Example Organization — All Employees
Calculated using the Scenario model and the current intervention portfolio.
Priority belonging dimensions
Results Dashboard
Review key outcomes, scenario ranges, segment risks, and multi-year projections.
Scenario comparison
| Scenario | Turnover reduction | Projected turnover | Employees retained | Avoided cost | Net benefit | ROI |
|---|---|---|---|---|---|---|
| Conservative | 1.00% points | 15.49% | 4.85 | $230,573.12 | $184,573.12 | 401.25% |
| Expected | 1.53% points | 14.96% | 7.43 | $353,358.91 | $307,358.91 | 668.17% |
| Optimistic | 6.50% points | 9.99% | 31.53 | $1,498,725.30 | $1,452,725.30 | 3,158.10% |
Formula Used and Methodology
Understand each calculation before using the results for workforce or investment decisions.
Retention Rate
The retention rate focuses on employees who were present at the beginning. New hires are removed from the ending headcount before the rate is calculated.
Turnover Rate
The turnover rate divides total departures by the average workforce. The average workforce is the mean of beginning and ending headcount.
Belonging Index
Each survey dimension is converted to a common zero-to-one-hundred scale. The calculator then applies the chosen weights.
Estimated Retained Employees
The expected turnover reduction is applied to the average workforce. The result is capped by the configured at-risk population.
Replacement Cost
Replacement cost combines recruiting, onboarding, training, vacancy, ramp-up, coverage, knowledge loss, manager time, and separation administration.
Avoided Cost, ROI, and Payback
Avoided cost multiplies retained employees by replacement cost. ROI compares net benefit with program cost. Payback estimates the months required for savings to recover investment.
How to Use This Calculator
Step 1: Define the population
Choose a clear workforce population and time period. Avoid mixing unrelated business units unless their workforce practices and survey instruments are comparable.
Step 2: Enter auditable workforce data
Use beginning headcount, ending headcount, new hires, and departures from a consistent source. Reconcile internal transfers and reclassifications before relying on the rate.
Step 3: Score belonging consistently
Use the same survey scale across dimensions. Exclude dimensions that were not measured. Keep custom weights visible and explain why those weights were selected.
Step 4: Select a defensible impact model
Use the scenario model when internal evidence is limited. Use correlation or historical models only when data quality, sample size, and analytical methods are adequate.
Step 5: Build the replacement-cost estimate
Include costs that genuinely change when an employee leaves. Avoid counting the same cost twice. Use role multipliers when replacement difficulty differs materially.
Step 6: Configure interventions
Select only planned initiatives. Estimate adoption, effectiveness, coverage, duration, initial investment, and recurring cost. Use conservative assumptions during approval reviews.
Step 7: Review scenarios and segments
Compare conservative, expected, and optimistic outcomes. Investigate aggregate groups with low belonging and high turnover, but protect small groups through suppression.
Step 8: Document limitations
Belonging and retention can move together without a simple causal relationship. Labor markets, leadership changes, compensation, workload, career paths, and business conditions also matter.
Interpretation Guidance
A high belonging score does not guarantee low turnover. Some employees leave for reasons unrelated to work experience. A low score indicates a need for deeper investigation, not a diagnosis.
Financial estimates should be treated as ranges. The conservative case helps test downside protection. The expected case supports planning. The optimistic case illustrates potential upside.
Segment analysis is most useful when groups have enough respondents and comparable survey conditions. Very small groups can expose identities or produce unstable percentages.
Recommended Governance
Assign an accountable owner for data quality, methodology, interpretation, privacy, and action planning. Keep an audit trail of assumptions and changes between reporting cycles.
Review the model with human resources, finance, legal, privacy, employee relations, and business leaders. Do not use aggregate estimates as the sole basis for employment decisions.
Track actual intervention adoption, belonging movement, turnover, and cost outcomes. Compare forecasts with realized results, then recalibrate assumptions transparently.