are decision traces in hiring?
- The $17.7M cost of a single hiring filter
- Decision traces: the full research
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