Infrastructure for Predictive Employee Attrition/Turnover

Whether operational knowledge is systematically recorded

• Longitudinal employee data capture must cover engagement survey responses, performance rating histories, manager change events, and compensation adjustment records with consistent employee identifiers across systems

How explicitly business rules and processes are documented

• Attrition event schema must formally define what constitutes a voluntary departure, involuntary termination, and internal transfer to prevent label leakage in training data

How data is organized into queryable, relational formats

• Feature schema for attrition signals (tenure brackets, promotion velocity, survey score deltas) must be versioned and stable across model retraining cycles

Whether systems share data bidirectionally

• Cross-system integration between HRIS, performance management platform, and engagement survey tool must resolve employee identifiers and align event timestamps

Whether systems expose data through programmatic interfaces

• Model output access controls must restrict individual risk scores to authorized HR business partners and managers, preventing self-fulfilling prophecy through inappropriate disclosure

How frequently and reliably information is kept current

• Model retraining cadence must be governed with drift detection thresholds, since attrition patterns shift materially after organizational restructuring or market shocks