Predictive, explainable, and decision-grade analytics for the workforce you have—and the workforce you're building.
HR already has more data than most leaders realize—HRIS records, ATS funnels, engagement pulses, performance systems, payroll, learning platforms. HR World helps you turn that data into forward-looking signals: who is likely to leave, where engagement is slipping, which teams are outperforming, and where pay or development gaps actually exist. Every model we deliver is explainable, auditable, and safe to present to a board.
Built for the questions HR and operating leaders actually ask.
Role- and team-level attrition probability with driver attribution. Typical features include tenure, recent manager change, promotion recency, compensation percentile, engagement trend, commute, overtime, and learning activity. Built on transparent models (logistic regression, gradient-boosted trees) with SHAP-based explanations so managers can act without a data-science degree.
Headcount and capacity models that tie directly to operating plans and revenue targets. Scenarios for growth, hiring freeze, RIF, and re-organization. Integrates talent-market supply data to spot roles that will be hardest to fill and geographies that will be most expensive.
Pulse-survey and open-comment analytics using topic modeling and sentiment classification. Goes beyond aggregated scores to surface what employees are actually saying, by team and by manager, so interventions target the real issue—not the survey theme.
Representation dashboards across the hire-to-promote-to-exit funnel, plus regression-based pay equity that controls for legitimate factors. Paired with fairness audits of any predictive model we deploy to ensure it does not reinforce bias across demographic groups.
A disciplined, boring, auditable process. Nothing mysterious about it.
Decision you're trying to make; acceptable cost of being wrong.
Extract, integrate, and clean HRIS, ATS, payroll, LMS, and engagement data.
Start simple. Validate with holdout sets. Prefer explainable over exotic.
SHAP values, drivers, manager-facing summaries, fairness audit.
Dashboards, refresh cadence, governance, and monitoring.
People analytics without guardrails becomes a liability. These are the guardrails.
Data minimization, role-based access, and privacy-impact assessments aligned with GDPR, CCPA/CPRA, and applicable state consumer-privacy laws.
Every predictive model ships with a model card: purpose, data, features, performance, limitations, and known blind spots.
Regular bias testing across protected groups. Models that fail a fairness gate don't ship.
Target retention conversations where the signal is strongest; realistic programs aim for a 10–20% reduction in avoidable attrition for focus groups.
Team-level engagement and turnover patterns surface managers whose results diverge from peers—before the exit interviews pile up.
Identify unexplained pay differences after controlling for legitimate factors and deliver a concrete remediation plan.
Tie the operating plan to a headcount plan the CFO will sign off on—no spreadsheets-only forecasts.
A short diagnostic on your existing HRIS data will usually surface the three most actionable signals inside a few weeks.