Retention Intelligence: Predict Attrition Before It Shows Up in a Resignation Letter
What This Is Not
Not surveillance software — No keystrokes, no screen monitoring, no email content. The system operates on behavioral signals already present in the work environment.
Not an engagement survey — No questionnaires, no annual rollouts, no response rate problems. Measurement is continuous and does not depend on employee self-report.
Not a replacement for good management — When the system identifies a degradation signal, the response is a leadership intervention. The system tells you where to look. What you do about it is a human decision.
The Measurement Gap in Retention
Annual engagement surveys capture attitudes at a single point in time through self-report — subject to response bias, survey fatigue, and substantial lag. Exit interviews capture reasons for leaving after the decision has already been made. Neither provides continuous, leading-indicator signal that identifies degradation before it manifests.
A Different Measurement Framework
Grounded in expectancy theory (Vroom), demand-control model (Karasek), and burnout research (Maslach). These models describe a progressive degradation pattern with identifiable stages and behavioral markers. Our patent-pending methodology provides continuous behavioral signal detection identifying productivity degradation in early stages, giving leadership weeks of advance warning.
Example: Team productivity degradation pattern detected — 3.2 standard deviations below rolling baseline. Lead time: 6 weeks before the first performance review flagged the issue. Intervention: Workload rebalancing prevented two departures.
Who This Is For
Professional services firms, technology companies, financial institutions, healthcare systems, and any organization where the cost of attrition is high, the labor market is tight, and institutional knowledge is concentrated in hard-to-replace individuals.