---
title: "How to validate every statistic in a proposal"
description: "Trace each figure to its population, period, denominator, method and source, then verify its calculation, wording, permission and currentness."
canonical: "https://zephior.com/insights/validate-proposal-statistics-before-submission"
last-updated: 2026-09-02
---

# How to validate every statistic in a proposal

> Trace each figure to its population, period, denominator, method and source, then verify its calculation, wording, permission and currentness.

By [Tony Kim](https://zephior.com/authors/tony-kim). Published 2026-09-02; updated 2026-09-02. 12 minute read.

## Definition

Proposal-statistic validation is the controlled check that a quantitative statement reproduces or derives correctly from an authorized source, describes the same population, geography, period, unit and measure as that source, communicates uncertainty and limitations needed for interpretation, and remains current and permitted for the intended buyer. It covers values in prose, tables, charts, captions, case studies, summaries and attachments. Validation asks both whether the arithmetic is correct and whether the resulting sentence is fit for the claim being made.

## Problem

Numbers acquire authority as they move through a proposal. A percentage copied from a case study loses its denominator. A market figure comes from a search snippet rather than the cited report. “Reduced by 20 percent” becomes “20 percentage points.” A median turns into an average. A pilot result becomes a product-wide performance rate. The same number appears rounded three different ways across narrative, chart and executive summary. A client-approved metric is reused after its measurement period or permission expires. Every individual edit looks small; together they can make a persuasive claim materially false, impossible to reproduce or inconsistent at evaluation.

## Point of view

Give every material number a claim record before polishing it. Preserve the original statement and source location, then capture population, sample, geography, period, unit, statistic, numerator, denominator, exclusions, method, uncertainty and permission. Reproduce the calculation independently and test whether the proposal grammar matches what was measured. Keep one approved display value and link every occurrence to it. Apply deeper review to figures that affect eligibility, promised performance, safety, compliance, customer outcomes or contract economics. If the source cannot support the sentence, narrow the sentence or remove the number.

## Find the numbers that ordinary proofreading misses

Inventory more than digits. Search for written numbers, percentages, ratios, ranges, dates, durations, currencies, units, ranks and sample sizes. Include quantified adjectives such as “half,” “double,” “majority,” “top three,” “fivefold,” “near zero” and “industry-leading.” Inspect axes, legends, icons, callouts, alt text, footnotes and filenames. A chart can carry a material result that never appears in body copy. A section heading can say “30 percent faster” after the paragraph was corrected to 18 percent.

Classify each figure by origin and consequence. Published third-party statistics need authority, date, applicability and citation. Internal operating metrics need a stable definition, source system and approved extraction. Client case-study results need measurement detail, contractual or client disclosure permission and contextual limits. Derived figures need a reproducible calculation. Estimates and forecasts need assumptions and uncertainty. Targets need an authorized future commitment and measurement plan. Buyer-provided values should be attributed and not silently recast as bidder facts.

Assign one statistic ID across all appearances. The record lists source wording, approved proposal wording, display value, full-precision calculation if relevant, owner, approver, expiry and every response location. This prevents an executive editor from updating prose while the old chart survives. It also separates two superficially similar values, such as annual transactions for the whole service and eligible transactions in the proposed automation scope. Shared units do not make quantities interchangeable.

**Statistic classes and primary controls**

| Class | Primary question | Required control |
| --- | --- | --- |
| External publication | Does the source support this use? | Primary source, date, scope and citation |
| Internal metric | Is the definition stable and approved? | Query or report, owner and extraction date |
| Client result | Can it be disclosed and generalized? | Permission, method and relevance boundary |
| Derived value | Can another reviewer reproduce it? | Inputs, formula, conversions and rounding |
| Estimate or forecast | Which assumptions and uncertainty apply? | Range, scenario, basis and authority |
| Target | Who authorized the commitment? | Baseline, metric, owner and measurement plan |
| Buyer value | Is it a buyer fact or bidder assumption? | Exact source and unchanged definition |

## Reconstruct the population, denominator, method and time period

Open the full source at the exact table, page, query or approved record. Capture what was measured, the eligible population, observed sample, geography, baseline and comparison periods, unit, statistic, numerator, denominator, missing-data treatment and exclusions. Record whether the result is raw, seasonally adjusted, weighted, normalized or modeled. A “4 percent error rate” is not interpretable until the reader knows whether the denominator is documents, fields, transactions or audited samples and whether repeated errors within one item count once or many times.

Check time semantics. Publication date is not observation period. A 2026 report may present 2024 data. A twelve-month total is not a monthly run rate, and annualizing one high-volume week needs an explicit seasonality assumption. Check geography and entity. A regional subsidiary’s performance cannot automatically represent the group. Check system boundaries. A platform uptime figure may exclude scheduled maintenance, third-party services or customer-controlled components. Those definitions determine what the proposal may say.

Use the source most capable of supporting the claim. A search result, press article or vendor summary can lead to evidence but should not replace an available primary publication. Inspect revisions and footnotes. Statistical series may be rebased; case-study figures may be superseded; internal dashboards may apply current logic retrospectively. The Office for National Statistics defines statistical quality in terms that transfer well to bid review: relevance, accuracy and reliability, timeliness, clarity, coherence and comparability. A number can be arithmetically correct and still fail the intended comparison.

- Capture observation period separately from publication date.
- Name population, sample, geography, entity and system boundary.
- Preserve numerator, denominator, unit and missing-data rule.
- Record adjustments, weighting, exclusions and uncertainty.
- Check whether a newer source revised the value or definition.

## Recalculate the number and test every word around it

Reproduce each derived value from controlled inputs. Check signs, units, order of operations, filters, grouping, duplicates and missing values. For a rate, recompute numerator divided by the correct denominator. For change, calculate both absolute and relative forms and choose the one stated. A rise from 20 percent to 25 percent is 5 percentage points or 25 percent relative growth, not “a 5 percent increase.” For an average, identify mean, median or another measure. For a range, confirm whether bounds are observed minima and maxima, confidence limits, percentiles or scenarios.

Preserve full precision in the calculation record and approve one display rule. Round once at presentation, not at every intermediate step. Check whether comparison values were rounded under the same rule. Avoid a sentence whose arithmetic appears false because chart labels and narrative use inconsistent precision. Conversions require source unit, target unit, factor, factor date and owner. Currency conversion also needs the chosen rate basis and date, but validating tender price itself remains part of the commercial pricing control.

Test the grammar. “Of respondents,” “of all customers” and “of completed cases” name different populations. “Up to” describes a bound, not a typical result. “Average saving” may falsely suggest every client achieved it. “Proven” can overstate an observational association. “Independent” requires an independent source or method. “Benchmark” needs a comparison population. Check the claim-support direction: the source must entail the proposal sentence, not merely discuss the same topic.

Apply consequence-based assurance. An analyst may verify an ordinary contextual market statistic. The authorized service owner should approve an operational performance claim. A named client result needs the case-study owner and disclosure authority. A safety, regulatory, financial-capacity or contractual service-level number may need specialist and executive review. The updated AQuA Book distinguishes verification of correct execution from validation that analysis is fit for its intended use. Both are necessary when an evaluator may rely on the result.

**Common quantitative wording errors**

| Source fact | Unsafe wording | Controlled wording |
| --- | --- | --- |
| 20% to 25% | Increased by 5% | Increased by 5 percentage points |
| Median of tested cases | Average for all customers | Median among the tested cases |
| Pilot in one region | Product-wide performance | Observed in the named pilot scope |
| Upper observed result | Customers achieve this result | Result reached in the cited setting |
| Modeled scenario | Measured saving | Estimated under named assumptions |
| Survey respondents | All market participants | Respondents to the cited survey |

## Keep the approved meaning intact across text, charts and submission files

Validate the visual claim, not only the underlying cell. Check axis origin and scale, intervals, category ordering, area and icon proportionality, labels, color meaning, sample size and uncertainty. A truncated axis can magnify a small difference; a three-dimensional shape can make area look like quantity; a cumulative line can be mistaken for a period rate. The caption should state measure, population, period and source succinctly. If a chart compares unlike methods or periods, explain the break rather than smoothing it away.

Provide citations that let the evaluator find the evidence. Name publisher or owner, title or record, publication or extraction date, exact table, page or section, and a durable link or controlled attachment where permitted. Confirm that the evaluator can access the source and that the cited location still contains the value. Do not cite a home page for a specific statistic. For confidential evidence, follow the disclosure rules and give the buyer the authorized route instead of exposing the source in a public appendix.

Edition 3.0 of the UK Code of Practice for Statistics emphasizes suitable sources and methods, assured production, openness about strengths, limits and uncertainty, and clear presentation. Proposal teams are not producers of official statistics merely because they cite the Code. The principles are useful as a release challenge: is the figure relevant, based on an appropriate source, checked, explained honestly and presented so it cannot readily be misread? Avoid cherry-picking one attractive period or subgroup while concealing a materially different full result.

Freeze statistics by ID, then verify every occurrence in the final rendered package. Search again after executive edits, translation, pagination and chart export. Check accessibility text and linked spreadsheet cells. Record approval date, approved wording, permitted buyers or channels and expiry or next-review trigger. If a late amendment changes scope, volume or dates, reopen affected statistics. The end state is not “all numbers checked” as a status label. It is a set of reproducible claims whose meaning survives every place the evaluator encounters them.

- Check chart design for exaggerated or obscured comparisons.
- Use a citation that resolves to the exact supporting location.
- Communicate material uncertainty and limitations beside the claim.
- Reconcile every repeated value after final edits and translation.
- Reopen approval when scope, source, permission or currentness changes.

## Useful outcomes

- Every material statistic resolves to an accessible authorized source and exact location.
- Population, period, geography, unit, numerator and denominator remain visible where needed.
- Derived values are independently recalculated with assumptions and rounding recorded.
- Wording distinguishes count, rate, percentage, percentage-point change, average, estimate and target.
- All appearances of a statistic use one approved value and interpretation.
- Client permission, confidentiality, currentness and approval are checked before release.

## Workflow

1. **Inventory every quantitative claim.** Search prose, tables, diagrams, captions, footnotes, summaries and attachments for numbers, ranges, rankings, rates, quantified adjectives and chart labels.
2. **Reconstruct the claim record.** Capture exact source, location, population, period, geography, unit, method, numerator, denominator, exclusions, uncertainty, owner and disclosure permission.
3. **Verify source and calculation.** Open the primary material, reproduce arithmetic and transformations, check version and definitions, and reconcile conflicting or revised sources.
4. **Validate wording and presentation.** Test whether grammar, rounding, comparison, chart scale, caption and caveats convey exactly the supported result without broadening its applicability.
5. **Approve and freeze all occurrences.** Route consequence-sensitive figures to the right authority, link every use to the approved record and recheck the final rendered files after edits.

## Key decisions

- What exact quantity or relationship was measured, estimated or targeted?
- Who or what belongs in the population, sample, geography and time period?
- Which numerator, denominator, unit, statistic and exclusions produced the result?
- Is the proposal value copied, converted, aggregated, annualized or otherwise derived?
- Does the cited source directly support the sentence at the stated level?
- Which uncertainty, limitation or revision is material to buyer interpretation?
- Does the company have authority to disclose the value and identify its origin?
- Where else does the same statistic appear in the submission package?

## Risks

- A percentage may be detached from a small, selected or changing denominator.
- Relative change may be confused with percentage-point change.
- An average may conceal whether mean, median or another statistic was used.
- A pilot, region or client result may be generalized to all users or products.
- An external source may be secondary, revised, inaccessible or misquoted.
- Currency, time, volume or distance conversion may introduce an unreviewed assumption.
- A chart may imply a stronger comparison through scale, truncation or omitted uncertainty.
- An approved value may diverge across proposal copies after late editing.

## Metrics

- material statistics with complete claim records
- figures independently recalculated
- statistics with source version and exact location
- claims with denominator, period and population where material
- external figures verified against primary publication
- client metrics with current disclosure permission
- duplicate occurrences reconciled to approved value
- figures corrected or removed before release

## Frequently asked questions

### Does every number need the same depth of review?

No. Scale review to consequence and complexity. Give deeper independent and specialist assurance to eligibility, safety, compliance, promised performance, client outcomes and contractual commitments.

### Can we cite a statistic from a search result or news article?

Use it to locate the underlying source. Verify the full primary publication, definitions, period, revisions and exact support before citing it. If no suitable source exists, narrow or remove the claim.

### Should we include the denominator in the proposal?

Include it when scale, selection or interpretation could change the evaluator’s view. Always preserve it in the claim record even when space prevents showing every detail in the main sentence.

### How should translated editions handle numbers?

Use the same approved claim ID and value, then localize decimal, thousands, date and unit conventions carefully. Recheck that translated grammar preserves population, comparison and uncertainty.


## Primary sources

- [Code of Practice for Statistics, edition 3.0](https://code.statisticsauthority.gov.uk/wp-content/uploads/2025/10/Code-of-Practice-for-Statistics-3.0.pdf), UK Statistics Authority
- [Quality defined for official statistics](https://www.ons.gov.uk/methodology/methodologytopicsandstatisticalconcepts/qualityinofficialstatistics/qualitydefined), Office for National Statistics
- [AQuA Book guidance on analytical quality assurance](https://www.gov.uk/guidance/the-aqua-book), UK Government Analysis Function
- [Verification and Validation for the AQuA Book](https://www.gov.uk/government/publications/verification-and-validation-for-the-aqua-book), UK Defence Science and Technology Laboratory


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- [How to trace an RFP answer down to individual claims](https://zephior.com/insights/build-claim-level-rfp-traceability)
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