canonical/modules/M067-charts-tables-and-evidence-design.md

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<!-- Module: 067 | Title: Charts, Tables, and Evidence Design -->

## PART XIV - RESEARCH COMMUNICATION AND MASTERY | MODULE 067

# Charts, Tables, and Evidence Design

> Mission. Use visuals to reveal relationships rather than decorate the narrative.

## Decision output

Objective: Use visuals to reveal relationships rather than decorate the narrative. The completed work product must be reproducible from evidence, show the downstream financial or decision effect when material, state the strongest contrary case, and define a dated update rule.

## Explicit operating procedure

1. Every visual must answer a decision question faster or more accurately than prose. Remove charts that merely decorate the memo.

1. Use consistent units, dates, scale, definitions, source notes, and axis treatment; disclose breaks in series and avoid truncated axes that exaggerate change without clear purpose.

1. Prefer driver bridges, cohort curves, scatterplots with economic interpretation, waterfall/reconciliation charts, and scenario tables over dense dashboards with no hierarchy.

1. Annotate material events and definition changes so correlation is not mistaken for causation.

1. Avoid dual axes unless the relationship truly requires them and labels/scales make interpretation unambiguous.

1. Design tables so reported, normalized, forecast, and scenario data are visually distinct and a reviewer can trace key numbers to sources.

## Required evidence and model bridge

- Primary-source set: investment memo, evidence pack, model outputs, monitoring dashboard, review and automation logs. Preserve exact document/version, date, period, and source location for every material factual input used in charts, tables, and evidence design.

- For each key concept - question-first visual choice, scales, denominators, annotations, uncertainty, source/date - state whether it is a reported fact, analyst calculation, management claim, external estimate, or judgment. Quantitative concepts must retain raw components and units; qualitative concepts must retain the specific evidence and counterevidence.

- Map only economically relevant findings into the model or decision record. Process-control modules such as charts, tables, and evidence design may have no direct valuation line; in that case document the downstream error or governance risk the control prevents.

## Metrics and calculation controls

| Metric / concept | Construction | Required validation |
| --- | --- | --- |
| source completeness | % of material claims and model inputs with complete source metadata, including document, date, page/section, and retrieval/version information. | source completeness: Audit a sample back to dated evidence and decision records; verify the stated threshold/score is reproducible by an independent reviewer and tied to a defined decision consequence. |
| denominator integrity | % of KPI/ratio calculations using a denominator that matches the numerator's scope, period, geography, cohort, and accounting definition. | denominator integrity: Recalculate independently from cited source data; verify definition, period, units, scope, signs, and any reconciliation to reported financial or operating totals. |
| question-answer speed | Elapsed time from a senior-review/IC question to a sourced, reconciled, decision-useful answer using the maintained research system. | question-answer speed: Recalculate independently from cited source data; verify definition, period, units, scope, signs, and any reconciliation to reported financial or operating totals. |



## Worked application

> Case: a truncated axis visually exaggerates a 100bp margin change.

- Reconstruct the relevant reported fact from primary evidence before interpreting the case. For charts, tables, and evidence design, show the raw components rather than only the resulting ratio or narrative.

- Build the causal chain through question-first visual choice, scales, denominators, annotations, then identify which link is directly observed and which link remains an assumption.

- Calculate source completeness, denominator integrity, question-answer speed from sourced components under the reported/base interpretation and at least one skeptical alternative interpretation.

- Translate the difference between cases into the variable that matters for charts, tables, and evidence design: evidence quality, revenue, operating profit/NOPAT, free cash flow, invested capital, financing/dilution, risk, or valuation. Mark non-applicable links instead of inventing them.

- Expert consistency test: use visuals to compress causal evidence, not decorate the memo.

- Precommit the specific future filing, KPI, customer/supplier observation, regulator action, or market input that would materially invalidate the charts, tables, and evidence design conclusion.

## Failure tests

- FAIL if question-first visual choice cannot be defined and reproduced from the source pack.

- FAIL if a visual omits units, period, source, definition, or uses scales and formatting that distort the economic relationship it is meant to show.

- FAIL if the charts, tables, and evidence design conclusion depends on an unstated assumption, unreconciled definition, or evidence that cannot be traced to its source/version.

- FAIL if evidence materially inconsistent with the charts, tables, and evidence design conclusion is omitted, reclassified, or dismissed without a documented definition, materiality, causal, timing, and source-quality analysis.

## Completion test

A senior reviewer must be able to reproduce the charts, tables, and evidence design conclusion, vary the most sensitive assumption independently, trace the change through the model, understand the strongest opposing case, and identify the next evidence that would force an update. If any link is missing, the module remains open.