Employee Exits and Non-Disclosure

You Are Not an Outlier

Invisible Attrition℠ does not distribute evenly across leadership populations.

The exits least likely to trigger succession review, most likely to be recorded as personal reasons, and most likely to leave unmapped knowledge gaps cluster by demographic. That concentration is structural. If you are a woman in leadership in the 38 to 58 window, you are in the population where the pattern is most dense.

This is not an identity argument. It is a concentration argument. The research confirms what many women in this window already sense: the exits that look like personal timing are not random. They share a profile. They share a tenure window. They share a classification pathway that ensures the institution cannot understand what actually happened, long after the woman who made the calculation has moved on.

Understanding where you sit in that pattern is not pessimism. It is precision.

What the Research Says About Women at Your Level

LHH’s 2025 survey of 2,675 executives found that 43% of leaders reported more than half their leadership team turned over in the prior year. That figure does not disaggregate by gender, but the downstream data clarifies who is carrying the concentration.

A 2024 Gartner survey of 200 CxOs found that 56% are likely or extremely likely to leave their current role within the next two years, with 27% reporting likelihood of departure within six months. The same survey found that 67% of these executives report being asked to do more, 58% report their function bears more organizational reliance, and 44% report increased work stress. Gartner’s own analysis found that more tenured executives are more likely to leave than newer ones. The leaders carrying the most institutional knowledge are the most likely to exit. That is the window you are in.

The Gartner framing concludes that organizations should address the causes of turnover, but it does not address why those causes go undisclosed, which leaders are least positioned to surface them, and what happens to the exit classification when the departure occurs. The 56% departure probability is a structural exposure figure. The mechanism producing it, for women at this level, is something the survey was not designed to see.

Miller and Nguyen’s analysis of SP1500 executive data from 1992 through 2022 found that 43% of organizations experience annual leadership loss at rates that erode institutional continuity. The research does not, however, disaggregate the exits that carry the highest cost from the exits that carry the most legible explanations. The two categories overlap significantly in the women in leadership population. The institution sees isolated mobility events, but the woman inside the pattern often knows, without being able to say, that she is not isolated at all.

How Your Departure Gets Recorded

In January 2026, Catalyst published research on 206 women who left the workforce during 2025. Forty-two percent of voluntary exits cited caregiving responsibilities, including childcare costs, as the primary driver. The recommended responses were predictable: schedule flexibility, paid emergency care days, financial subsidies for childcare.

The methodology surveyed women who had already left and asked them why they left. That methodology is structurally blind to what it is trying to measure.

When disclosure carries professional risk, people give safe answers. Caregiving is a socially acceptable exit label. It is precise enough to satisfy the reporting field and vague enough to protect the person completing it. A woman in leadership who exits because she could not sustain cognitive load during a health transition she could not disclose will not write that on an exit survey. She will select the closest available label that carries no professional consequence.

This is not a failure of honesty. It is the rational response of someone who has accurately read the cost of the alternative. She has been practicing that calculation for months, possibly years, before the exit form arrives. The form simply asks her to formalize a decision she has already made, using language the institution designed for its own purposes.

The Catalyst data contains one additional finding that has not been widely engaged. Women from marginalized racial and ethnic groups reported being laid off at 53%, compared to 37% of White women. That gap is not explained by performance data. It reflects a concentration of involuntary exits in the population that also faces the highest barriers to disclosure, the most constrained access to institutional support, and the deepest exposure to the silence that precedes departure. The demographic concentration of exits is not uniform across women in leadership. It is further concentrated in the women least likely to surface strain and most likely to receive an exit classification that forecloses any institutional understanding of what occurred.

When you leave, and if you choose a label that protects you over one that accurately describes what you were managing, that choice is not a distortion of anything. It is what the institution’s system produces when it asks people to disclose the undisclosable.

What the Institution Will Not See

When exits are classified as personal reasons, the institutional process closes. There is no post-departure review, no signal that connects this exit to prior exits in the same population, the same tenure window, or the same organizational layer. Each departure becomes a discrete event. The pattern it belongs to remains unmeasured.

This means that what you carried, how long you carried it, what eroded during tenure, and what was never transferred because no transfer protocol was triggered will not appear anywhere in what the institution files. The succession plan that has your name in it identifies who fills the role after you leave, but it does not identify what degraded before you decided to leave, or how long that degradation had been underway.

LHH found that 56% of executives report burnout, and that exits are concentrated in transformation sectors at 73%. The leaders most likely to be carrying the highest cognitive load are the leaders most likely to exit. When those exits are classified as personal, the institution loses both the leader and any possibility of understanding what happened. What they will show is a departure. Nothing more.

What you were managing does not make it into the conversation. What you produced does. The departure code does not capture the gap between the two.

What This Means If You Are Still Here

The demographic concentration of silent exits is not a signal that you failed to advocate for yourself. It is a signal that the measurement architecture was not designed to see what you are managing.

The instruments the institution uses — exit interviews, engagement surveys, performance reviews, succession matrices — share a common design feature. They depend on you initiating contact, naming the source of strain, or surfacing what you have already calculated it is not safe to surface. They activate after the professional cost of honesty has been reduced to zero, which is to say, after you have already decided. That is too late, and it was designed for a different problem than the one you are living.

Support that works for your situation does not require you to name what you are managing to the institution that employs you. It does not depend on a wellness program you calculated not to use. It does not require a disclosure that changes how you are perceived before you are ready to make that choice. That decision, the calculation of whether it is safer to name what you are carrying or to continue managing it privately, is what Tacere describes: not silence as absence, but silence as strategy.

The exits in this pattern are not unpredictable. They are the end of a very long calculation, made under conditions the institution’s measurement system was not built to observe. You are not invisible because you chose to be. You are invisible because the architecture was never designed to see you.

That is a different problem, and it requires a different kind of access.

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References

Catalyst. (2026, January 29). Caregiving pressures top factor pushing women out of the workforce, Catalyst finds.

LHH. (2025). Views From the C-Suite: Executive burnout and leadership retention survey. Survey of 2,675 executives across 10 countries.

Miller, R. A., and Nguyen, A. (2024). Optimal long-term executive contracts. Tepper School of Business, Carnegie Mellon University. Analysis of SP1500 executive data, 1992–2022.

Gartner. (2025, February 5). Gartner HR survey reveals more than half of C-suite leaders are likely to leave over the next two years.