People, retention & knowledge
Attrition, onboarding, contribution and knowledge concentration, with cohort privacy built in.
23 of 388 tools.
Analyze info gap robust satisficing
Select a robust-satisficing action under severe uncertainty with Info-Gap Decision Theory: evaluate worst and best payoff across a governed nested uncertainty envelope, maximize the radius before a critical requirement fails, report windfall opportuneness, and use no scenario probabilities.
Audit attention fragmentation evidence integrity
Audit consented point-in-time contributor identity, availability, privacy-safe calendar metadata and work-session lineage before reporting aggregate meeting load, protected focus blocks or cross-project switching.
Audit attrition risk prediction integrity
Audit an attrition model's complete eligible cohort, point-in-time features, supportive-use governance, intervention-contaminated labels, competing outcomes, calibration, false positives and authorized subgroup error before any person-level use.
Audit code knowledge concentration integrity
Audit file, module, service, or repository knowledge concentration from point-in-time substantive changes, reviews, incident response and documentation using identity-confidence filtering, recency decay, Bayesian ownership uncertainty, entropy-effective owners, HHI and leave-top-owner-out resilience—without turning contribution evidence into a person-performance score.
Audit onboarding mentorship evidence integrity
Audit point-in-time onboarding cohorts, ordered autonomy milestones, source completeness and corroborated mentorship windows before publishing privacy-safe ramp evidence.
Audit org health score integrity
Reconstruct the organization-health composite from frozen component evidence and block publication when source completeness, consent, versioning, construct balance, cross-group measurement invariance, redundancy, privacy or leave-one-component stability fails.
Audit probability policy subgroup equity
Audit an aggregate probability-driven policy across governed groups using weighted selection, error-rate, predictive-value, Brier, and calibration disparities; within-group bootstrap uncertainty; practical tolerances; privacy/support abstention; and Benjamini-Hochberg false-discovery control.
Estimate role adjusted contribution
Estimate role-relative outcome contributions with empirical-Bayes shrinkage, uncertainty, provenance, and cohort privacy.
Explain metric shift shapley
Fit a cross-validated second-order ridge response surface and decompose its reference-to-current aggregate metric shift with an efficiency-preserving Shapley allocation, bootstrap uncertainty, and an explicit unexplained residual.
Forecast aggregate workforce capacity risk
Forecast aggregate role-capacity shortfall with a partially pooled discrete-time competing-risk model that learns cause-specific hazards from right-censored employment spells, simulates the active role portfolio, exposes unseen-role and unsupported-period extrapolation, and never produces named-person attrition scores.
Forecast focus fragmentation delivery economics
Forecast current-task completion and delay-cost tails with a company-local ridge log-normal accelerated-failure-time model that uses attention covariates only after beating a global model on the latest whole period.
Forecast governed attrition competing risks
Forecast voluntary departure, internal transfer and involuntary exit as calibrated discrete-time competing risks with company-local chronological validation, peer partial pooling, posterior intervals and an automatic abstention when the model does not beat role base rates.
Forecast hiring ramp capacity
Forecast an aggregate hiring plan with a locally calibrated hierarchical lognormal ramp-time model, Weibull productivity curves, correlated organization shocks, mentor-load displacement, commitment risk, and discounted capacity economics.
Forecast knowledge continuity semimarkov
Forecast critical code-knowledge continuity with a company-local hierarchical Bayesian semi-Markov model whose state-exit hazard depends on time already resilient, concentrated, orphaned or recovering; require a strict latest-period holdout improvement over persistence, simulate coherent common shocks, and expose orphaning, delay, recovery-cost and portfolio VaR/CVaR without predicting named departures.
Forecast onboarding time to autonomy economics
Forecast remaining time-to-autonomy and delay-cost tails with a company-local right-censored, partially pooled log-normal AFT model that must beat a global baseline on the latest whole cohort.
Forecast org health operating loss
Prove whether the company-local organization-health score leads later delivery, reliability and capacity losses, then simulate their correlated economic tail only after a latest-whole-period baseline challenge passes.
Optimize focus coordination policy portfolio
Choose aggregate async, meeting-batching, protected-focus or coordination policies using prospectively identified effects shrunk by design reliability, common scenarios, unique shared loss, Pareto search and hard budget, capacity, response, focus, timezone and CVaR gates.
Optimize knowledge resilience portfolio
Choose one baseline, cross-training, paired-review, rotation, documentation or backup-owner posture per critical knowledge unit using prospectively identified transport-weighted Beta-binomial relative-failure effects, contributor-availability and common-loss scenarios, exact or disclosed beam search, mentor/learner capacity, budget, expected-failure, CVaR and Pareto constraints.
Optimize onboarding mentorship portfolio
Choose an interference-aware mentorship portfolio using only prospective controlled effects, reliability shrinkage, common autonomy scenarios, unique shared loss, mentor capacity, service gates, CVaR and exact-or-disclosed beam search.
Optimize org health intervention portfolio
Select an anti-Goodhart intervention portfolio using conservative causal lower bounds on real operating loss, never score movement, with design/transport/fidelity shrinkage, negative controls, interference, shared-loss, equity, resource and CVaR constraints.
Optimize retention interventions by principal strata
Estimate who an optional retention intervention can actually help—not merely who looks likely to leave—from randomized principal strata, then allocate scarce capacity by conservative net value under harmed-stratum sensitivity, budget and fairness constraints.
Optimize stochastic flow control MPC
Optimize the next delivery-flow control with stochastic receding-horizon model-predictive control, serial queue dynamics, calibrated arrival and capacity scenarios, expected/CVaR cost, switching limits, exact sequence search, and a disclosed beam-search fallback.
Stress test knowledge resilience
Simulate partial-mastery knowledge coverage under individual and correlated team shocks, attribute continuity criticality, and optimize cross-training under money and capacity constraints.