Employee attrition analysis: how to predict and prevent turnover

Employee attrition analysis is the process of using workforce data to work out why people leave and who is likely to leave next. Calculate your attrition rate (departures divided by average headcount, multiplied by 100), segment it by department, tenure, performance and engagement, then trace the patterns back to causes you can act on.

Last reviewed July 2026.

Step 1: calculate the rate, then split it

The base formula is simple:

Attrition rate = (departures in the period ÷ average headcount in the period) × 100

A single company-wide number hides more than it reveals, so split it straight away:

• Voluntary vs involuntary: resignations tell a different story from role eliminations.
• Functional vs dysfunctional: low performers leaving is functional attrition and can be healthy. Your high-potential stars moving to competitors is dysfunctional attrition, and it is the number that matters most.
• Regrettable loss rate: the share of departures you genuinely did not want to lose. Track it separately from headline turnover.

Review these quarterly rather than annually. A quarterly cycle catches seasonal trends and department-level shifts before they spread.

Step 2: segment the data

Meaningful attrition analysis needs more than a headcount. Pull data from the whole employee lifecycle: entry and exit interviews, performance review scores, engagement surveys and departure dates. Then cut it four ways.

• By department and manager: a spike inside one team usually points to a localised leadership or workload issue, not a systemic one.
• By tenure: find your tenure cliff, the point in the employee journey where people are most likely to leave. A cliff at six months implicates onboarding and hiring fit; a cliff at three years usually means people hit a career ceiling.
• By performance: if your top quartile leaves faster than everyone else, you have a dysfunctional attrition problem regardless of how healthy the headline rate looks.
• By engagement score: layering survey results over departure data shows you where disengagement is converting into resignations, and where it soon will.

Context matters too. Check the external market: competitors offering more flexibility, or a skill set in your team suddenly in high demand elsewhere, will show up in your data as an unexplained cluster of exits.

Step 3: identify the drivers

Every resignation has a story, but in aggregate the themes repeat. The common drivers are a lack of career progression, poor management behaviour, burnout, and a mismatch between someone's work personality and their daily tasks. If the Doers in your operations team are leaving faster than anyone else, their roles may have become too ambiguous for people who thrive on structure. That is a design problem you can fix, not a hiring problem.

This is where qualitative data earns its keep. Real-time sentiment from Compono Engage explains the quantitative trends in your turnover reports, so you can tell whether the issue is systemic (career development, pay, flexibility, workload) or local (one team, one leader, one badly designed role).

Step 4: predict flight risk and intervene early

The goal is to move from hindsight to foresight. The reliable early flight-risk indicators are a sudden drop in engagement survey participation and an increase in unplanned leave, along with a performance plateau from someone who was previously climbing. Any two together deserve a conversation.

That conversation is a stay interview: an honest discussion about what would keep the person engaged and supported, held while they are still deciding rather than after they have signed elsewhere. Managers who run stay interviews consistently convert flight risks back into committed employees, because the biggest driver of regrettable loss is people concluding nobody noticed they were unhappy.

For a deeper look at spotting risk signals early, see our guide to attrition risk and how to spot it.

Step 5: turn the analysis into action

Data without action is just a spreadsheet. Match the intervention to the driver the analysis surfaced:

• People leave for growth: build internal mobility and development paths, and make them visible.
• People leave one manager: coach or restructure. Do not run another survey to confirm what the data already shows.
• People leave early in tenure: fix hiring fit. Assessing candidates for organisation fit before they join, with a tool like Compono Hire, cuts early-stage attrition at the source.
• People leave from burnout: rebalance workload and check whether your team's personality mix matches the work you are asking of it.

Then keep the cycle running. Attrition analysis is not a one-off project; it is a quarterly rhythm of analysis and improvement. Teams that understand their collective work personality profiles handle stress and conflict better, and people who feel understood stay longer. That is the compounding return on doing this properly.

Frequently asked questions

What is the formula for employee attrition rate?

Attrition rate equals departures in the period divided by average headcount for the period, multiplied by 100. Calculate it separately for voluntary and involuntary departures, and track regrettable loss (high performers you did not want to lose) as its own metric.

What is the difference between attrition and turnover?

Turnover usually refers to the total number of people leaving and being replaced within a set period. Attrition is broader, covering resignations and retirements as well as role eliminations, without necessarily an immediate replacement. Analysing both matters for workforce planning.

How often should we run an employee attrition analysis?

Quarterly. Annual reviews arrive too late to act on. A quarterly cycle lets you spot seasonal trends and react to cultural shifts inside specific departments before they become widespread.

What are the early warning signs an employee might leave?

The most reliable indicators are a sudden drop in engagement survey participation and an increase in unplanned leave, along with a plateau in performance. When these appear, a stay interview focused on what would keep the person engaged is the most effective intervention.