Decision-grade rigor
Confidence intervals, effect sizes, and lift estimates tied to business thresholds—so leaders can act with clarity.
Validated measurement + modern data science. Decisions you can defend across hiring, performance, engagement, retention, and org design.
Start a People Analytics ProjectConfidence intervals, effect sizes, and lift estimates tied to business thresholds—so leaders can act with clarity.
DIF/bias checks, model cards, and auditable pipelines. Human + AI workflows with explicit guardrails.
Lightweight ingestion, templated dashboards, and incremental rollouts—value in weeks, not quarters.
Construct clarity, factor structure (EFA/CFA), reliability (α/ω), IRT scaling, and interpretable score bands.
Explainable models, parity audits, versioned features, and transparent governance embedded end-to-end.
Executive briefs, tech appendices, action guides, and runbooks aligned to your cadence and ownership.
Metrics wired to revenue, quality, cycle time, and risk—so change management earns fast internal buy-in.
Score calibration, pass-rate analysis, adverse-impact review, utility modeling, interview/screener validation.
Implementation process →Role KPIs, manager/peer calibration drift, leading indicators tied to output, quality, and customer outcomes.
Methods →Validated survey design, driver analysis, and team-level action guides grounded in practical effect sizes.
Case snapshots →Survival analysis, risk cohorts, opportunity mapping for internal moves, mentorship, and career pathways.
Toolstack →Span-of-control health, scenario planning, budget-sensitive staffing models linked to demand and SLAs.
Implementation process →Construct mapping, EFA/CFA, reliability (α/ω), IRT, DIF/fairness checks, score norms and interpretability.
Uplift modeling, panel/DiD, multilevel/hierarchical, survival/hazard, interpretable ML with SHAP/ICE.
A/B and multivariate tests, power analysis, sequential monitoring, guardrail metrics and risk bands.
Bias audits, privacy by design, model cards, versioned data dictionaries, decision logs and approvals.
ATS/HRIS/CRM exports, survey platforms, product and finance signals; lightweight ELT + schema harmonization.
Python/R pipelines, reproducible notebooks, validation reports, scheduled jobs where beneficial.
KPI views with uncertainty bands, driver drill-downs, cohort trends, and role-based access patterns.
Executive brief, technical appendix, survey/assessment tech-pack, operational runbooks and handoffs.
Score-based thresholding increased quality-of-hire index by 14–22% at constant pass rates, with zero flagged DIF.
Manager clarity + task autonomy explained 31% of variance; action plans reduced regrettable attrition by 6 pts.
Span-of-control tuning lowered cycle time 9–12% while holding budget neutral through redeployments.
Clarify decisions, success criteria, constraints, and required signals; define a minimal viable metric set.
Ingest sources, map entities, run quality checks, validate measures for reliability, fairness, and stability.
Fit interpretable models, quantify effect sizes, and link findings to practical actions and thresholds.
Ship dashboards, action guides, runbooks; institute review cadence, decision logging, and model stewardship.
Typical starts: HRIS/ATS exports, survey CSVs, plus performance or ticketing data. Minimal viable inputs are fine to begin.
Every relevant metric/model is parity-checked; you receive documentation and mitigation recommendations.
File-based transfers or secure connections supported. No production changes required to start discovery work.