PsychFlo / Retention Intervention Lab
Find Out Whether a Retention Investment Deserves More Funding.
Explore how PsychFlo evaluates workforce interventions, examines outcome differences, and translates assumptions into financial decision scenarios.
Approximately 3 minutes · No registration · No uploads
This demonstration uses synthetic data and illustrative assumptions. Results do not represent actual customer outcomes.
Commercially validated · Company-reported
PsychFlo reports completed customer evaluations, documented purchasing commitments and payments. This company-reported status has not been independently verified.
See the workflow
From a retention question to a decision report.
Watch the working product compare outcomes, explore financial assumptions and export an evidence review.
Read the video transcript
- Commercially validated · Company-reported. This status has not been independently verified.
- Start with a defined retention decision and a fixed synthetic example.
- Inspect the intervention, comparison group and aligned observation period.
- Compare observed turnover rates and review uncertainty. Observed differences do not establish causation.
- Explore financial assumptions separately from measured outcomes.
- Generate and download a report containing the calculations, assumptions, limitations and next steps.
For a real evaluation, agree scope, approved data sources and success criteria with your organization.
Stage 1 of 5
Understand the decision
A synthetic company is considering whether to continue, modify or further evaluate an employee retention initiative. HR and Finance need to distinguish observed outcomes from assumptions before committing more funding.
- Workforce group
- Customer support; two independent synthetic cohorts of 120 people each.
- Intervention
- Manager coaching initially; choose another supported scenario label in stage 2.
- Observation period
- January–June 2026. The comparison of interest uses April–June 2026.
- Outcome metric
- Qualifying voluntary turnover divided by complete outcomes.
- Reference group
- A separate synthetic comparison cohort with equal follow-up.
- Starting financial assumption
- GBP 6,000 program cost and GBP 20,000 replacement cost per departure. Editable in stage 4; neither is a benchmark.
Dataset: four fixed aggregate employee-period rows. Repeated periods are not additional unique people. Nothing is uploaded or saved to organization storage.
Use “Start Interactive Demonstration” above to load the fixed example.
How These Results Are Calculated
Plain English: compare the two synthetic groups over the same quarter, explain uncertainty, then calculate a separate financial “what if.” A lower observed turnover rate does not establish that the intervention caused the difference.
Data and comparison
Four fixed aggregate rows, January–June 2026. The main comparison is April–June 2026: two independent cohorts, with voluntary departures and missing outcomes recorded separately. No random regeneration, employee identifiers or uploads are used.
Uncertainty
Conservative approximate 95% difference interval from Bonferroni-adjusted marginal 97.5% Wilson score limits. Independent groups, equal-duration windows and consistent definitions are assumed. Sparse departures, selection and unmeasured confounding limit interpretation. The chart shows the recorded interval, not an invented confidence measure.
Financial formulas
Expected avoided departures = 120 × assumed percentage-point reduction ÷ 100. Gross value = expected avoided departures × replacement cost. Net value = gross value − program cost − additional implementation cost. ROI = net value ÷ total intervention cost × 100, unavailable at zero cost.
Replacement-cost sensitivity at 50%, 100% and 150% is illustrative, not a confidence interval. Horizon changes do not extrapolate observed results. Avoid double-counting recruitment/training/vacancy costs already bundled in replacement cost.
Full methodology, safeguards and limitations →Want to Evaluate a Real Workforce Decision?
Discuss a scoped enterprise evaluation using appropriately governed workforce data, defined outcomes, and transparent assumptions.
Commercial scope and terms must be agreed. Do not submit employee-level or health information through the inquiry form. This synthetic example is not a customer result. Commercial outcomes require evidence from actual evaluations.
Explore the other modules
AI Workforce ROI Auditor separates cash savings, avoided spending, redeployed capacity and hypothetical productivity value.
Organizational Change Simulator uses explicit assumptions and seeded simulations, not individual termination recommendations.
Open the full Retention Intervention Lab →