PortfolioComputational Model
Computational Workforce Capacity
Workforce capacity as a computable model.
01 — Why
Nuvoraisnotastaffingportalbutacomputationalmodelofworkforcecapacity:sevenlayers,eachbuildingonthelast,turnpersonneldataintoreliableanswers—whatcapacityreallyexists,whatispermitted,andwhathappenswhenthingschange?
02 — Problem space
Capacityismorethanheadcount
01
Available does not mean deployable
Qualification, authorization, deployment context, recovery: real deployability is a multi-layered model — not a column value.
02
Decisions without reproducibility
Make a workforce decision twice and you often get two different results. A computable model makes them reproducible.
03
What-if remains gut feeling
What happens on absence, shifts, or new requirements? Without simulation, the answer stays speculation.
03 — How it works
Sevenlayers
Seven layers, each building on the one below. As you scroll, the model stacks up — exactly as it does in the architecture.
R1Layer 1 / 7
Semantics
What can be represented at all? The semantic foundation.
R2Layer 2 / 7
Eligibility
What is permitted? Rules and authorizations decide.
R3Layer 3 / 7
Readiness
What is true right now? The current state.
R4Layer 4 / 7
Capacity
What capacity actually exists? The computation.
R5Layer 5 / 7
Optimization
What should we do? The optimization.
R6Layer 6 / 7
Counterfactual
What happens if we do it? The simulation.
R7Layer 7 / 7
Execution & Memory
What actually happened? The system learns from execution.
04 — Architecture Contract
architecture.contract
01 R1 represents.
02 R2 decides.
03 R3 determines current state.
04 R4 computes capacity.
05 R5 optimizes.
06 R6 simulates.
07 R7 learns from execution.
Hypotheses are explicitly separated from proven statements.
Privacy and authorization are architecture, not a setting.
Specification depth is no proof of product maturity — evidence decides.