Service Coverage and Shortfall Hours Calculator

Worked example

A service team can identify how long assessed coverage fell below its target. Keep zero-demand intervals and missing coverage separate from the measured shortfall.

In the fictional exercise, the service meets 80 of 100 requests overall. It falls below the 80% target for two hours. One hour has no demand and is counted separately.

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.

Overall demand coverage 80 %
Hours in known intervals averaging below target 2 hours
Hours with assessed coverage 5 hours
Hours with no demand 1 hours
Hours with missing data 0 hours

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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.

Save comparison inputs on this device until I clear them

Executive brief and reproducible export

Public exercise notes

Review for personal, confidential or sensitive material before saving or sharing. No automatic submission occurs.

Read the generated brief

Method, inputs and limits

Summarize demand-weighted coverage and hours below a declared minimum across a service interruption. Method version 0.2.0. Infer individual outcomes, fill gaps in observations, or identify the cause of a shortfall.

CORE-024 input dictionary
Input	Unit / type	Required interpretation
periods — Disjoint service intervals	hours and matching service units / number	Each row has hours, demand and served. Null means unknown. Optionally supply startAt and endAt as ISO timestamps on every row to verify duration, overlap and gaps. Any row unit must match the declared service unit.
target — Minimum interval coverage	fraction / number	Enter 0.8 for an 80% interval target.

Visible mathematics / decision rules

Overall coverage = sum(served) ÷ sum(demand) for a complete series with positive demand.

Below-target interval hours = sum of interval hours with positive demand and average coverage below target.

What this result cannot establish

Interval totals describe average coverage within each interval. They provide no information about changes inside an interval.
Missing or zero-demand intervals remain separate from the below-target total. Any gap between dated intervals counts as missing data.

What would falsify the assumptions?

Compare the declared disjoint intervals with verified intake and service records.
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",
    "origin": "synthetic",
    "sources": [
      {
        "id": "SYN-024",
        "kind": "synthetic",
        "label": "Fictional continuity exercise",
        "url": null
      }
    ],
    "periods": [
      {
        "hours": 2,
        "demand": 80,
        "served": 60
      },
      {
        "hours": 3,
        "demand": 20,
        "served": 20
      },
      {
        "hours": 1,
        "demand": 0,
        "served": 0
      }
    ]
  },
  "parameters": {
    "target": 0.8
  }
}

Expected checks

{
  "overallCoverage": 80,
  "belowTargetHours": 2,
  "noDemandHours": 1,
  "unknownHours": 0
}

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Authoritative background references

NIST: Cybersecurity Framework 2.0 — Outcome taxonomy, not a calculated national risk score. Reviewed 2026-11-09. Reference, not endorsement or validation.
UNDRR: Sendai Framework monitoring — Country-reported indicators have coverage limits; no causal program effect is inferred. 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.

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