Capacity, staffing & flow

Size teams, route work, and find where the queue — not the people — is the constraint.

18 of 388 tools.

Allocate attention budget

Use exact knapsack optimization to allocate limited expert-review time by expected avoided loss.

Constrained optimization

Allocate capacity by marginal value

Allocate indivisible aggregate capacity across initiative-specific diminishing marginal-value scenario curves, activation thresholds, hard minimum commitments, unit cost, and portfolio CVaR with discrete next-unit value and explicit solver certainty.

Constrained optimization

Allocate capacity nash bargaining

Allocate discrete shared capacity by weighted Nash social welfare over concave team utility curves, with disagreement guarantees and a utilitarian counterfactual.

Constrained optimization

Calculate engineering runway

Compare three-point roadmap effort with three-point team capacity and expose unfunded commitments.

Decision analysis

Calculate hidden work tax

Translate unplanned work, rework, incidents, and coordination into capacity and cost leakage.

Decision analysis

Calculate shadow price of capacity

Calculate lumpy, discrete capacity shadow prices by re-optimizing a scenario-valued initiative portfolio after a governed increment to each resource, with CVaR penalty and explicit exact or heuristic solver status.

Constrained optimization

Estimate engineering learning curve

Estimate a team-fixed-effects power-law learning curve with work-size adjustment, cluster bootstrap uncertainty, and a defect-rate quality guardrail.

Statistical audit & measurement

Estimate team stochastic frontier

Estimate a Cobb-Douglas team production frontier with half-normal inefficiency, symmetric noise, conditional efficiency, and bootstrap uncertainty.

Statistical audit & measurement

Forecast feature adoption revenue

Forecast feature adoption, revenue, and contribution with a grouped discrete-time hazard model trained on reconciled censored cohorts, required to beat a pooled-hazard baseline on later cohorts before posterior and capacity-constrained forecasts are decision-safe.

Sequential Bayesian & bandits

Optimize capability transition network

Plan training and hiring as integral capacity flows through a time-expanded skill network, maximizing multi-period demand value net of transition cost and lead time.

Network & dependency analysis

Optimize global review assignment

Assign an entire review portfolio globally under expertise, conflict, capacity, urgency, quality, independence, and load-balance constraints.

Constrained optimization

Optimize queue staffing SLA

Invert an Erlang-C queue across weighted demand scenarios to find the lowest expected-cost staffing level that satisfies a wait-time SLA.

Constrained optimization

Optimize queueing network capacity

Choose minimum-cost integer capacity additions across a routed open queueing network using traffic equations, M/M/c waits, and exact budget dynamic programming.

Network & dependency analysis

Optimize sequence dependent roadmap

Optimize a dependency-feasible roadmap sequence under category setup time, execution duration and cost, aligned uncertain value, and exponential value decay, with bounded exact enumeration and visible heuristic fallback.

Constrained optimization

Optimize workforce policy tree

Optimize staged team/role capacity actions through uncertain demand by Monte Carlo backward induction.

Constrained optimization

Simulate delivery flow digital twin

Simulate delivery as a network of finite queues with stochastic arrivals, lognormal service, rework, WIP limits, and policy economics.

Network & dependency analysis

Solve robust multiobjective portfolio

Solve a budgeted dependency-safe portfolio against both scenario-probability ambiguity and every vertex of a bounded stakeholder-preference simplex, using governed utility anchors and returning practically nondominated supported tradeoffs.

Constrained optimization

Value dependency unblocking

Value shortening one blocker by propagating aligned duration scenarios through a dependency DAG, repricing earlier completion under task-specific value decay, and mixing unblock success or failure after cost.

Forecasting & survival

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