Enterprise Workforce Laboratory

A deliberately separate firm-level model

Economy-wide labor statistics describe the aggregate outcome of decisions, while enterprise systems record the administrative details of employment relationships. This project uses synthetic enterprise records, not confidential employer data, to demonstrate how those details can be modeled.

Enterprise semantic model

The model distinguishes people, employment spells, assignments, time-bound snapshots, compensation events, leave episodes, and applications. These entities represent different analytical units and should not be merged into a single generic employee table.

The diagram includes:

• Dimensions for person, job, organization, and date.
• Employment spell, assignment history, and workforce month-end facts.
• Compensation events, leave episodes, and recruiting applications.
• DAX measures for headcount, hires, separations, and workforce reconciliation.

Analytical questions

How sensitive is turnover to the selected separation events and denominator? How do month-end counts differ from exposure-based measures? What changes when a model uses employment spells and time-varying covariates rather than a one-row-per-person extract?

Modeling roadmap

The synthetic dataset is intended to support reproducible data-quality tests, descriptive dashboards, survival modeling, and predictive diagnostics. Any reported model performance will require actual fitted results and documented validation.

Status: Architecture under development. The diagram demonstrates structure; it does not claim deployed forecasting or prediction performance.