How exit interviews hide the truth about December resignations
Key Takeaways
Exit interviews capture late-stage stories and are prone to social desirability bias; treat them as directional, not diagnostic.
Add earlier, lower friction inputs such as brief anonymized pulses or self-administered check-ins to surface issues that people will not say face to face.
Run targeted stay interviews in November using simple risk signals such as stalled mobility, a recent manager change, and peer pay gaps, and log the specific “save” actions taken.
In January, show leaders exit themes alongside pre-exit signals to focus fixes on mobility, manager coaching, and compression.
Exit interviews are helpful, but if you treat them as “the truth,” you’ll fix the wrong problems. December departures are often months in the making. By the time someone sits down for an exit interview, memory has blurred, bridges need preserving, and the story is simplified to something polite and externally focused (“a better offer,” “relocation”). That’s not dishonesty, it’s human nature. Recall bias and social desirability (answering in ways that look good) both pull exit narratives away from root causes.
Harvard Business Review has cataloged how to make exit interviews more useful—structure them, combine standardized prompts with open questions, and avoid putting immediate managers in the interviewer seat. That makes the process better, but it can’t fix what exit data can never do: capture the multi-month path that led to the decision or reliably diagnose the fixable upstream issues on a specific team. Use exit interviews to spot themes, not to diagnose December spikes.
The December distortion
Year-end timing adds three distortions:
Calendar artifacts (bonuses, performance ratings, Q1 budgets) make “pay” or “opportunity” the easy narrative, even when the precipitating factors were internal.
Relationship preservation: people keep references and friendships intact; they won’t torch bridges in an exit form.
Speed: people are trying to wrap projects and get to holidays; interviews are shorter and more superficial.
The result: you over-index on “better pay elsewhere” and under-weight signals that were visible months ago.
A better conversation with people who plan to stay
Instead of waiting for “reasons for leaving,” run data-informed stay interviews with your at-risk population in November. Example: “It’s been 20 months since your last move; your pay is 12% below internal peers after merit; and your team changed managers last month. What would make next year a career step forward here?” That’s a practical way to operationalize the “career and manager” levers research keeps pointing to.
Reframe your January readout:
Left column: Top five exit interview themes (e.g., “compensation,” “career opportunity”).
Right column: Top five pre-exit signals (e.g., “no internal move in 18 months,” “manager change,” “compression >10%”).
Narrative: “While 55% cited pay, 74% had no internal moves for 18+ months and 61% experienced manager changes in Q4. Our plan: unblock mobility, equip managers, and address targeted compression.”
This side-by-side is honest about what exits say and what the data shows, which boosts leadership trust.
You don’t need a full data team. Start with the three signals you can compute every month from basic HRIS/ATS fields: time since last move, recent manager change, peer pay comparison. Publish a simple exception list for managers and a one-page exec summary. Iterate from there.
Where PeopleInsight Essentials fits
PeopleInsight Essentials helps teams move from post-mortems to early warnings. It consolidates your scattered data and ships executive-ready monthly pages with AI-assisted callouts that surface root causes—so you can act early, rather than explaining when it’s too late. That’s visibility and credibility – fast.
Exit interviews are a mirror, not an x-ray. Use them—but build your diagnosis from signals that show up before the resignation email.
See how PeopleInsight Essentials surfaces root causes (not just exit anecdotes) in monthly executive reports. Reach out here and get a live look at AI-generated trend callouts, manager/risk signals, and a sample save-plan pack.