Executive Failure Rates
Executive Failure Rates in Corporate Leadership
A synthesis of peer-reviewed research, advisory indices, and consulting studies
Reported "executive failure rates" vary widely because researchers and advisory firms measure different things under the same label. Across the most-cited empirical and industry sources, the underlying metrics cluster into four families, each with a different denominator and a different meaning:
- Managerial derailment and perceived leadership failure rates typically fall in a 30%–67% range (mean about 47%, median 50%) when "failure" is defined broadly as managerial ineffectiveness or eventual failure, and when estimates are aggregated across heterogeneous studies and samples. These figures are best interpreted as a coarse base-rate claim about leadership ineffectiveness, not a precise probability for any single role, firm type, or time horizon.
- Leadership transition failure or disappointment rates are commonly reported in the high double digits, but they are usually based on perception-based definitions such as "failure" or "disappointment" two years after a transition. A McKinsey & Company synthesis cites a range (27% to 46%) for executive transitions "regarded as failures or disappointments" after two years, explicitly attributing the endpoints to two different industry studies. Because denominators and rating criteria differ across these inputs, the range should be read as "what multiple surveys have reported," not as a single unified estimate.
- Forced CEO removal is materially lower than "transition failure" estimates, largely because it is a narrower outcome. In a peer-reviewed Strategic Management Journal article building a CEO departure and dismissal database for S&P 1500 firms (2000–2018), two dismissal codes account for 1,023 of 4,141 CEO departures. That is 24.7% of CEO departures classified as dismissals over the period (95% CI: 23.4%–26.0%). This is the share of recorded CEO departures that are dismissals in that dataset, not the annual probability that a sitting CEO is fired.
- Role-level turnover rates (CEO/CFO/CHRO/COO churn) are often the most comparable cross-function numbers because they use a clear denominator: the number of role-holders within an index universe. Russell Reynolds Associates reports 2024 global CFO turnover of 15.1% across 12 major indices (six-year average 14.8%) and notes a six-year-average CEO turnover rate of 11% in that index universe.
Why executives fail also depends on what counts as failure. In derailment research, relationship failures and inability to adapt repeatedly dominate. In CEO turnover and governance data, "failure" is more often tied to performance under scrutiny, activist pressure, ethical lapses, or a board's decision that the pace of transformation is insufficient.
Evidence about what reduces executive failure is uneven. The strongest support is for interventions that reduce misfit and accelerate alignment: structured succession planning, realistic role scoping and mandate clarity, transition/onboarding architecture, and assessment tools that identify derailment risks and readiness gaps.
The most important practical takeaway is to treat "failure rate" as a function of (1) failure definition, (2) time horizon, and (3) executive population. Mixing these generates misleading conclusions, especially when moving between "derailment" (broad competence and behavior), "transition disappointment" (perception-based), "turnover" (role churn), and "dismissal" (forced exit).
What Counts as "Executive" and "Failure"
This review uses "executive" as an umbrella term but preserves each source's own definition in the comparative tables. Across the literature, "executive" typically resolves into one of four operationalizations:
- Top-of-firm (CEO)
- Academic governance datasets often focus on CEOs of public firms because CEO identity and exit events are observable and systematically recorded.
- C-suite functional executives (CFO, CHRO, COO)
- Industry indices track these roles across public-company index universes and treat any departure/appointment as turnover (whether planned or forced).
- Middle-to-upper-level managers and executives
- Derailment research frequently samples managers and executives across levels rather than restricting to the CEO office; the unit of analysis is the individual leader's effectiveness or trajectory, often measured via interviews and multi-rater instruments.
- External hires and leaders in transition
- Transition research is often framed around leaders moving into new roles (promotion, lateral move, external hire) and evaluates success/failure based on perceived outcomes after a specified period (commonly 18–24 months).
"Failure" has even more variation. The most consequential definitional choices are the numerator (what events count) and the evaluation mechanism (objective vs. subjective). Common failure constructs include:
- Dismissal / forced exit
- In the S&P 1500 CEO dismissal database paper, "dismissal" is implemented via specific departure codes (codes 3 and 4), with code 3 explicitly defined as "dismissed for job performance" and the dismissal classification based on media coverage and filings around the departure.
- Derailment
- In classic derailment framing, derailed leaders are high-achievers whose progress becomes involuntarily stalled or reversed, often due to interpersonal and adaptation issues rather than technical deficits.
- Failure / disappointment of a transition
- In consulting syntheses of transition success, "failure" is often defined by stakeholder judgment that the transition outcome is a "failure" or "disappointment" after a set time (for example, two years), rather than by termination alone.
- Turnover as a proxy
- Many indices treat turnover as the observable outcome, sometimes distinguished by reason (retirement, board move, external opportunity) and sometimes not.
A practical way to keep these constructs separate is to treat them as different endpoints on a severity ladder:
This ladder is conceptually useful but should not be mistaken for a validated progression, because many individuals exit voluntarily while struggling, and many who are "disappointments" remain in role.
The Research Landscape and Methodological Issues
The evidence base splits into two partially overlapping knowledge streams: (1) peer-reviewed research on CEO dismissal/turnover and managerial derailment, and (2) consulting and advisory research on leadership transitions, succession, and role turnover across C-suite functions.
Peer-reviewed CEO dismissal and turnover research
The S&P 1500 CEO turnover/dismissal database project was motivated by a replicability problem: CEO dismissal is hard to observe, datasets rely on author judgment, and different coding schemes often disagree. In the paper's comparison of three published datasets, correlations across dismissal measures range roughly 0.43 to 0.62, and the authors report disagreement on dismissal coding between 10% and 25% of the time. This implies that small definitional shifts can move reported failure rates meaningfully, especially when dismissal is rare relative to all CEO-year observations.
Peer-reviewed derailment and "bad manager" base rates
A chapter on management derailment aggregates "estimated base rates for management failure" from multiple sources, producing a range 30%–67% with mean 47% and median 50%. These estimates pool heterogeneous constructs (e.g., willingness to work for a boss again; consultant estimates; organizational studies), so statistical confidence intervals are generally not meaningful, and population comparability is limited. The chapter's value is in documenting that multiple independent sources have historically produced high base-rate estimates, not in providing a single precise percentage for a specific executive role.
Consulting / industry transition studies
Consulting research often answers a different question: "How often do leadership transitions yield disappointing outcomes?" and "What practices increase success?" These studies tend to be practical and high-level, but they frequently omit sampling frames, operational definitions, and detailed methodology needed to compute uncertainty intervals. When specific sample sizes and denominators are presented (as in several role turnover indices), turnover rates can be quantified more cleanly.
Key methodological limitations
Quantitative Failure Rates and Time-to-Failure
This section synthesizes quantitative rates by metric family, provides confidence intervals where the source supplies enough information, and summarizes what is known about time-to-failure.
Quantitative synthesis and comparability warnings
Large-scale hiring failure research provides an additional reference point for interpreting executive failure statistics. Leadership IQ's "Why New Hires Fail" study tracked more than 20,000 employees and found that 46% failed within 18 months. This figure aligns closely with managerial derailment base-rate estimates reported in the literature (30–67%, mean approximately 47%).
The Leadership IQ study also reinforces a key theme in executive derailment research: most failures stem from behavioral and interpersonal issues rather than technical capability. In the Leadership IQ dataset, 89% of hiring failures were attributable to attitudinal factors such as coachability, emotional intelligence, motivation, and temperament.
The table below lists high-quality peer-reviewed papers, original consulting/advisory reports, and widely referenced research documents that provide either (a) an explicit failure/derailment/turnover percentage, or (b) enough counts to compute one. If a detail is not available in the source, it is marked "unspecified."
Because these metrics are not directly comparable, pooled estimates must be grouped by measurement family rather than averaged into one "executive failure rate." The most defensible pooled summaries are:
Share of CEO departures that are dismissals in a large public-company dataset
Using the S&P 1500 CEO departure database counts (codes 3 and 4 as dismissals), dismissals represent 1,023 of 4,141 CEO departures (24.7%).
Approximate 95% confidence interval (Wilson) for this proportion: 23.4%–26.0% (computed from the published counts).
Interpretation: among recorded CEO departures in large United States public firms over 2000–2018, about one quarter are classified as dismissals in this coding scheme. This is a "composition of departures" statistic, not a CEO-year firing probability.
Annual CFO turnover rate in a defined global index universe
RRA reports 2024 global CFO turnover of 15.1% across 12 major indices with 275 new CFO appointments, and states the denominator universe is N=1,822 companies/roles in its methodology.
If one treats 275 appointments as turnover events out of 1,822 role slots (a reasonable reading of the report's turnover construction, given 275/1,822 ≈ 15.1%), an approximate 95% CI for the turnover proportion is 13.5%–16.8% (computed).
Interpretation: CFO seats in large public-company indices turn over at a mid-teens annual rate; this includes retirement and upward moves and is not synonymous with failure.
Base-rate estimates for management failure/ineffectiveness
The management derailment chapter's table reports 12 base-rate estimates ranging 30%–67% with mean 47% and median 50%.
No meaningful confidence interval can be computed because the table aggregates heterogeneous sources without consistent denominators and because the estimates are not drawn from one sampling distribution.
Interpretation: a substantial portion of "managers" are rated as ineffective in various studies, but translating this to a "C-suite failure rate" requires assumptions that the underlying sources do not justify.
Visual summary chart of rate families
The chart below deliberately separates the four "rate families" to reduce category error. Values are ranges or point estimates as reported in the cited sources.
Source anchors: managerial base-rate table; transition failure range; CEO dismissal-share counts; CFO turnover and denominator.
Time-to-failure and "when" executives fail
Evidence about tenure-to-failure is strongest for CEOs and for the early transition window.
Early transition window as an observed "risk period"
Multiple practitioner and consulting sources focus on the first 18–24 months as a high-risk window, using constructs like "fail within 18 months" or "disappointment after two years." While these statements are widely cited, they are not consistently tied to a shared dataset or definition, and they frequently conflate "exit" with "underperformance."
The more defensible claim is that early tenure compresses the time available to establish mandate clarity, stakeholder support, and team alignment, making early missteps more predictive of later adverse outcomes. That aligns with both transition-focused guidance and derailment mechanisms emphasizing relationship and adaptation failures under stress.
"Boards are making the call earlier" (CEO-specific)
RRA's 2025 CEO report notes an increase in short-term CEO appointments, reporting that the proportion of CEOs departing within a 30–36 month window increased 79% year-over-year and explicitly framing this as boards making earlier judgments in the CEO lifecycle. This is consistent with a governance environment in which CEO mandates are increasingly transformation-linked and time-bound, and with heightened activism-related scrutiny.
Longer-horizon failure / exit
Role turnover indices provide average tenures: for example, RRA reports average outgoing CEO tenure of 7.1 years (2025) and CFO tenure of 5.8 years (2024), indicating substantial churn over a medium horizon even when "failure" is not the driver.
In private equity contexts, succession dynamics are more aggressive. A Heidrick & Struggles report targeted at private equity suggests that over 70% of CEOs at PE-backed companies are replaced over an average hold of roughly 5.5–6 years. This is better interpreted as a feature of the PE governance model (active ownership and performance thresholds) than as a pure "CEO incompetence" rate.
Why Executives Fail: Drivers and Mechanisms
Across derailment research, turnover indices, and transition guidance, failure drivers recur in four interacting buckets: behavioral, strategic, organizational, and contextual. The most evidence-supported view is that "failure" is usually an interaction effect: a leader's behavioral tendencies under stress + an ill-defined mandate + misaligned stakeholders + a context that punishes early errors.
Behavioral and interpersonal drivers
Derailment research repeatedly highlights relationship breakdowns as the most frequent proximate cause. In a summary of CCL's early derailment work, derailed executives are described as high achievers whose progression halts non-voluntarily, with the "most frequent cause for derailment" identified as insensitivity to others, which under stress manifests as abrasiveness and intimidation.
In the cross-regional CCL study, themes that differentiate derailed from successful executives include inability to build and lead a team, problems with interpersonal relationships, and difficulty adapting to change.
The management derailment chapter's base-rate table is accompanied by a mechanism narrative emphasizing "the dark side" of personality, where dysfunctional dispositions show up under pressure as bullying, intimidation, arrogance, and excessive deference, degrading trust and performance.
Transition research converges on similar behavioral bottlenecks but often labels them pragmatically: failure to align with expectations, failure to build effective teams and networks, and low self-awareness during early months.
Strategic and execution drivers
CEO and CFO turnover research often locates failure in perceived inability to deliver results fast enough or to execute a transformation agenda under scrutiny.
RRA's CEO turnover report explicitly frames elevated CEO churn as an outcome of relentless disruption and boards becoming more explicit about what results must be delivered and when. The report highlights the narrowing "margin for error" as activist pressure rises and boards become more responsive to that pressure.
For CFOs, the 2024 turnover report describes the CFO role as increasingly operational and strategic, highlighting demands spanning strategy, capital allocation, investor relations, regulatory complexity, and activist pressure, and links these pressures to higher turnover and shorter tenure.
Organizational drivers
A large fraction of "executive failures" can be reframed as organizational design failures: unclear decision rights, misaligned incentives, poor team composition, or lack of transition support.
The CHRO index explicitly recommends structured transition support to "de-risk first-time CHROs," embedding transition planning as part of the appointment decision, and it links the CHRO role's stability to CEO turnover given the CHRO's relationship to the CEO.
The CFO turnover report similarly emphasizes the need for robust CFO succession plans and notes that a new CEO often wants to choose their own executive team members when strategies and horizons misalign.
McKinsey's transition synthesis also emphasizes that leaders need more than a standard "first 100 days" plan, explicitly challenging the "100-day myth" and presenting a broader set of actions (including stakeholder engagement and operating rhythm) to stabilize the transition.
Contextual and governance drivers
Executive performance is judged relative to context, and governance conditions shape the tolerance for errors.
In CEO governance environments, investor activism can accelerate exits. RRA cites external market data indicating that activist campaigns are associated with CEOs resigning within a year of campaigns and that activism is heavily concentrated in large-cap universes, reinforcing that CEO exits are not solely a consequence of internal performance metrics.
In cross-market geography, RRA notes structural differences that shape tenure, including differences in governance norms and ownership structures across markets (for example, fixed-term appointments in parts of continental Europe vs. more flexible notice norms elsewhere).
Typical Executive Failure Paths
The flowchart below synthesizes the most consistent causal pathways described across derailment research, transition studies, and governance turnover analyses. It is a conceptual model (not a validated causal DAG), designed to make explicit where interventions typically act.
Under high scrutiny (activism, crisis, new CEO), the pathway compresses toward forced exit or resignation under pressure. Under lower scrutiny or supportive ownership, there is more room for coaching, role redesign, or quiet underperformance. Interventions at the early stages — selection, mandate clarity, transition architecture — have the highest leverage because they reduce the probability of entering a negative spiral.
Segment Differences Across Level, Function, Industry, Firm Type, and Geography
This section summarizes what the cited sources can and cannot support about differences in failure risk.
Level differences: C-suite vs. VP vs. "manager"
The derailment and "bad manager" base-rate estimates are mostly not stratified cleanly by level. The management derailment chapter aggregates sources that include managers broadly; it does not publish a level-specific base rate for C-suite leaders.
CCL's derailment comparison study covers "executives" and "middle-to-upper-level managers," but it uses a case–control design (comparing derailed vs. successful leaders) rather than estimating prevalence by level. It is therefore informative about differentiators but not about "what percent of VPs fail."
Transition "failure" ranges (27%–46% two-year disappointment) are similarly broad and not level-stratified in the McKinsey synthesis, because they are compiled across multiple studies.
Evidence gap conclusion: high-quality, level-stratified failure rates (VP vs SVP vs C-suite) are rarely published in open sources, likely because many datasets are proprietary and because internal performance "failure" is not externally observable.
High-quality, level-stratified failure rates (VP vs SVP vs C-suite) are rarely published in open sources, likely because many datasets are proprietary and because internal performance "failure" is not externally observable.
Functional differences: CEO vs CFO vs CHRO
The cleanest cross-function comparison comes from turnover indices in comparable index universes:
CFO vs CEO turnover. In RRA's CFO annual report, 2024 global CFO turnover is 15.1% and the six-year average CFO turnover is 14.8%, compared with a six-year average CEO turnover rate of 11% in the same index universe. This indicates CFO seats churn more frequently than CEO seats, even though CEO changes are more salient.
CHRO tenure and first-time prevalence. The CHRO index reports an average tenure of 4.2 years and that first-time CHROs comprise 53% of new CHRO appointments in 2024, suggesting a relatively rapid churn and a large first-timer cohort, which is a known risk factor for transition misfires absent structured support.
CEO dismissal specificity. CEO dismissal datasets are more mature than CFO/CHRO dismissal datasets because CEO departures are more observable and widely covered. The S&P 1500 CEO dismissal database documents both performance-related and other dismissals, enabling more nuanced analysis of "failure" drivers.
Industry differences
Industry differences are most consistently documented for CEOs and CFOs in the cited sources.
CEO technology sector. RRA reports that technology CEO turnover dynamics differed sharply from broader global trends, with 40 technology CEO departures in 2024 and 20 in 2025, and interprets this as boards being reluctant to run CEO succession amid intense strategic demands.
CFO industrial sector hiring patterns. RRA reports that experienced CFO hires (previous public-company CFO experience) rose to 40% globally in 2024 and that industrial firms were most likely to hire an experienced CFO (46% of industrial CFO hires), implying either higher perceived risk or greater demand for "ready-now" capability in that sector.
Healthcare CFO exits. The CFO report notes retirement/board moves in healthcare CFO departures at 60% in 2024 (above the 54% global average), while also suggesting possible links between sector valuations/performance and turnover pressure.
Company size and public vs. private
Public-company evidence dominates. The most rigorous dismissal datasets in this review focus on large publicly traded firms, such as S&P 1500 companies.
Private equity (PE) environments show substantially higher CEO replacement prevalence, but these are typically described as governance model outcomes rather than "failures" in a psychological derailment sense. In Heidrick & Struggles' PE succession report, "over 70%" CEO replacement prevalence is tied to the average hold period of five and a half to six years, and the report positions robust succession planning as necessary to manage repeated leadership change.
Implication: "CEO replacement probability over the hold period" can be dramatically higher in PE than "annual CEO turnover percentage" in public indices, but these measures differ and are driven by different selection and governance mechanisms.
Geography differences
Geographic differences are better documented for turnover and tenure than for derailment prevalence.
Public markets and governance structure. RRA explicitly discusses how CEO tenure differs across markets and connects divergence to governance structures such as fixed-term systems and ownership concentration.
Country-specific activism and market pressure. RRA's 2025 CEO report highlights activism dynamics and includes commentary on activism contributing to CEO turnover in Japan, alongside market and regulatory pressures.
Derailment research cross-national generalization. The management derailment chapter summarizes cross-cultural derailment research as generalizing across time and national cultures, citing samples spanning multiple European countries and the United States. This is suggestive but not an estimate of differential failure rates by geography.
What Reduces Failure Rates: Succession, Onboarding, Assessment, and Development
High-quality evidence about interventions that reduce executive failure is distributed unevenly: there is more support for selection and succession processes (reducing mismatch) and for structured transition support (reducing early friction) than for any single "silver bullet" program.
Succession planning and internal pipelines
Multiple sources converge on the idea that proactive succession planning reduces destabilizing turnover and de-risks first-time appointments, even when they do not quantify a precise reduction in failure rate.
The CFO turnover report explicitly argues for "robust CFO succession plans" and frames succession readiness as a multi-year process, driven by CEOs, boards, and CFOs themselves. The CHRO turnover index similarly advises starting early, building bench strength, and de-risking first-time CHROs with structured transition support.
In CEO succession, RRA frames elevated turnover and shorter runways as increasing the importance of "getting CEO succession right," and it notes that boards overwhelmingly appoint first-time CEOs, raising the stakes for pipeline quality and transition support.
A recurrent empirical challenge is that "succession planning quality" is hard to measure and is often endogenous to firm quality. Even when studies observe that better-prepared boards have fewer disruptive transitions, the causal pathway is difficult to prove without quasi-experimental variation.
Onboarding and transition architecture
McKinsey's transition synthesis frames transition failure/disappointment as common and argues that leaders need to manage a multidimensional transition process beyond a static 100-day plan. While the McKinsey piece is not a controlled study, it is valuable as a structured articulation of the "mechanisms of transition failure" that align with derailment research: stakeholder engagement, team building, and creating an operating rhythm.
RRA's CHRO index makes the transition support recommendation explicit and positions it as a way to de-risk first-time CHRO appointments. The CFO report similarly notes that success for first-time CFOs is linked to how well the organization sets up the mandate and supports transition.
Evidence of effectiveness is most credible when intervention outcomes are measured against well-defined endpoints (e.g., "left role within 18 months") and when selection biases are discussed.
Assessment tools and readiness screening
The most explicit numeric "intervention effect" in the accessible sources comes from Korn Ferry Institute outcomes research.
The Korn Ferry proofpoint report cites an "average CEO failure rate" of 40% within the first 18 months (attributed to a practitioner article) and reports that among CEOs who scored highest on Korn Ferry's CEO Readiness Assessment, fewer than 2% left within 18 months; among low scorers, 9% left within 18 months. It also reports that the tracked study followed 162 executives who completed the assessment and later became CEOs.
This evidence is practically important but methodologically constrained: the "40% average" is not measured within the 162-person cohort (it is a cited external benchmark), the cohort is pre-selected (people assessed by Korn Ferry and later appointed CEO), and the report does not provide the number of high scorers vs low scorers, preventing precise confidence intervals for the <2% and 9% figures.
Still, it provides directional evidence consistent with industrial-organizational psychology: structured assessments that measure competencies and behavior under simulated stress may identify risk earlier than unstructured interviews alone, and they can be paired with coaching to remediate gaps.
CCL's Benchmarks suite is cited in derailment literature as a multi-rater assessment framework that measures derailment factors and leadership capabilities, supporting the broader claim that feedback and self-awareness interventions can target known derailment risks.
Coaching, development, and "rescue" interventions
Direct evidence that coaching reduces executive failure rates (as opposed to improving proximal competencies) is limited in the sources reviewed here. The Korn Ferry proofpoint suggests that even low scorers had lower failure rates than the stated average, and it interprets this as the potential value of intense feedback and coaching for CEO candidates.
Derailment research suggests that failure mechanisms often involve low self-awareness and relational damage under stress, which are plausible coaching targets, but translating this to a quantified reduction in dismissal probability requires data that most studies do not publish openly.
A more realistic evidence-based claim is that the highest-leverage interventions happen upstream: selection, mandate clarity, and early alignment reduce the probability of entering a negative spiral where coaching becomes "too late."
Additional Evidence: Leadership IQ "Why New Hires Fail" Study
Leadership IQ studied more than 20,000 new hires and 1,463 HR executives to understand why employees fail in new roles. The study discovered that 46% of newly hired employees fail within 18 months while only 19% achieve unequivocal success. Attitudes drive 89% of hiring failures while technical skills account for only 11%.
Top reasons for failure
The research also found that 82% of hiring managers reported seeing warning signs during the interview process that suggested the employee might fail.
Comparative chart of leadership failure metrics
The following chart compares several commonly cited leadership failure metrics discussed in this report. These figures measure different phenomena and therefore should not be interpreted as directly comparable. However, placing them side-by-side highlights how the Leadership IQ dataset aligns with long-standing estimates of managerial derailment and executive transition difficulty.
The chart helps illustrate that the Leadership IQ research falls very close to the historical base-rate estimates of managerial derailment. This alignment suggests that behavioral factors driving early hiring failure may represent the early manifestation of the same dynamics that later produce executive derailment.
Additional large-scale evidence on leadership failure comes from Leadership IQ's "Why New Hires Fail" study, which tracked more than 20,000 employees across 312 organizations. The research found that 46% of newly hired employees failed within 18 months, while only 19% achieved unequivocal success. Importantly, 89% of failures were attributed to attitudinal factors such as coachability, emotional intelligence, motivation, and temperament rather than technical skill deficiencies. These findings align closely with the managerial derailment literature (30–67% estimated failure rates) and suggest that many behavioral patterns associated with executive derailment are visible much earlier in organizational careers.
Evidence Gaps and Research Recommendations
Even with substantial citation volume, the evidence base has clear missing pieces. These gaps explain why popular "failure rates" are often overstated, why they wander between 30% and 70%, and why moving from CEOs to "executives broadly" is difficult.
Key gaps
Research recommendations
Publish consistent denominators and uncertainty intervals. Advisory reports often provide compelling percentages without enough detail to compute confidence intervals. Where denominators exist, publishing N by year would enable more rigorous inference.
Unify transition outcomes with turnover classification. Future research could link "disappointment" measures to concrete outcomes such as early exit, team turnover, or financial restatements, bridging transition research and governance datasets.
Develop open dismissal datasets for CFO/CHRO/COO. CEO datasets have advanced via open-source efforts; similar projects for other executives would materially improve the evidence base, especially around function-specific drivers (e.g., CFO exits after financial reporting crises vs CHRO exits after cultural incidents).
Exploit quasi-experimental variation in onboarding investments. Natural experiments (policy changes in onboarding, sudden governance reforms, exogenous shocks affecting transition support) could provide causal evidence on whether structured onboarding reduces early executive failure/disappointment.
Primary Sources
- Gentry et al. — Database of CEO Turnover (S&P 1500, 2000–2018)
- Russell Reynolds Associates — Global CEO Turnover Index Report 2025
- Russell Reynolds Associates — Global CFO Turnover Index 2024
- Russell Reynolds Associates — Global CHRO Turnover Index
- McKinsey & Company — Successfully Transitioning to New Leadership Roles
- Korn Ferry Institute — ProofPoint: CEO Outcomes
- Center for Creative Leadership — A Look at Derailment Today
- PwC — CEO Turnover at Record High (2019)
- Heidrick & Struggles — Private Equity: CEO Succession Planning in a New Normal
