Find where work stops moving, and say what it costs to leave it there. Report capacity from observed throughput rather than a theoretical rate. Never report a cost improvement without the metric that moved against it.
The Role Pack contains the method. The canonical profile contains the governed capability boundary. They reference each other without duplicating ServAI Core.
Identify bottlenecks from where waiting accumulates rather than from where volume is highest.
Compare committed load against capacity derived from observed throughput.
Report cost per unit alongside lead time and error rate so the trade-off is visible.
Detect handoff stalls by pair rather than by step, and never name an individual as a bottleneck.
Decompose late delivery by cause and step, reporting the unexplained share.
Forecast arrivals from at least two cycles of history and give headroom by period.
Report failure causes as a Pareto and refuse where coding quality is too poor to read.
Report inventory cover both ways: stock-out risk and dead stock.
Every method maps to a registered capability the profile can actually prepare or recommend. Repeating a precondition sentence is not evidence.
operations.bottleneck.queue_analysisArrival rate, service rate and queue length per step. The bottleneck is where waiting time accumulates, not where the most work happens.
operations.capacity.load_vs_availableCommitted load against available capacity per period, with capacity from actual observed throughput rather than a theoretical rate.
operations.cost.per_unit_with_tradeoffCost per unit alongside the metrics that move against it — queue length, lead time, error rate — so the trade is visible in one place.
operations.handoff.stall_detectionTime between one step completing and the next starting, by pair, so a handoff that stalls is visible as a pair rather than a step.
operations.delivery.on_time_root_causeDecompose late deliveries by cause category, each traced to a step, with the share unexplained reported rather than absorbed.
operations.demand.forecast_for_capacityForecast arrivals from the arrival series' own seasonality, then compare against observed throughput to give headroom by period.
operations.quality.pareto_root_causeFailures by cause, cumulative share, with each cause traced to the step it arises in.
operations.inventory.reorder_exposureCover in days from consumption rate against on-hand and on-order, both ends: stock-out risk and dead stock.
The Role Pack cannot grant itself authority. The shared resolver binds only what the profile, organization, tools, data classification and human policy permit.
Choose from 1,000 named connector routes. Every connection remains tenant-specific, least-privilege, admitted and health-gated; write authority is never implied by catalogue presence.
ServAI proposes the exact role manifest. Your people review the profile, data scope, tools and approval path before anything becomes active.
This is a separately entitled cross-industry Role Pack. It can join an Industry Pack mission only when the organization owns both entitlements.