Tools · Management & HR
Turnover Cost
Enter a role and a few numbers — get a fully-loaded, cited cost of turnover and the retention business case.
How it works
The number is code's, the defense is the corpus's: a deterministic layer computes the fully-loaded cost per separation (recruiting + onboarding + ramp-productivity + vacancy coverage + knowledge loss) with canon-typical, overridable default rates, annualizes it over the segment, and adds recurring absenteeism — then the model justifies each default against the people-analytics corpus, flags the highest-leverage assumptions, and frames the retention-investment business case. Distinct from talent-value (what an employee is WORTH) — this is what losing one COSTS; it consumes comp/headcount inputs, never duplicates them. Missing inputs are reported, never invented.
You bring
{ segment, annualSalary?, headcount?, annualSeparations?|turnoverRatePct?, recruitingPctOfSalary?, onboardingPctOfSalary?, rampMonths?, rampProductivityLossPct?, vacancyDays?, knowledgeLossPctOfSalary?, absenceDaysPerYear? }
You get
{ segment_summary, components[] (formula · assumption · per_separation), per_separation_total, separations, segment_annual_total, absenteeism_annual, grand_total, sensitivity_drivers[], interpretations[], business_case, grounded_in, provenance }
Use it for
- →Build the retention business case: enter a role + turnover rate → a board-ready dollar total broken out by driver, each cited
- →Stress-test the number: override the recruiting/ramp/vacancy assumptions → see the sensitivity on the grand total
- →Reframe 'people are leaving' as a P&L line for the segment, annualized over its separations + absenteeism
Run it on your data
Call it on your own inputs — over the API, or hand it to your AI agent via MCP. Discovery is open; running it is metered.