Serial service bottleneck

Worked example

A food distribution team can compare loading, transport and receiving on one serial route. Use the parallel delivery calculator when shipments can take different routes.

Finds the smallest capacity in a required serial chain and all tied limiting stages.

Try it yourself

The calculator opens with the fictional example already filled in. Change one input, choose Calculate locally, and compare the result to the original values below. Use Reset fictional fixture to start over.

An unknown result means the available inputs do not support a value. Check the calculator’s Warnings tab for what is missing or uncertain.

Effective serial ceiling 80 requests/day
Serial upper bound including rated capacity 80 requests/day
Supported service ceiling 80 requests/day
Unmet demand at ceiling 20 requests/day
Demand coverage ceiling 80 %

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Calculator

Approach (label only)Changing the label does not improve capacity, speed, error rates or confidence. Enter measured differences explicitly.

Comparison conditions and human review

Equal-resource comparison conditionsRecord budget, staffing, resources, information release dates, scenario conditions and evaluation criteria. Material differences can make options not comparable.

Evaluation period

Geography / exercise boundary

Human reviewers and roles

This evaluation depends on a real transaction

Supplied human authority gateThis declaration is not legal certification. Blocked, pending or assumed gates stop transaction-dependent evaluation.

Keep units consistent within each table. Enter zero when the amount is known to be zero. Leave optional amounts blank when they are unknown. If a required value is missing, the calculator will ask for it.

Advanced: complete input envelope and optional fields

Edit optional fields using the method dictionary. Apply validates and recalculates the entire input. Unknown values remain null.

Versioned input JSON

Import local JSON or CSV

Files stay in this browser. Maximum 1 MiB. JSON imports are recalculated. CSV supports flat observation tables, with column types taken from the displayed fixture. Empty cells become null.

Workbench JSON / input envelope

CSV target table

CSV file, matching the target table headers

Compare the arrangements

Keep physical resources and evaluation conditions equal. With identical inputs, all three approaches produce identical arithmetic. The comparison refuses material differences in declared conditions; it does not verify those declarations.

Show only differing metric rows

Privacy: comparison inputs may contain sensitive notes or operational details. Storage is off by default. Do not enter personal records or sensitive infrastructure details. Reproduction exports include supplied inputs and notes, including raw small-cell inputs suppressed from CORE-009 result tables. Suppression of displayed results does not make a reproduction export safe to publish.

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Executive brief and reproducible export

Public exercise notes

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Read the generated brief

Method, inputs and limits

Finds the smallest capacity in a required serial chain and all tied limiting stages. Method version 0.2.0. Schedule queues, model parallel paths, infer completions or guarantee service.

CORE-002 input dictionary
Input	Unit / type	Required interpretation
demand — Demand during the declared period	observations.unit / number	Use the supplied schema and declared units. Minimum 0.
period — Common capacity period	text / text	Use the supplied schema and declared units.
stages — Required serial stages	observations.unit / json	Rows require id, label, capacity and matching unit. If measuredAvailability is a fraction from 0 to 1, capacity is rated and adjusted. Null means rated with unknown availability. Omit measuredAvailability when capacity already represents usable throughput.
topology — Topology (serial only)	text / text	Use the supplied schema and declared units.
changedStage — One hypothetical stage change	matching capacity units / json	Optional parameters.changedStage with id and effectiveCapacity. Shows the change at the same demand.

Visible mathematics / decision rules

effective capacity = rated capacity × measured availability when supplied; serial ceiling = min(effective stage capacities)

supported service = min(demand, theoretical ceiling)

unmet demand = demand − supported service

What this result cannot establish

Bounded implementation from supplied acceptance checks and restored CORE definitions; scope choices are explicit below.
Arithmetic assumes every service unit passes through every stage in the same declared period.
Capacities must use matching throughput units and period. Adjustment assumes measured availability applies to that same period and service mix. Parallel paths, rework and travel time need a different model.
A manual minimum produces the same answer; this ceiling is not observed completion.

What would falsify the assumptions?

The result fails if a required stage or shared constraint is absent.
Independent observed throughput above the ceiling contradicts a supplied capacity or serial assumption.
No physical flow is generated: supported service cannot exceed demand or any stage capacity.
Calculate the stage minimum manually.
This is a theoretical arithmetic bound, not a forecast or causal estimate.
MAR adds no benefit if manual capacity review is equally accurate, and adds risk if it obscures omitted constraints.
Assumptions fail if the supplied definitions, units, period, scope or source records are wrong or incomplete.
An independent source audit or replication may contradict an input or the recorded dependency.
This method creates no resources. Physical conservation is checked in the inventory and transfer ledgers; descriptive graphs and checklists are not resource-flow models.
The same equations and review checklist can be reproduced with a spreadsheet or structured human-only process.
This is deterministic arithmetic, a descriptive comparison or a structured governance check, not a fitted causal effect or forecast. Fictional inputs remain an exercise.
Equal or worse measured errors, net review effort, disclosure burden or fallback under MAR would show no added benefit or added risk; no improvement is assumed.

Reproducible fictional fixture and independently calculated expectations

This fixture is synthetic. It does not describe a country, government, company or event.

{
  "observations": {
    "unit": "requests/day",
    "origin": "synthetic",
    "sources": [
      {
        "id": "SYN-001",
        "kind": "synthetic",
        "label": "Fictional serial service chain",
        "url": null
      }
    ],
    "period": "one declared day",
    "demand": 100,
    "stages": [
      {
        "id": "intake",
        "label": "Intake",
        "capacity": 120,
        "unit": "requests/day"
      },
      {
        "id": "review",
        "label": "Review",
        "capacity": 80,
        "unit": "requests/day"
      },
      {
        "id": "delivery",
        "label": "Delivery",
        "capacity": 90,
        "unit": "requests/day"
      }
    ]
  },
  "parameters": {
    "topology": "serial"
  }
}

Expected checks

{
  "theoreticalCeiling": 80,
  "supportedService": 80,
  "unmet": 20
}

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Authoritative background references

U.S. GAO: Cost Estimating and Assessment Guide — Published 12 March 2020. Estimation and sensitivity guidance; no endorsement of this implementation. Reviewed 2026-11-09. Reference, not endorsement or validation.

These sources inform definitions or review practices. They do not validate this implementation or endorse MAR.

Open the original Scenario Studio Examine original hypotheses Find related policy modules