You can predict employee turnover by watching four signals: engagement scores trending away from their baseline, changes in an individual's normal behaviour, misalignment between a person's role and their natural work personality, and friction between a team and its manager's style. When two or more of these flag at once, the risk of resignation climbs sharply.
Last reviewed July 2026
Losing a key team member is never just an empty desk. It is the lost institutional knowledge, the dip in team morale, the disruption to customers and the cost of recruiting and training a replacement. Exit interviews explain the loss after the decision is final. Prediction gives you time to change the outcome while the person is still in the building.
The signals are there to find. Disengagement is a slow erosion of commitment that shows up in small, measurable ways months before a resignation letter, and organisations that keep their best people are the ones set up to see it early.
Falling engagement is the leading indicator of turnover. Measure it regularly rather than annually, and read trends against each team's own baseline rather than a company-wide average. A department that slides across two consecutive surveys is telling you something, even if its absolute score still looks acceptable.
Then segment. Turnover risk hides in the cuts: people two years past their last promotion, teams under a recently arrived manager, or one personality group whose engagement diverges from everyone else's.
Disengagement shows up as change from what is normal for that individual. A Campaigner who is usually the most vocal person in a brainstorm goes quiet. An Evaluator known for logical rigour starts submitting work without its usual depth. Neither is a performance problem yet; both are psychological signals of withdrawal.
Managers can only spot drift if they know what engaged looks like for each person. This is where work personality profiles earn their keep: they describe what normal actually is for each of the eight types, which makes departures from it visible.
The most overlooked driver of turnover is misalignment fatigue: the slow burnout that comes from consistently working against your natural grain. A Helper stuck in a highly competitive, individualistic sales role will eventually look for a more collaborative environment, however good the pay.
Compare each role's daily tasks with the work personality of the person doing it. Where most of the work runs against natural preference, you are looking at a high churn risk. Often a modest shift in responsibilities is enough to move someone from at-risk back to high-performing.
People leave managers more often than they leave companies. A highly directive leader might be exactly right in a crisis and still drive away a team of Advisors who value autonomy. When one team's turnover sits well above the rest of the organisation, check the compatibility between the leader's style and the team's collective work personality before assuming pay or workload is the cause.
Training leaders to flex their style to different personality types addresses the root cause rather than the symptom.
Compono Engage handles the measurement layer. It maps work personalities, tracks engagement continuously and shows where role fit is breaking down, so the four signals above surface in your data rather than in resignation letters.
Compono Engage tracks engagement and role fit continuously, so churn risk shows up while there is still time to act on it.
Talk to usLook for shifts from that person's baseline behaviour: decreased participation, a sudden drop in productivity, withdrawal from optional meetings or fading enthusiasm from someone previously engaged. Regular engagement surveys and work personality assessments help surface these risks early.
Low or falling engagement scores, a lack of recent career development, poor alignment between a person's work personality and their daily tasks, and high stress or burnout concentrated in one team.
Yes. People whose roles align with their natural strengths are far less likely to look elsewhere, and personality data also predicts which conditions push each type out, so interventions can be targeted instead of generic.
Exit interviews explain why someone has already decided to leave, which is usually too late to change the outcome. Prediction lets you intervene while the employee is still with you, when their concerns can still be resolved.