What this product does
The HR Capacity Model forecasts HR service load versus sustainable capacity across a planning horizon,
surfaces peak risk (worst-week utilization), and evaluates leadership interventions as scenarios.
It is designed for executive planning and governance review, not individual-level actioning.
Primary decision
Will HR demand exceed sustainable capacity, and what interventions prevent operational risk?
Key metric
Worst-week utilization, plus cumulative gap hours and role-period utilization
Sample artifacts
The files below demonstrate the artifact set produced by a validated run. These are examples for review.
They are aggregated and governance-safe.
Tip: If any links 404, confirm the folder names match your repo. GitHub Pages is case-sensitive.
Executive guide: how to read the sample artifacts
These outputs represent a validated HR Capacity Model run. They are intended to support leadership decisions
about sustainable HR capacity, timing of service pressure, and which interventions reduce operational risk.
They are not intended for individual employee actioning.
Start here: Scenario summary
File: scenario_summary.csv
- Worst-week utilization: the most decision-relevant metric. Peak overload drives service delays and operational risk more than average utilization.
- Total gap hours: cumulative demand that cannot be serviced within sustainable capacity. Proxy for backlog growth and delay risk.
- Interpretation: lower is better for both. Scenarios that reduce the peak usually reduce risk more than scenarios that only improve totals.
Then review: Utilization by role and period
File: utilization_by_role_period.csv
- Identify the constrained roles and timing patterns (short peak vs sustained pressure).
- Confirm whether interventions reduce load or shift burden to other roles.
- Leadership use: prioritize targeted capacity adds, sequencing changes, or demand moderation policies.
Totals
File: totals.csv
- High-level summary of aggregate demand vs sustainable capacity over the planning horizon.
- Use totals to explain magnitude. Use worst-week utilization to determine when it becomes operationally dangerous.
Manifest
File: manifest.json
- Governance and audit record: run metadata, input fingerprinting, resolved configuration hash.
- Declared governance constraints and prohibited uses to prevent misuse and ensure traceability.
- Leadership use: ensures results can be trusted and reproduced without spreadsheet drift.
Decision logic for executives
- Do we exceed sustainable capacity at any point in the planning horizon?
- Which scenario reduces worst-week utilization the most with minimal operational disruption?
- Does the scenario reduce pressure in the constrained role, or does it only shift burden elsewhere?
- Are the interventions realistic to execute and governance-safe in intended use?